How NTIA “Call to Action for 6G Leadership and Security” might influence 6G/IMT-2030 standards and 3GPP specifications

Posted on by Alan Weissberger

Introduction:

The U.S. National Telecommunications and Information Administration (NTIA) has launched the “Call to Action for 6G Leadership and Security,” a multilateral initiative uniting more than 20 like-minded governments to coordinate on a shared vision for open, interoperable, secure, and resilient 6G networks. While politically significant, the effort operates alongside—not in place of—the established technical standards ecosystem led by 3GPP and ITU-R, and its impact will hinge on closing critical supply-chain and participation gaps.

“The Call to Action for 6G Leadership and Security reflects an unprecedented level of international coordination on the future of communications technology,” said Arielle Roth, Assistant Secretary of Commerce for Communications and Information and NTIA Administrator. “Today’s action recognizes that 6G will be dramatically different from 5G, and that advancing U.S. and allied leadership requires a dramatically different playbook. By working now with trusted partners, we will ensure that next generation networks reflect our shared security interests, strengthen our competitiveness, and drive innovation. I am proud of the role NTIA has played in building this global partnership, and I look forward to seeing our shared commitments translated into meaningful action.”

NTIA is launching this initiative alongside more than 20 partner governments spanning Europe, the Indo-Pacific, and the Western Hemisphere. Through the Call to Action, participating governments have pledged to strengthen cooperation on 6G over the next 12 months and beyond in support of security, interoperability, and resilience in next generation networks. The initiative also recognizes that trusted artificial intelligence (AI) will be central to the development and operation of secure and innovative 6G networks for the United States and its global partners.

Initiative scope and strategic alignment:

The Call to Action explicitly advances the objectives of President Trump’s December 2025 Presidential Memorandum on “Winning the 6G Race,” which frames 6G as foundational to U.S. national security, foreign policy, and economic prosperity. Participating governments commit to strengthening cooperation over the next 12 months and beyond on security, interoperability, and resilience, with an emphasis on trusted AI as central to 6G operations. The document also stresses avoiding duplication with industry-driven standards bodies while exploring constructive interfaces with private-sector stakeholders.

 

Initial milestones include establishing government points of contact, engaging industry and academia, identifying barriers to leadership, and exploring ways to strengthen secure and resilient supply chains.

Membership composition and notable absences:

The coalition includes the United States and key advanced-economy partners with strong mobile capabilities and intellectual property portfolios—among them Finland, Sweden, Japan, and South Korea—alongside a broader set of allies across Europe, the Indo-Pacific, and the Western Hemisphere. However, several strategically important economies are not signatories, including India, Vietnam, and Taiwan, as well as Thailand, Malaysia, and Mexico.ntia+2

  • India and Taiwan participate in various Huawei-free supply initiatives but are not part of this specific Call to Action.

  • Vietnam maintains a cautious posture toward China and has pursued domestic 5G equipment development, yet it remains outside the current framework.

These absences matter because 6G security is only as strong as its end-to-end supply chain. A credible security posture requires participation from low- to medium-cost manufacturing hubs aspiring to grow their hardware sectors—an endeavor that demands coordinated reshoring and friend-shoring at scale.

Standards reality check – 3GPP and ITU-R WP5D remain responsible:

This NTIA led alliance is a high-level political and policy forum; it does not set 6G standards or specifications. The NTIA will likely shape U.S. positions and coordinate federal input so that U.S. industry contributions to 3GPP and ITU‑R reflect national security, spectrum, and innovation priorities. In practice, NTIA’s role is policy, spectrum, and interagency coordination, while the detailed 6G standards are produced by 3GPP and then submitted to ITU‑R WP5D for IMT‑2030 approval.  Technical standardization will continue to be driven by:

  • 3GPP Release 21, expected to deliver the first set of 3GPP 6G technical specifications and serve as the basis for IMT-2030 submission before 2030.

    • The Release 21 timeline is to be finalized by June 2026, with ASN.1/OpenAPI freeze no earlier than March 2029 (some industry views target end-2028).

  • ITU-R WP5D, which is developing the IMT-2030 framework and evaluation guidelines, and has opened a submission window for candidate Radio Interface Technologies (RIT/SRIT) from February 2027 to February 2029.itu+3

IMT-2030 RIT/SRIT submissions are expected to align closely with 3GPP Release 21 outputs. The Call to Action can help smooth policy disagreements and align security priorities, but it cannot override or replace these processes; at worst, it risks adding another layer of complexity or politicization if not carefully scoped.

How NTIA interfaces with 3GPP:

  • Policy and requirements feed‑in: NTIA gathers input from industry, academia, and other agencies (e.g., via its 6G Request for Comments and the Commerce Spectrum Management Advisory Committee) to inform the U.S. government’s 6G policy and priorities. Those priorities—open, interoperable, secure, and reliable architectures; public‑safety needs; and spectrum alignment—are then reflected in U.S. positions carried into 3GPP by U.S. standards bodies and companies.

  • Standards‑body channel via ATIS: In 3GPP, the U.S. Organizational Partner is ATIS. NTIA does not sit inside 3GPP as a member, but it works with ATIS and U.S. stakeholders to ensure that federal requirements (e.g., for public safety, security, and spectrum harmonization) are represented in 3GPP work items and technical reports. For example, the FirstNet Authority (working under a congressional mandate) actively participates in 3GPP to advance public‑safety requirements into 5G‑Advanced and 6G.

  • Spectrum and R&D alignment: NTIA’s National Spectrum Strategy and federal R&D programs are designed to make sure that the bands and research directions needed for 6G are available and de‑risked before 3GPP locks in key radio and system designs. This indirectly shapes what is feasible in 3GPP Release 21 (the expected first 6G release).

How NTIA interfaces with ITU‑R WP5D (IMT‑2030):

  • U.S. administration role in ITU‑R: NTIA is the U.S. administration for ITU‑R matters. It coordinates U.S. government positions, prepares proposals, and supports U.S. delegations at ITU‑R WP5D meetings, including WP5D’s work on IMT‑2030 (6G) RIT/SRITs.

  • Requirements and evaluation framework: ITU‑R WP5D defines the IMT‑2030 framework, minimum performance requirements, and evaluation guidelines for candidate 6G radio technologies (RIT/SRIT). NTIA helps ensure that U.S. views on security, resilience, spectrum, and public‑safety are reflected in these high‑level requirements and evaluation criteria.

  • From 3GPP specs to IMT approval: 3GPP develops the actual 6G technical specifications (expected to be completed around 2028–2029 for Release 21) and, through ATIS, submits them to ITU‑R WP5D as the primary IMT‑2030 candidate. WP5D then evaluates the candidates against its requirements and, if they pass, incorporates them into ITU Recommendations. NTIA’s role here is to coordinate the U.S. position on those evaluations and the resulting Recommendations, not to write the 3GPP specs themselves.

In summary NTIA influences 6G standards indirectly—through spectrum policy, federal R&D, interagency coordination, and U.S. positions in ITU‑R—while relying on ATIS and U.S. industry to carry those priorities into 3GPP’s technical work and into ITU‑R’s IMT‑2030 process.

Implications for 6G security and supply-chain resilience:

The new NTIA‑led Call to Action is a multilateral policy forum which could:

  • Align partner governments on shared security and interoperability principles that then inform national positions in 3GPP and ITU‑R.

  • Support supply‑chain and trusted‑AI initiatives that underpin secure 6G deployments, complementing the technical standards produced by 3GPP and approved by ITU‑R.

The initiative’s greatest value lies in creating a trusted, action-oriented forum to:

  • Coordinate on security-by-design principles, including open interfaces, interoperability, and resilience requirements that can feed into national procurement and regulatory frameworks.benton+1

  • Accelerate trusted AI integration into 6G network operations and management.ntia+1

  • Map and mitigate supply-chain vulnerabilities, especially for radio access network (RAN) components, semiconductors, and test/measurement ecosystems.

However, without bringing in pivotal manufacturing and assembly locations—particularly in South and Southeast Asia and Latin America—the alliance risks leaving the most exposed links in the 6G supply chain unaddressed.

From political alignment to measurable impact:

Given the proliferation of 6G alliances, the Call to Action must demonstrate tangible progress to remain relevant. Priority actions include:

  • Operationalize working groups within 12 months to produce concrete guidance on secure RAN architectures, AI-enabled operations, and resilience metrics.ntia+1

  • Bridge to standards work by channeling consensus positions into 3GPP and ITU-R via national standards bodies and industry coalitions, without duplicating technical workstreams.benton+1

  • Expand the circle by engaging non-signatory economies through targeted supply-chain and innovation programs, making participation economically attractive to members.

If executed with discipline, the Call to Action can reduce fragmentation, elevate security baselines, and de-risk the path to commercial 6G. If not, it may become another layer of diplomacy with limited effect on the technical and industrial realities that will define 6G.

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References:

https://www.ntia.gov/press-release/2026/ntia-launches-global-call-action-6g-leadership-and-security

https://www.ntia.gov/sites/default/files/2026-07/call-to-action-for-6g-leadership-and-security.pdf

https://www.lightreading.com/6g/new-us-6g-alliance-must-show-it-can-make-a-difference

Roles of 3GPP and ITU-R WP 5D in the IMT 2030/6G standards process

IMT-2030 (“6G”) Minimum Technology Performance Requirements for Radio Interface Technologies

ITU-R M.[IMT-2030.EVAL] & ITU-R M.[IMT-2030.SUBMISSION] reports: Evaluation & Submission Guidelines for 6G RIT/SRITs (6G)

ITU-R WP5D IMT 2030 Submission & Evaluation Guidelines vs 6G specs in 3GPP Release 20 & 21

ITU-R WP 5D Timeline for submission, evaluation process & consensus building for IMT-2030 (6G) RITs/SRITs

Comparing AI Native mode in 6G (IMT 2030) vs AI Overlay/Add-On status in 5G (IMT 2020)

AI wireless and fiber optic network technologies; IMT 2030 “native AI” concept

Verizon’s 6G Innovation Forum joins a crowded list of 6G efforts that may conflict with 3GPP and ITU-R IMT-2030 work

Highlights of 3GPP Stage 1 Workshop on IMT 2030 (6G) Use Cases

Ericsson and e& (UAE) sign MoU for 6G collaboration vs ITU-R IMT-2030 framework

Analysis: Cell Tower Companies (towercos) & market forecast with small cells in the lead

Posted on by Alan Weissberger

Over the last few years, mobile network operators all over the world generated cash to fund their 5G buildouts by selling cell towers [1.]. Private equity has also entered the market in this period, and consolidation is expected to continue. There are hundreds of smaller tower companies that could be aggregated into a company that could rival American Tower, if the private equity firms have a strong desire to invest in them.  They certainly have deep enough pockets.

Tower assets are monetized over multiple decades, in which the value is derived from the sum of its parts, rather than individual locations.  Because of this, the average revenue per tower is surprisingly low on an annual basis.

Note 1.  Cell Towers are telecommunications sites capable of transmitting 4G and 5G “New Radio” signals for wide-area coverage. They are typically 50 to 200 feet tall and designed to blend into the natural environment to limit the aesthetic impact.  5G cell towers use a combination of low, mid, and high-frequency bands for various connectivity use cases. For example, macrocell antennas can be installed on towers to efficiently deliver low-frequency cellular coverage to millions of devices over a large region. Low-band 5G can travel far distances and penetrate walls, windows, and other physical barriers.

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RAN Research expects the number of cell towers to increase, yet the revenue generated per tower is projected to decline.  For the towercos that post public data, the highest results are: ~$7,000 for China Tower, ~$13,000 for Indus Towers, to over $70,000 for American Tower.  However, these headline public figures only scratch the surface. The reality is far more complex: utilization varies dramatically, portfolios are a mix of owned and leased assets, and amortization reshapes how these towers should be valued. A $70,000 annual return, for example, is actually more like $1.4 million over a 20-year lifecycle.

The market research firm expects total annual tower revenue to reach $173.83 billion in 2031, up from roughly $120–$130 billion in 2026. While top-line revenues are climbing due to higher lease rates, the physical asset market (hardware and construction) is growing at a more measured pace—rising from $30.07 billion in 2026 to $34.3 billion by 2031 at a 2.67% Compound Annual Growth Rate (CAGR). This disparity highlights a major industry shift: the market is transitioning from rapid greenfield building toward maximizing co-location leasing, structural density, and secondary infrastructure monetization.

RAN Research’s analysis is based on determining an average revenue per tower in each of the regions and then applying this to the number of towers. It is focused on the large towers that support the wide area footprint of the macro cell network.  Asia is the biggest market, the firm says.

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The top 10 cell tower companies worldwide operate millions of macro sites combined. Led by state-backed giants and massive independent multinational operators, the largest owners include:

  • China Tower: The world’s largest cellular tower company, managing roughly 2.15 million sites exclusively across China. 
  • Indus Towers: Based in India and majority-owned by Bharti Airtel, operating over 259,000 towers. 
  • Altius (Brookfield-owned): A major Indian infrastructure operator managing around 257,000 sites. 
  • Summit Digitel: A massive digital communications infrastructure provider operating heavily in India with over 150,000 sites. 
  • American Tower Corporation (AMT): Headquartered in Boston, the largest international and independent tower real estate investment trust (REIT), managing nearly 149,000 sites across the U.S., Latin America, Europe, and Africa/APAC. 
  • Cellnex Telecom: Europe’s leading independent wireless telecommunication operator, managing over 100,000 to 138,000 infrastructure sites across 12 European nations. 
  • BSNL Tower Corporation: A state-backed Indian tower operator controlling tens of thousands of communication sites.
  • edotco Group: A pan-Asian regional tower infrastructure company owned by Axiata Group, operating over 50,000 sites across 9 countries. 
  • Vantage Towers: A prominent European tower infrastructure company spun out of Vodafone, managing upwards of 45,000 sites. 
  • Crown Castle: A major U.S.-focused infrastructure provider owning over 40,000 towers alongside an extensive footprint of small cells and fiber routes.

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Market Size & Projections (2026–2031) via Google Gemini:

The 2026–2031 forecast window marks the definitive shift of 5G infrastructure from macro tower builds to hyper-dense, street-level, and indoor deployments. Because high-frequency 5G mid-band and millimeter-wave (mmWave) signals struggle to penetrate buildings, the industry is relying heavily on small cells and neutral host operating models to solve the multi-carrier coverage puzzle economically. The global small cell networks market is projected to skyrocket from $37.14 billion in 2026 to $147.56 billion by 2031, expanding at a massive 31.74% CAGR.
Because market value is split between long-term leasing revenue and physical asset value, leading research firms evaluate the forecast through specific industry layers:

Market Layer / Sub-Sector 2026 Valuation 2031 Projected Valuation CAGR Primary Growth Catalyst
Global TowerCo Leases & Revenue ~$135 Billion $173.83 Billion ~5.2% Skyrocketing data consumption and Multi-tenant leasing
Physical Tower Assets & Hardware $30.07 Billion $34.30 Billion 2.67% Urban infill, macro-to-small cell handoffs
U.S. 5G Cell Towers Only $7.80 Billion $13.50 Billion 11.6% Mid-band spectrum densification, C-band rollouts
Tower Power Infrastructure $6.70 Billion $10.55 Billion 9.53% Off-grid expansions, hybrid lithium-ion & solar swaps

Core Growth Drivers:
    • 5G Standalone (SA) and Mid-Band Densification: The 2026–2031 window marks the peak expansion of 5G Standalone networks. Unlike early 5G, mid-band and millimeter-wave frequencies require dense infrastructure setups, compressing typical urban inter-site distances to under 0.5 miles. 
    • The Independent TowerCo Oligopoly Model: Telecom operators are aggressively divesting their physical tower portfolios to free up capital for spectrum licenses and core software upgrades. Independent TowerCos (like American Tower and Cellnex) are absorbing these sites, immediately optimizing them by adding multiple tenants per pole. 
    • Infrastructure Sharing (Co-location): To defend profit margins against heavy capital expenditures, operators are increasingly abandoning proprietary towers in favor of neutral host infrastructure sharing. Increasing the co-location ratio heavily expands TowerCo revenue without the cost of building new physical sites. 

Key Trends Transforming the Market:
💡 Revenue Diversification (Smart Towers)
Tower companies are transitioning from simple “dumb steel” landlords to integrated digital infrastructure providers. Throughout the forecast period, operators are retrofitting existing macro sites to house edge compute racks, EV battery-swap kiosks, and IoT gateways to maximize yield per square foot. 
🔋 The “Green Tower” Power Transition
Operational expenditure risks—primarily energy consumption and highly volatile diesel fuel prices in remote areas—are forcing a massive power overhaul. The telecom tower power system market is expanding quickly, with renewable-only installations projected to grow at a 16.45% CAGR through 2031 to hit carbon neutrality goals. 
🏙️ Rooftop & Stealth Deployments:
Zoning laws, land scarcity, and local municipal friction are making traditional lattice towers difficult to build. Rooftop deployments captured over 54% of new site footprints heading into 2026. Furthermore, aesthetically masked “stealth structures” (like camouflaged trees and flagpoles) are growing at double the rate of conventional monopoles. [1, 2, 3]
⚠️ Macroeconomic and Operational Headwinds:
    • Elevated Capital Costs: Higher long-term interest rates have widened bid-ask spreads for infrastructure transactions, making debt-fueled portfolio acquisitions more expensive and delaying consolidation. 
    • Regulatory Obstacles: Complex permitting timelines and local aesthetic restrictions continue to delay urban site construction, shifting near-term focus toward indoor small cells. 

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References:

https://www.anscorporate.com/blog/what-is-a-5g-cell-tower

Cell Tower Forecast 2026-2031 – Rethink

RAN-Research-Cell-Tower-Forecast-2026-2031-Executive-Summary-ec806.pdf

https://www.mordorintelligence.com/industry-reports/small-cell-network-market

 

 

Analysis: Huawei”s upgraded Xinghe Intelligent Network Solution for South Africa

Posted on by Alan Weissberger

The Huawei Network Summit 2026 South Africa concluded successfully in Johannesburg, drawing more than 400 industry leaders, technical experts, and ecosystem partners.  At the event, Huawei introduced its upgraded Xinghe Intelligent Network Solution for Southern Africa, now positioned under the “Secure and Intelligent Connectivity” framework.

The announcement underscores Huawei’s continued push to enable intelligent transformation across industries in collaboration with customers and partners.  As AI agents move from experimental deployments to mission-critical production environments, network requirements are shifting accordingly. Industry attention is increasingly moving beyond token consumption metrics to Daily Active Agents (DAA), reflecting the emergence of large-scale agentic AI adoption and the need for next-generation networks with stronger performance, resilience, and security.

Leon Wang, President of Huawei’s Data Communication Product Line, said: “Real-time AI interaction, multidimensional data flow, core business security, and other scenarios are driving networks to embrace an AI-centric paradigm shift. This marks a transition from ubiquitous ultra-broadband into a new journey defined by lossless computing power, integrated communication and sensing, full-scope security, and network autonomy.”

Powered by a next-generation intelligent network foundation, Southern Africa’s digital and intelligent transformation is entering a new phase, according to Huawei.

“Johannesburg is a vibrant city rich in opportunities, connecting talent, industries and cultures across Africa,” said Vincent Chen, Vice President of Enterprise Business, Southern Africa Region, Huawei. “Today, AI is becoming a key driver of global innovation, and its adoption in Africa is transitioning from pilot exploration to real-world deployment, accelerating intelligent transformation across sectors such as finance, education and public services. For the Southern African market, Huawei’s goal is to advance intelligence across industries by collaborating with industry partners to build intelligent, secure and reliable network infrastructure for the AI era.”

The rapid growth of AI agents is creating new use cases and requirements, placing unprecedented technical demands on network infrastructure.

“Today’s enterprise network infrastructure faces four major challenges on its path to digital and intelligent transformation. These include the ever-widening gap between computing supply and demand; traffic pattern shifts driven by AI agents; surging O&M complexity; and new AI-driven attacks compounding the vulnerabilities of new systems,” said Arthur Wang, Vice President of Huawei’s Data Communication Product Line. “To address these challenges, Huawei has upgraded its Xinghe Intelligent Network Solution under a new paradigm of ‘Secure and Intelligent Connectivity.’ The first is an intelligence upgrade, expanding AI beyond O&M into the entire network. The second is a security upgrade, advancing from single-point defence to end-to-end protection that deeply converges network and security. Through these two key upgrades, we aspire to build a solid connectivity foundation for every enterprise in the Agentic AI era.”

During the event, Huawei also unveiled its upgraded Xinghe Intelligent Network product portfolio and the Xinghe AI Cloud Campus SaaS Service Platform for Southern Africa.

Shi Lei, Vice President of the NCE Data Communication Domain of Huawei’s Data Communication Product Line, said:

“In the past, intelligent O&M was a luxury exclusive to large enterprises. Now, we have deeply integrated AI into the cloud management service platform, enabling SMEs to easily access these capabilities as a cloud service. This is more than tech inclusion; it is about making AI network services genuinely accessible, affordable, and actionable.”

Analysis & Opinion:

Huawei’s upgraded Xinghe Intelligent Network Solution for South Africa reflects a clear shift toward AI-native enterprise networking, with Huawei positioning the platform around “secure intelligent connectivity.” In practical terms, the upgrade extends AI beyond operations and management into the broader network fabric, while also tightening the convergence of networking and security across campus, WAN, data center, and security domains. The announcement also ties the solution to the broader “Agentic AI era,” which suggests Huawei is targeting workloads where connectivity, automation, and security need to operate together.

For South African enterprises, the strategic value is clear: AI adoption is pushing networks to support heavier east-west traffic, lower latency, stronger segmentation, and more autonomous operations. Huawei is effectively arguing that traditional, siloed infrastructure is no longer sufficient for production AI environments.  Instead, the network must become a more autonomous, security-aware control layer that can sustain business continuity and scale with intelligent services.

The solution is strategically relevant, but its real value will depend on execution: interoperability in multivendor environments, demonstrable performance gains, and local supportability. If Huawei can substantiate its claims with measurable outcomes and robust deployment references, Xinghe could be a compelling modernization path. Otherwise, it risks being viewed as another vendor-led repositioning exercise.

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References:

Huawei unveils upgraded Xinghe Intelligent Network for Southern Africa

Huawei’s AI-Centric Network Vision: Six Imperatives for the Next Decade; Critical Questions for IEEE Techblog Community

Huawei FY2025: 2.2% YoY revenue increase; strategic pivot to AI and intelligent automotive solutions

Huawei unveils AI Centric Network roadmap, U6 GHz products, 5G Advanced strategy and SuperPoD cluster computing platforms

Huawei, Qualcomm, Samsung, and Ericsson Leading Patent Race in $15 Billion 5G Licensing Market

Huawei Cloud Review and Global Sales Partner Policies for 2026

Omdia on resurgence of Huawei: #1 RAN vendor in 3 out of 5 regions; RAN market has bottomed

Analysis & Opinion: SpaceX to build, lease or buy a hybrid/terrestrial satellite network?

Posted on by Alan Weissberger

Should SpaceX’s Starlink build, lease/rent or buy a hybrid terrestrial/satellite mobile network or perhaps do it through a mix of these alternatives. Several industry watchers see an MVNO deal as the most likely path (we agree- see Analysis & Opinion below). That way SpaceX/Starlink can deliver reliable service indoors and out because it will have access to necessary low band and mid band spectrum, plus access to its own direct-to-device (D2D) service to cover areas out of reach of the terrestrial cellular network.  Some analysts suggest that SpaceX might try to exchange some of its spectrum for an MVNO agreement, or perhaps come up with some other means to achieve that goal.

“Starlink is playing the long game. It will continue to negotiate, cajole, and, if necessary, coerce, in an effort to secure an MVNO agreement with one of the Big Three,” MoffettNathanson analyst Craig Moffett said in a recent report (subscribers only) that sized up SpaceX’s options. “It is clear, however, that the Big Three (AT&T, Verizon, T-Mobile) fully understand the clear and present danger that would be posed by Starlink’s market entry as another Cable-like hybrid MNO/MVNO.”

Image Credit: Stephen Searle/Alamy Stock Photos

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A recent a Semafor report suggests the build and buy options are both being consdiered at SpaceX, kicking it off with a lead proclaiming that “Elon Musk is coming for your cell phone networks.”  The report said SpaceX is seeking spectrum that can deliver service in “cities and dense areas,” and is exploring some options to get there that include acquiring companies that already own spectrum or obtaining spectrum at auction.

“In the most recent sign that Musk’s Starlink plans to compete directly with AT&T, Verizon, and T-Mobile. Musk’s SpaceX has taken other steps into the conventional telecommunications business. President Gwynne Shotwell demonstrated a prototype mobile handset to some investors earlier this year, the Wall Street Journal reported. The Financial Times also reported that Shotwell had expressed interest in building their own terrestrial networks.”

“SpaceX wants to grow its Starlink mobile business, which analysts expect to hit $15 billion in revenue this year and which SpaceX, in its IPO pitch to investors, pegged at a $740 billion market. SpaceX is working on new technologies to improve Starlink’s coverage in tree-covered areas and inside buildings, and Musk has also said he’s considered building a hybrid satellite-terrestrial network to bolster the service.”

Elon Musk has kept the door open for SpaceX to attempt a takeover of an MNO in the future. Whether any would be willing to sell is a completely different discussion.

  • Roger Entner, analyst and founder at Recon Analytics, suggested that SpaceX’s fight over the upper C-band buildout rules indicates that it’s not shopping to acquire a wireless carrier. He said it shows that SpaceX “is a company that means to win spectrum at auction and build a satellite and terrestrial hybrid network on it from the ground up, the same way it built its own dish and its own router rather than buying either off a shelf.”
  • “The key thing to look at is where SpaceX can exert pressure on the MNOs at minimal cost to itself. I expect we’ll see more rumors of a Starlink phone & cable partnership. Perhaps even a CBRS purchase from EchoStar. But strict buildout timetable now makes upper C-band unappealing,” Tim Farrar, principal at TMF Associates, explained on X.

The Semafor report notes that SpaceX’s plans are fluid, and the company could ultimately choose not to follow through. Building a network is capital intensive, requiring continuous, steady investment in both towers and spectrum —- drawing capital away from businesses that investors more richly reward, chiefly AI.

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Analysis and Opinion (aided by Perplexity.ai):

 SpaceX is most likely to buy spectrum and selectively acquire/lease assets, rather then build a lean, satellite‑centric terrestrial layer — not buy a legacy carrier, and not build a Dish‑scale greenfield MNO.

This is a hybrid “buy‑then‑build” playbook: buy the airwaves (and maybe some small operators or tower portfolios) to secure optionality, then build only the terrestrial pieces that are economically justified, letting Starlink Direct‑to‑Device do the heavy lifting for coverage.

Why a pure “build” MNO is unlikely:

  • Capital allocation: SpaceX’s 2025 capex was already dominated by AI (~$18B in AI spend, with total near‑term IG funding needs around $300B before FCF turns positive). A full terrestrial MNO build would compete directly with that priority.

  • Strategic fit: SpaceX’s historical pattern is to design and build its own infrastructure, but only where it unlocks a new market or margin (rockets, satellites, user terminals). A retail MNO with dense tower grids and low ARPU is a different beast.

  • Regulatory reality: FCC rules for the EchoStar spectrum impose strict buildout and performance obligations, but they also allow blending space and ground infrastructure—exactly what a satellite‑first hybrid needs.

Why a pure “buy a carrier” is also unlikely:

  • No willing seller at the right price: Major carriers have rejected MVNO/wholesale overtures, and buying AT&T/T‑Mobile/Verizon is not realistic.

  • Asset mismatch: Legacy carriers come with large, costly tower grids and cost bases that a satellite‑terrestrial hybrid is designed to minimize.

The middle path: buy spectrum, build sparingly:

Evidence points to this as SpaceX’s actual strategy:

  • Spectrum first: The $17B EchoStar deal (AWS‑4, H‑Block, unpaired AWS‑3) gives SpaceX ~65 MHz of nationwide, exclusive, contiguous midband spectrum explicitly for direct‑to‑cell and hybrid services.

  • Auction strategy: SpaceX is expected to bid aggressively in the upcoming upper C‑band auction (3.98–4.14 GHz, 160 MHz) to secure urban capacity for a full‑service mobile offering.

  • Terrestrial as a complement: In dense areas, smartphones would connect to terrestrial base stations SpaceX plans to deploy; outside those zones, devices would switch to Starlink Direct‑to‑Cell. This keeps tower counts and capex manageable.

  • Selective M&A: Rather than buying a Big Three carrier, SpaceX is more likely to acquire spectrum‑rich smaller operators or lease/buy tower capacity where it accelerates coverage without a full build.

Bottom line:

SpaceX will almost certainly enter the U.S. mobile market as a hybrid operator, but the most capital‑efficient and strategically consistent route is:

  • Buy: spectrum (EchoStar + auctions) and possibly small, targeted assets.

  • Build: a lean terrestrial layer only where density and economics justify it, relying on satellites for the rest.

This balances a valid concern about AI’s capital pull with SpaceX’s clear intent to control the customer relationship and avoid being just a wholesale satellite internet operator.

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References:

https://www.lightreading.com/5g/spacex-might-build-and-buy-its-way-to-a-terrestrial-wireless-network-report

https://www.semafor.com/article/07/29/2026/spacex-looks-to-compete-with-the-carriers

FT: SpaceX considering Starlink Direct-to-Consumer mobile service & terrestrial cellular network infrastructure in the U.S.

Elon Musk: Starlink could become a global mobile carrier; 2 year timeframe for new smartphones

US Mobile’s new bundle combines its multi-network mobile service with Starlink residential internet

Direct-to-Device (D2D) satellite network comparison: Starlink V2 (Starlink Mobile) vs “Satellite Connect Europe”

U.S. BEAD overhaul to benefit Starlink/SpaceX at the expense of fiber broadband providers

SNS Telecom & IT: Private 5G for the Defense Sector to hit $2.5 Billion by 2029

Posted on by Alan Weissberger

SNS Telecom & IT’s latest research report indicates that cumulative spending on private 5G networks in the defense sector will reach $2.5 billion between 2026 and 2029.  The military has a longstanding history of leveraging wireless communications, and some of the most significant wireless-related innovations of the 20th century originated in the defense sector. With significant advances in COTS (Commercial Off-the-Shelf) technology over the past two decades, there has been a growing focus on complementing proprietary solutions with 3GPP standards-based networks to deliver both local and wide area coverage for capabilities extending from smart base operations and tactical networking to ISAC (Integrated Sensing & Communications)-enabled sensing for counter-drone protection.

Although public networks running over national mobile operator-owned RAN and core infrastructure are widely utilized for personal connectivity and non-sensitive IoT applications, defense sector stakeholders are increasingly turning their attention to exclusive-use, private 5G networks tailored to specific operational requirements in terms of security, access control, customization and specialized feature support.

Spearheaded by initiatives such as the United States DOW’s (Department of War) FutureG program, South Korean Ministry of National Defense’s private 5G project for unmanned and remote operations, United Kingdom MOD’s (Ministry of Defence) Project Morpheus, German Army’s D-LBO (Digitalization of Land-Based Operations), Spanish Air & Space Force’s BACSI (Connected, Sustainable & Intelligent Air Base), Italian Ministry of Defense’s DII (Defense Information Infrastructure), EU-funded 5G COMPAD 2.0 (5G Communications for Peacekeeping & Defense), NATO’s MN5G (Multinational Collaboration on 5G) and DIANA (Defence Innovation Accelerator for the North Atlantic), armed forces around the globe are actively investing in both permanent and transportable private 5G networks for warfighters at the tactical edge, military bases and training facilities. The U.S. military, for instance, has multiple deployments across the continental United States and overseas, including operational networks for the Indo-Pacific and Africa Commands. Canada, Germany, United Kingdom, France, Belgium, Netherlands, Switzerland, Spain, Portugal, Italy, Sweden, Norway, Denmark, Finland, Estonia, Latvia, Czech Republic, Hungary, Greece, Türkiye, Ukraine, Russia, China, Australia, Japan, South Korea, Singapore, India, Pakistan, Saudi Arabia, United Arab Emirates, Qatar, Jordan, Egypt, Israel and Brazil are among the other countries where experimental and operational networks have been deployed, operating in spectrum ranging from sub-1 GHz frequencies to bands n78 (3.5 GHz), n77 (3.7 GHz) and n79 (4.4-5 GHz), as well as mmWave bands.

The expanding influence of private networks is also evident from the recent use of rapidly deployable cellular systems for enhanced communications in military exercises such as the JIFX (Joint Interagency Field Experimentation) program hosted by the Naval Postgraduate School; Washington Air National Guard’s Exercise Phoenix Dawn; Italian Navy’s OPEX (Operational Experimentation) 2-25 in the Gulf of Taranto; German Army’s urban warfare training drills; Norwegian military’s Joint Viking exercise in the Arctic Circle; SABAK, a joint exercise of the Philippine Army and USARPAC (U.S. Army Pacific) forces; U.S. Marine Corps’ Steel Knight and ITX (Integrated Training Exercise); JGSDF’s (Japan Ground Self-Defense Force) Nankai Rescue disaster response training drill; and REPMUS, an unmanned systems experimentation exercise led by the Portuguese Navy.

SNS Telecom & IT’s “Private 5G/4G Cellular Networks for Defense: 2026 – 2030” report projects that global spending on private 5G and 4G LTE networks in the defense sector will grow at a CAGR of 24% over the next three years, collectively accounting for nearly $2.5 billion in cumulative investments between 2026 and 2029. For more information, please visit: https://www.snstelecom.com/defense.

About SNS Telecom & IT

SNS Telecom & IT is a global market intelligence and consulting firm with a primary focus on the telecommunications and information technology industries. Developed by in-house subject matter experts, our market intelligence and research reports provide unique insights on both established and emerging technologies. Our areas of coverage include but are not limited to 6G, 5G, LTE, Open RAN, vRAN, small cells, mobile core, xHaul transport, network automation, mobile operator services, FWA, neutral host networks, private 4G/5G cellular networks, public safety broadband, critical communications, MCX, IIoT, V2X communications and vertical applications.

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References:

https://www.snstelecom.com/defense

SNS Telecom & IT: Private 5G Market to Reach $6.6 Billion as Physical AI Takes Hold

GSA: Global private mobile networks exceed 2,000 worldwide; Ericsson Private 5G from Verizon Business extends beyond U.S.

Private 5G networks move to include automation, autonomous systems, edge computing & AI operations

SNS Telecom & IT: Private 5G Market Nears Mainstream With $5 Billion Surge

Verizon partners with Nokia to deploy large private 5G network in the UK

SNS Telecom & IT: Private 5G and 4G LTE cellular networks for the global defense sector are a $1.5B opportunity

 

 

Highlights and Analysis of July 30th U.S. Senate hearing on AI and telecommunications

Posted on by Alan Weissberger

Disclaimer:  Perplexity.ai was used for research used to generate this article.

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Introduction:

Today, U.S. Senator Deb Fischer (R-Neb), Chairman of the Senate Commerce Subcommittee on Telecommunications and Media, convened a hearing examining how artificial intelligence (AI) is transforming telecommunications networks and how the technology can enhance services across America.  Titled “Intelligent Networks: Powering Artificial Intelligence and Transforming Communications,” the hearing examined the bidirectional relationship between AI and network infrastructure. In particular, AI demands low-latency, high-bandwidth networks, while also offering tools to make those networks more efficient and secure.

Witnesses:

  • Jonathan Spalter, President and CEO, USTelecom — The Broadband Association

  • Dan Watermeier, Commissioner, Nebraska Public Service Commission

  • Bob Everson, Chief Architect of Provider Mobility, Cisco

  • Asad Ramzanali, Director of AI and Technology, Vanderbilt Policy Accelerator

From Senator Fischer’s opening remarks:

“As AI adoption increases, so will the demand for reliable and resilient communications infrastructure. Networks are the backbone along which the enormous amounts of data associated with AI are transmitted. I look forward to discussing both how networks are adapting to respond to AI and how AI is being used in networks to proactively plan for the future.”

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Permitting Reform Dominates Discussion

The clearest consensus across industry witnesses was that outdated permitting processes are the primary barrier to deploying AI-ready fiber infrastructure. Spalter testified that “the biggest barrier to building the broadband infrastructure our country needs isn’t technology or investment — it’s outdated permitting processes,” and urged Congress to establish consistent permitting timelines while preserving environmental and historic review requirements.

Watermeier emphasized that fiber is the only broadly deployable technology capable of supporting AI-era traffic, noting that “fiber optic networks can greatly exceed” the FCC’s current 100/20 Mbps threshold. Everson echoed the urgency, stating that providers are ready to build if permitting can be accelerated. Sen. Shelley Moore Capito (R-WV) supported establishing permitting “shot clocks.”

Spalter also identified cybersecurity and sustainable broadband funding as essential priorities, though specific proposals on either topic were not detailed in reported testimony.

Digital Divide and BEAD Funding

Sen. Lisa Blunt Rochester (D-DE) pressed witnesses on the impact of the Trump administration’s approximately 74% cut to the Broadband Equity, Access, and Deployment (BEAD) Program. Ramzanali responded that unconnected households are excluded from AI’s economic benefits, telehealth access, and educational tools, stating: “We shouldn’t accept the state of the country where not every American is connected to high-quality networks”

Grid Reliability and Spectrum: Largely Absent

Despite the hearing’s framing, two critical topics received little direct attention. Grid reliability — a pressing concern given that PJM Interconnection reported data-center-driven supply cost increases exceeding 60%, and Bank of America projected ~125 GW of new U.S. electric load from data centers by 2030 (Legis1) — was not substantively addressed by witnesses.

Spectrum policy was similarly underexplored, despite significant adjacent developments: the FCC’s July 22 vote to auction 160 MHz of upper C-band spectrum, NTIA’s $53 million funding announcement for secure AI-enabled Radio Access Networks, and a detailed spectrum reform brief published by the International Center for Law & Economics timed to the hearing. The ICLE brief recommended five reforms: preserving a balanced mix of licensed, unlicensed, and shared spectrum; streamlining the Spectrum Relocation Fund; strengthening FCC-NTIA coordination; replacing worst-case interference analysis with risk-informed probabilistic methods; and coherent U.S. engagement at the ITU World Radiocommunication Conference to counter Chinese influence in standards bodies.

Cybersecurity: Listed but Undefined

Spalter listed cybersecurity among his three essential priorities but did not elaborate on specific threats or mitigation strategies. The absence is notable given that an adjacent House hearing on July 22 featured testimony from Lindsay Gorman warning that AI is “expanding the cyberattack surface” through prompt-injection attacks, data poisoning, and model exploitation. Gorman urged Congress to mandate AI cybersecurity standards and recommended next-generation networks implement AI-automated defenses and post-quantum cryptography.

Industry vs. Regulatory Divergence

The hearing revealed a clear fault line. The three industry witnesses uniformly advocated for reducing regulatory friction and enabling private investment. Ramzanali, whose broader research at Vanderbilt advocates utility-style regulation of digital infrastructure, structural separation of AI hardware and software, and a dedicated digital regulator, provided the only counterweight — though his reported testimony focused on digital divides rather than his full structural reform agenda.

Sen. Fischer’s opening remarks captured the industry-aligned framing: “Opaque regulations and lack of coordination should not get in the way of network development.” Sen. Blunt Rochester’s questioning represented the regulatory perspective, challenging funding cuts and emphasizing equitable access.

Outlook

The hearing underscored that the U.S. telecommunications policy debate around AI is currently dominated by infrastructure deployment concerns — particularly permitting — while cybersecurity, spectrum management, and grid reliability remain underexamined. With the Senate Commerce Committee delaying broader AI legislation markup until after the summer recess (Washington Times), the substantive policy work on these gaps may not advance until fall.

Full written testimony and a hearing transcript are not yet available on the committee website.

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Analysis via Perplexity.ai:

Comparison Matrix: Key Recommendations by Topic

1. Grid Reliability and Energy Demand

Witness Position Key Details
Spalter Not directly addressed in testimony Focused on permitting and broadband funding as primary barriers; did not testify on grid/energy specifically
Watermeier Indirect — framed fiber as the infrastructure solution Argued fiber networks are the only broadly deployable technology capable of supporting AI-era traffic loads, implying grid demands flow through network capacity
Everson Not directly addressed Focused on deployment speed; Cisco’s corporate positions tie AI adoption to network readiness but not grid energy specifically
Ramzanali Indirect — connected to digital divide Warned that unconnected households cannot benefit from AI economy; broader work warns of AI infrastructure financial risks and economic mismatch
Context Hearing framing acknowledged grid strain Legis1 reported that PJM Interconnection saw data-center-driven supply cost increases of 60%+; Bank of America projected ~125 GW of new U.S. electric load from data centers (2026–2030). Sen. Fischer’s opening remarks noted AI demand requires “reliable, high-speed, high-capacity networks”

2. Cybersecurity Vulnerabilities

Witness Position Key Details
Spalter Cybersecurity is one of three essential priorities Told the subcommittee that “permitting reform, cybersecurity, and sustainable broadband funding are all essential to preparing the nation’s communications infrastructure for AI” — but did not detail specific cyber threats or mitigation proposals in reported testimony
Watermeier Not directly addressed in reported testimony Focused on fiber capability and permitting
Everson Implicit via Cisco’s corporate positions Cisco’s government policy blog states “AI is rewriting the rules of cybersecurity, and we have a real opportunity to tip the scales in favor of defenders” and emphasizes modernizing legacy infrastructure as essential for security. Cisco advocates for NIST GenAI program participation and lifecycle governance frameworks
Ramzanali Not directly addressed in reported testimony His broader research at Vanderbilt focuses on financial and structural risks of AI infrastructure rather than network cybersecurity per se
Sen. Fischer Framed as strategic imperative Opening remarks: “AI has real potential to make networks more efficient and secure” and “we cannot fall behind in developing the most resilient and secure networks” (Fischer press release)
Context Adjacent House hearing (July 22) Wiley Rein reported that witness Lindsay Gorman testified AI is “expanding the cyberattack surface,” creating vulnerabilities including prompt-injection attacks, data poisoning, and model theft. She urged Congress to mandate cybersecurity standards for AI and recommended next-gen networks leverage AI for automated defenses and implement post-quantum cryptography

3. Spectrum Policy

Witness Position Key Details
Spalter Not directly addressed in reported testimony USTelecom’s membership is primarily wireline/fiber-focused; spectrum was not a featured topic in his reported remarks
Watermeier Not directly addressed Focused on fiber deployment; as a state PSC commissioner, spectrum falls outside his primary jurisdiction
Everson Implicit via Cisco’s positions Cisco’s title “Chief Architect of Provider Mobility” implies wireless expertise. Cisco’s policy blog advocates unlocking 6 GHz Wi-Fi as “the foundation for the AI Era” and ties spectrum capacity directly to AI adoption
Ramzanali Not directly addressed in reported testimony Focus was on digital divides and BEAD funding
Policy context (ICLE) Five-reform framework published as hearing context The International Center for Law & Economics issued a brief timed to the hearing recommending: (1) preserve balanced mix of licensed/unlicensed/shared spectrum, judged by total economic value not auction revenue; (2) streamline the Spectrum Relocation Fund to move federal spectrum faster; (3) strengthen FCC-NTIA coordination via common technical record; (4) replace worst-case interference analysis with risk-informed probabilistic methods; (5) present coherent U.S. positions at ITU/WRC to counter China’s standards influence
Regulatory context FCC and NTIA actions Legis1 reported the FCC voted July 22 to auction 160 MHz of upper C-band spectrum (60% more than Congress required), creating a potential 440 MHz “super band.” NTIA opened $53M in funding for secure AI-enabled Radio Access Networks. NTIA’s Arielle Roth testified to the House on July 15 about unlocking 30+ GHz of additional spectrum for AI-enabled satellite services

4. Regulatory Reform vs. Government Oversight

Witness Stance Categorization Key Details
Spalter Regulatory reform (deregulation-oriented) Industry self-reliance with streamlined rules Urged Congress to establish “consistent permitting timelines” and “modernize federal, state, Tribal, and local review processes” while preserving environmental/historic review. Framed the problem as bureaucratic delay, not market failure: “The biggest barrier… isn’t technology or investment… It’s outdated permitting processes” (MeriTalk)
Watermeier Regulatory reform (state-level pragmatist) Practical deployment focus Echoed permitting concerns from state regulator perspective. Argued fiber is the only technology meeting AI-era thresholds, implying regulatory frameworks should favor fiber-capable infrastructure. Did not advocate for new oversight mechanisms
Everson Regulatory reform (industry-aligned) Private-sector readiness “The sooner we can speed that permitting process along, the better, because then we can get to the work of deploying those resources.” Positioned industry as ready to build if government gets out of the way. Cisco’s blog advocates modernization as investment, not regulatory expansion
Ramzanali Government oversight (structural reform advocate) Public-interest regulation His Vanderbilt Policy Accelerator report “After the AI Crash” advocates utility-style nondiscrimination rules for foundation models/cloud/chips, a “Glass-Steagall for AI” structural separation, a dedicated digital regulator, publicly funded compute infrastructure, and restrictions on financial engineering in AI infrastructure. His hearing testimony focused on the digital divide as a market failure requiring government action: “we shouldn’t accept the state of the country where not every American is connected to high-quality networks” (Blunt Rochester press release)
Sen. Fischer (R-NE) Regulatory reform “Opaque regulations and lack of coordination should not get in the way of network development”
Sen. Capito (R-WV) Regulatory reform Advocated permitting “shot clocks” to accelerate deployment
Sen. Blunt Rochester (D-DE) Government oversight Challenged BEAD funding cuts (~74%), framing broadband access as a government responsibility essential for AI economy participation

5. AI-Enabled Services: Industry Priorities vs. Regulatory Proposals

Dimension Industry Priority (Spalter, Everson) Regulatory/Public-Interest Proposal (Ramzanali, Blunt Rochester) Divergence
Infrastructure deployment Speed up permitting; let private capital build Ensure equitable deployment via BEAD and universal service; don’t accept unconnected Americans Industry wants fewer procedural hurdles; regulators want equitable outcomes, not just speed
Broadband funding “Sustainable broadband funding” needed (Spalter) but framed as enabling private investment BEAD funding must be restored; 74% cut harms rural AI access (Blunt Rochester) Both want funding, but industry sees it as complement to private investment while advocates see it as essential public obligation
Technology standards Fiber-first; fiber exceeds FCC’s 100/20 threshold (Watermeier) Quality networks for all, not just checkbox milestones Industry favors specific tech mandates; advocates focus on outcome-based universal access
AI infrastructure governance Modernize and build; Cisco frames AI as defense opportunity Structural separation of software/hardware; regulate as digital utilities; restrict circular equity financing Sharpest divergence: industry wants freedom to integrate vertically; Ramzanali’s framework would break those integrations apart
Spectrum Cisco advocates 6 GHz unlicensed for AI-era Wi-Fi ICLE (external brief) recommends balanced licensed/unlicensed/shared mix with risk-informed analysis Partial alignment on unlicensed spectrum value, but ICLE’s framework is more nuanced than industry’s single-band focus
Cybersecurity Spalter lists it as essential but offers no specifics; Cisco positions AI as defensive tool Gorman (House hearing) urges Congress to mandate AI cybersecurity standards and implement post-quantum cryptography Industry prefers voluntary standards and market-driven security; regulatory voices want mandated standards

Key Divergences and Synthesis

Consensus Points

  • Permitting reform is urgent. All three industry witnesses and Republican senators agreed that permitting delays are the single biggest barrier to AI-ready network deployment. Even Sen. Fischer’s opening remarks flagged “opaque regulations.”

  • Fiber is foundational. Spalter, Watermeier, and Everson all positioned fiber as the backbone infrastructure for AI. Fischer encapsulated it: “AI runs on infrastructure, and infrastructure runs on fiber.”

  • AI transforms networks bidirectionally. Fischer’s framing — that AI requires better networks but can also make networks more efficient and secure — was implicitly accepted across witness testimony.

Sharpest Divergences

  • Industry self-regulation vs. structural oversight. The three industry witnesses (Spalter, Watermeier, Everson) uniformly advocated for removing regulatory friction and letting private capital deploy infrastructure. Ramzanali’s framework — developed at Vanderbilt and reflected in his testimony on digital divides — argues for utility-style regulation, structural separation, and a dedicated digital regulator. This is the fundamental fault line.

  • BEAD funding. Industry witnesses mentioned “sustainable broadband funding” as a priority but did not challenge the Trump administration’s 74% cut to BEAD. Sen. Blunt Rochester and Ramzanali directly attacked the cuts as harmful to AI equity. Industry silence on BEAD cuts suggests a pragmatic accommodation with the administration’s budget priorities.

  • Cybersecurity specificity. Spalter listed cybersecurity as essential but offered no concrete proposals in reported testimony. This stands in contrast to the adjacent House hearing where witnesses like Lindsay Gorman called for mandated congressional cybersecurity standards. The gap between listing cybersecurity as a priority and proposing actual security mandates represents a significant industry-regulatory divergence.

  • Spectrum was largely absent. Despite ICLE publishing a detailed five-reform spectrum brief timed to the hearing, and despite the FCC’s July 22 C-band auction vote and NTIA’s $53M AI-RAN funding announcement, none of the witnesses’ reported testimony engaged substantively with spectrum policy. This is a notable omission given that Everson’s title (Chief Architect of Provider Mobility) implies wireless expertise. The ICLE brief’s warning that “the United States cannot lead at digital speed while governing the airwaves at bureaucratic speed” went unaddressed in the hearing room.

Implications for Next-Generation AI-Enabled Services

  • The hearing’s overwhelming focus on permitting reform and fiber deployment — while important — left cybersecurity, spectrum, and grid reliability largely underexplored. The most consequential gap is the absence of detailed cybersecurity testimony, given that AI is simultaneously expanding the attack surface and offering new defensive tools.

  • Ramzanali’s presence provided the only counterweight to the industry consensus, but his reported testimony focused narrowly on digital divides rather than his broader structural reform agenda. Whether his Vanderbilt research on AI infrastructure financial risks and digital utility regulation will influence future Senate action remains to be seen.

  • The ICLE spectrum framework — published as context for this hearing — represents the most detailed policy roadmap for AI-enabled wireless services, but it was not directly debated by the witnesses. The FCC’s C-band auction and NTIA’s AI-RAN funding are proceeding on parallel tracks outside the hearing’s scope.

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References:

Fischer Leads Hearing on AI in Communications Networks

NEWS: Senator Blunt Rochester Highlights How AI Will Impact Digital Divides

 

Dell’Oro: Telecom carriers are on a 5G SA spending spree with more to come

Posted on by Alan Weissberger

Dell’Oro Group, says that telecom wireless carriers have spent 208% more on 5G Standalone (SA) than they had on 4G Core functions at the same point in the technology’s lifecycle. However, 5G Mobile Core Network revenue growth is expected to slow over the next two years, as carriers put off transformation projects due to elevated server costs.

“The way the 3GPP specifications unfolded created an offset between 5G RAN spending and the implementation of 5G SA,” said Siân Morgan, Senior Director at Dell’Oro Group. “However, the complexity of the 5G SA is driving cumulative vendor revenues much higher than they were at the same stage in the LTE Evolved Packet Core (EPC) lifecycle.

“5G SA revenues have not yet peaked,” Morgan added. “The majority of mobile network operators haven’t made 5G SA services available to a broad base of their customers.  Some operators are delaying core transformation projects because memory shortages are driving up server prices, but we expect double-digit 5G Mobile Core Network revenue growth to resume in 2028.”

Additional highlights from Mobile Core Network and Multi-access Edge Computing 5-Year Forecast July 2026 Report include:

  • EMEA (Europe, Middle East and Africa) will drive the most Mobile Core Network revenue over the next five years.
  • Despite being superseded by 5G, 4G core revenue grew in 2025, and Dell’Oro Group raised the forecast for this market.
  • AI will have a variable impact on mobile core networks, with opportunities for efficiency and revenue generation, alongside a risk of escalating costs.

 

About the Report

The Dell’Oro Group Mobile Core Network & Multi-Access Edge Computing Quarterly Report offers complete, in-depth coverage of the market with tables covering manufacturers’ revenue, shipments, and average selling prices for Traditional Packet Core, Evolved Packet Core, 5G Packet Core, Policy, Subscriber Data Management, Signaling, Circuit Switched Core, and IMS Core by geographic regions. To purchase this report, please contact us at [email protected].

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From Perplexity.ai and Ericsson:

Analysis:

5G SA differs from NSA because it uses a 5G core rather than relying on 4G core (EPC) anchoring, which makes it better suited for advanced capabilities like network slicing and more flexible service control. All 5G features and functions, e.g. 5G security, network slicing, MEC, etc require a 5G SA core network.  5G network operators can package differentiated services instead of treating 5G only as a faster broadband layer.

Adoption is already broadening geographically. Ericsson says more than 60 service providers had deployed or launched public 5G SA networks by the end of September 2024, with early leadership in North America, China, Southeast Asia, and Australia, and with deployments expanding into Latin America, the Gulf Cooperation Council, and South Africa.

Device readiness is also improving quickly. Ericsson notes that the share of announced 5G devices supporting SA was about 70 percent by the end of June 2024, which lowers one of the biggest historical blockers to mass adoption.

From a vendor and operator perspective, the value of SA is shifting from coverage to monetization. Dell’Oro says many operators already use SA for enterprise and fixed wireless access, even if they have not yet opened it broadly to consumers, which suggests the strongest initial revenues may come from business services before mass-market consumer plans.

Market Forecast:

The strongest public forecast in the sources is subscriber growth: Ericsson projects global 5G SA subscriptions will reach about 1.2 billion by the end of 2024 and approximately 3.6 billion by 2030, which would represent nearly 60 percent of all 5G subscriptions by that time.

On the infrastructure side, Dell’Oro expects the 5G mobile core network market to grow at a 6 percent CAGR from 2024 to 2029, largely driven by SA adoption, while MEC is forecast to grow faster at 17 percent CAGR because of network slicing, RedCap, and network APIs tied to Open Gateway.

A reasonable market view is that 2025–2027 will be the period when SA shifts from launch announcements to scale, especially as more operators convert consumer traffic, expand enterprise use cases, and retire older core dependencies. By the late 2020s, growth should be driven less by “first deployment” and more by monetization density: more SA subscribers, more eligible devices, and more services built on top of the SA core.ericsson+1

What to watch:

  • Consumer rollout pace. Operators that keep SA limited to enterprise and FWA will likely monetize more slowly than those that open it to consumers.

  • Device defaults. SA-enabled devices matter less if SA is not the default setting, so default-on support is an important adoption catalyst.

  • Enterprise use cases. Slicing, private wireless integration, and low-latency applications are likely to produce the clearest near-term ROI.

  • Regional timing. China and India are expected to remain major contributors, while Europe and parts of the Americas close the gap later in the decade.

References:

5G Standalone Revenue Triples 4G Core at Same Stage of Tech Cycle, According to Dell’Oro Group

GSA: 5G Non Terrestrial Networks, 5G SA and 5G Advanced gain momentum

Dell’Oro: Mobile Core Networks +15% in 2025; Ookla: Global Reality Check on 5G SA and 5G Advanced in 2026

Dell’Oro: RAN market stable, Mobile Core Network market +14% Y/Y with 72 5G SA core networks deployed

AT&T deploys nationwide 5G SA while Verizon lags and T-Mobile leads

Ericsson CEO’s strong statements on 5G SA, WRC 27, and AI in networks

Amazon Leo plans to deploy 5,105 D2D to interoperate with Apple devices

Posted on by Alan Weissberger

Executive Summary:

Amazon Leo, the #1 competitor to SpaceX’s Starlink for LEO satellite internet, is proposing a new Direct to Device (D2D) constellation comprising 5,105 low-Earth orbit (LEO) satellites that will work in concert with satellites Amazon is acquiring from Globalstar. 

Amazon Leo has disclosed additional technical and regulatory detail on its proposed global direct‑to‑device (D2D) low Earth orbit (LEO) constellation, envisioned to comprise 5,105 satellites and to operate in conjunction with D2D capacity obtained via Amazon’s planned acquisition of Globalstar.

System architecture and spectrum use:

According to an FCC application filed by Kuiper Systems LLC on Saturday, July 25, the Amazon Leo D2D system is designed to leverage Mobile‑Satellite Service (MSS) spectrum as well as selected terrestrial mobile bands to deliver “ubiquitous global coverage.” The constellation will employ D2D‑optimized spacecraft using service links in the 1.6–2.4 GHz range, supported by feeder links and TT&C in Ka‑ and V‑band. Outside the US, Amazon plans to utilize additional available L‑band and S‑band allocations for service links to expand geographic reach and regulatory flexibility.

In a Monday technical blog post, Amazon Leo outlined a five‑shell orbital architecture, with three mid‑latitude shells designed to serve densely populated regions and two high‑latitude shells to extend coverage into remote geographies, including polar areas. Amazon reiterated that the D2D constellation is being engineered to interoperate with Apple devices (including iPhone and Apple Watch) and to complement its Kuiper broadband network, which is expected to enter commercial service later this year.

Integration with Globalstar and optical ISLs:

The Amazon Leo D2D constellation will incorporate optical inter‑satellite links (OISLs) to integrate the new D2D system with existing Amazon Leo satellite infrastructure and to “work in close concert” with the Globalstar MSS constellation in the 1.6–2.4 GHz band, assuming timely closing of the transaction. Amazon states that it will mitigate inter‑system interference between the Amazon Leo D2D system and Globalstar’s HIBLEO‑4, HIBLEO‑X, and planned C‑3 MSS operations via unified global network management and coordinated controls.

The proposed $11.5 billion Amazon–Globalstar deal remains under active regulatory review. Amazon Leo has previously indicated that its own D2D constellation is targeted for launch around 2028, positioning the system as a smartphone‑ and device‑centric coverage layer beyond the reach of terrestrial radio access networks and as a competitor or complement to emerging D2D offerings from SpaceX, AST SpaceMobile, and others. Amazon has highlighted canonical D2D use cases, including emergency messaging, in‑vehicle connectivity, and a broad range of IoT applications.

The potential role of Amazon’s D2D platform within the new US rural‑coverage D2D joint venture formed by AT&T, T‑Mobile, and Verizon remains unspecified.

Satellite lifecycle, deorbiting, and debris mitigation:

Each Amazon Leo D2D satellite is designed with a nominal operational life of six to eight years, contingent on orbital shell parameters. Amazon plans active end‑of‑life management and deorbiting, reserving approximately 40% of each satellite’s propellant for “disposal operations” to support controlled removal from orbit.

The FCC filing also provides additional detail on collision‑risk management and debris‑mitigation strategies. To reduce the probability of fragmentation events, Amazon has engineered propellant tanks to leak rather than burst under most failure modes, including micrometeoroid and orbital‑debris impacts, and has characterized tank behavior under high‑velocity impact conditions. The constellation will be monitored on a 24/7 basis for conjunction and collision risk, and each satellite will be equipped with onboard propulsion and maneuvering capability to perform collision‑avoidance maneuvers with respect to other spacecraft and tracked objects.

 

References:

https://www.lightreading.com/satellite/amazon-leo-files-plan-to-deploy-5-105-d2d-satellites

Cheap Chinese AI Models: Unappreciated Threat to U.S. Hyperscaler AI Dominance

Posted on by Alan Weissberger

Introduction:

IEEE Techblog readers are keenly aware of the stupendous AI capex that has eliminated most hyperscaler free cash flow.  There’s also the ROI question when there’s no “killer app” or a clear way to monetize AI services.  And let’s not forget issues like: the competition for AI benchmark bragging rights. price per token, rack density, and power consumption-per-dollar.

Now the next AI battleground will be competition from Chinese open-weight models, which are pushing AI toward commoditization faster than many U.S. hyperscalers expected.  That shift could quietly erode the economics of the entire AI infrastructure stack.

Raffi Krikorian, the chief technology officer at Mozilla, which runs the Firefox browser, switched to Chinese AI startup Moonshot’s Kimi K3 for many of his day-to-day activities within days of the new, powerful model’s launch more than a week ago.  “It just seems snappier,” Krikorian said of K3, comparing it with the acclaimed, higher-priced Claude Fable chatbot from Anthropic, the San Francisco private AI company with a $1 trillion assessed market value. Earlier, he had been using another strong Chinese model, Z.ai’s GLM-5.2, for everyday tasks such as managing his calendar, documents, and email.

Krikorian is among a growing number of Americans turning to Chinese AI systems, which are gaining traction worldwide because they are more affordable and increasingly efficient. U.S. companies such as cryptocurrency exchange Coinbase have said they are switching to Chinese AI models to help reduce costs. Their growing popularity has frustrated some U.S. tech giants, but barring an outright ban, these models are likely to keep attracting independent software developers in the U.S. and beyond.

The shift from training to inference:

The AI buildout is moving from model training toward sustained inference, and that changes the economics of the stack. Training demands enormous one-time bursts of compute, but inference creates continuous load on accelerators, interconnect, storage, and power systems, which means utilization and token pricing now matter as much as raw model capability.

That is where Chinese open-weight models matter most. Reports indicate that some are 60% to 90% cheaper than leading U.S. AI offerings, while still being “good enough” for a large share of enterprise and developer workloads.

Why open weight matters technically:

Open-weight models reduce deployment friction by allowing organizations to download, modify, and run models on their own infrastructure rather than through a centralized API. NTIA has noted that this can broaden access and accelerate innovation, but it also shifts responsibility for integration, safety, and lifecycle management onto deployment.

From an infrastructure perspective, that means AI demand becomes more distributed. Instead of concentrating in a small number of hyperscale regions, workloads can move into private clouds, regional facilities, enterprise data centers, and even edge-adjacent environments, changing traffic patterns and backend topology.

Impact on hyperscaler design:

The first-order risk for hyperscalers is not loss of raw demand; it is lower monetization per unit of demand. If users route routine inference to cheaper Chinese models, the same physical infrastructure may carry more tokens but generate less revenue, pressuring the economics of GPU clusters, accelerator networking, and power-hungry cooling systems.

That is a serious issue because modern AI facilities are purpose-built systems. They rely on dense GPU racks, low-latency fabrics, liquid cooling, and carefully engineered power distribution, all of which are justified by high utilization and strong margins. If the average workload shifts to lower-value inference, the return on those assets falls even if the machines stay busy.

Network and power consequences:

The networking impact is equally important. More self-hosted and regionally deployed inference increases east-west traffic inside enterprise environments and raises demand for metro transport, interconnect, and secure private connectivity, rather than only for giant centralized AI campuses.

Power and cooling are the other pressure points. AI infrastructure already consumes substantial electrical power and water, and inference-heavy systems can run continuously, making thermal design and power delivery central to total cost of ownership. If cheaper models fragment the market across more sites, the industry may need more distributed capacity without the same revenue density to support it.

The strategic takeaway:

For U.S. AI companies and hyperscalers, the threat from Chinese open-weight models is best understood as commoditization of inference. The frontier race may continue at the top end, but the commercial center of gravity is shifting toward lower-cost, portable models that reduce lock-in and weaken pricing power across the stack.  The infrastructure question is no longer whether AI demand will grow; it is whether the industry can preserve enough margin, utilization discipline, and network economics to make that growth pay.

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Open-weight AI model landscape

Model family Examples Primary strengths Infrastructure implications Key tradeoffs vs US closed models
Alibaba Qwen Qwen3, Qwen3.5, Qwen3 VL Multilingual coverage, broad model family, strong open-weight ecosystem Attractive for regional deployment, private clouds, and multilingual inference Lower cost and more deployment flexibility, but usually less integrated than top US managed offerings
DeepSeek DeepSeek-V3, R1-family Strong reasoning/coding, efficient inference, active developer adoption Good fit for cost-sensitive inference clusters and self-hosted stacks Very competitive on price-performance, but governance, provenance, and safety concerns remain
Zhipu AI / GLM GLM-5.2 Long context, agent/tool-use orientation, strong benchmark visibility Useful for agentic workflows and document-heavy enterprise inference Open deployment flexibility, but smaller global enterprise ecosystem than US leaders
Moonshot AI Kimi K2.6, K2.7, K3 Long-context assistant behavior, strong reasoning focus Suitable for knowledge retrieval and long-context enterprise use cases Competitive on context handling, but support and platform maturity trail US vendors
MiniMax MiniMax-M3 Efficient inference, long-context design Potentially attractive for distributed deployments and lower-cost serving Good economics, but narrower enterprise footprint outside China
MiMo / Xiaomi MiMo-V2.5-Pro Efficient large-model performance Useful where cost and self-hosting matter more than premium managed tooling Less mature ecosystem and weaker enterprise integration
Google Gemini, Gemma Strong multimodal performance, cloud integration Best suited for managed cloud deployments and enterprise workflows on Google Cloud Gemini is closed; Gemma is open-weight but not always frontier-class
OpenAI GPT-4.1, o-series, open-weight initiatives Strong reasoning, coding, and ecosystem depth Drives premium API demand and centralized inference on provider infrastructure Highest capability and tooling depth, but also highest lock-in and often higher cost
Anthropic Claude family Enterprise writing, coding, and long-context use Strong fit for managed inference in corporate workflows Closed model stack limits portability and self-hosting
xAI Grok family Fast iteration, real-time orientation Useful where rapid product updates matter more than deployment flexibility Closed deployment and a less mature enterprise stack
Amazon Nova family AWS-native enterprise integration Supports cloud-first AI deployment inside AWS environments Strong platform fit, but less portable and not open-weight
Microsoft Phi family, Copilot stack Enterprise distribution, Azure/M365 integration Encourages centralized AI consumption through Microsoft platforms Productized and convenient, but not optimized for open self-hosted infrastructure

Hyperscaler AI Race: Soaring Capex Wipes Out Free Cash Flow; AGI and Digital Gods

Posted on by Alan Weissberger
The tsunami wave of generative AI investment is now facing intense scrutiny due to an unsustainable imbalance between massive capital expenditure (capex) and negligible return on investment (ROI). Despite unprecedented infrastructure spending (mostly for AI Data Center buildouts), the sector has yet to deliver a definitive “killer app” or high-utility enterprise software capable of generating meaningful corporate revenue.  Consequently, stakeholders are shifting from speculative funding toward rigorous evaluation of tangible monetization and operational efficiencies. This lack of clear value realization raises valid concerns about a potential market correction as the technology struggles to transition from a capital sink to a self-sustaining ecosystem.
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Google parent company Alphabet boosted its forecast for capital spending for both 2026 and 2027 last week, citing supply constraints amid surging demand for more computing power. The company said its 2026 capex would increase its potential maximum to $205 billion from $190 billion.  That $15 billion increase places Alphabet neck-and-neck with Amazon at the absolute top of the hyperscaler spending ladder. Paul Meeks, head of technology research at Freedom Capital Markets, told CNBC that Wall Street is expecting about $260 billion in capex from Google/Alphabet in 2027.  “I think people would be satisfied [with that],” he added. “The thing I worry about is if you have a drop in spending: All of a sudden it’s $205 billion for Google this year, and next year it’s, say, $100 billion – it collapses.”
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Hyperscaler Annual Capex Forecast (2024–2027):
All figures represent billions of USD ($B) and reflect current consensus updates.

Company 2024 (Actual) 2025 (Actual) 2026 (Current Guidance / Est) 2027 (Projected)
📦 Amazon $53B $112B $195B – $210B $230B – $260B
🔍 Alphabet (Google) $51B $104B $195B – $205B $240B – $280B
💻 Microsoft $56B $108B $185B – $195B $220B – $250B
♾️ Meta $38B $85B $125B – $145B $150B – $180B
🗄️ Oracle $13B $25B $45B – $50B $55B – $65B
🧮 Combined Aggregate $211B $434B $745B – $805B $895B – $1,035B
Source: Google Gemini
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The huge increase in hyperscaler capex, wipes out their free cash flow (revenues-expenses is now negative for all but Microsoft). The shift in focus by investors from earnings to free cash flow marks a turning point in market perceptions.  The correct way to describe free cash flow is the cash flow a company generates during a period of time that is available to be paid to the company’s shareholders and debtholders.Companies with negative free cash flow are only able to cover the interest and principal on their debt by additional borrowing or by issuing new equity. In other words, cash is flowing from investors to the company, not the other way around.  In a financial crisis, investors become unwilling to support companies not able to cover interest and principal, with the result being a cascade of defaults and runs on financial institutions.

A major concern with the massive AI-capex which has occurred during the last two years is that much of it is debt financed. As the real cost of generative AI-tokens is becoming clear, lower priced Chinese competitors are emerging, and AI customers are beginning to economize on their use of AI. As a result, investors are becoming increasingly alarmed about whether U.S. AI firms will be able to cover their debt obligations.  AI-capex has been the main, and perhaps only driver of U.S. economic growth. If more companies announce negative free cash flows, that increase in magnitude, the financial system and overall economy will move closer to the tipping point.

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But wait, Google/Alphabet co-founder says it’s more about winning AI market share than skyrocketing capex or ROI.  On Patrick O’Shaughnessy’s Invest Like the Best podcast, Gavin Baker, Chief Investment Officer for Atreides Management, shared an anecdote about what’s been going on within Google/Alphabet offices. According to Baker, Google co-founder Larry Page has been telling Google employees, “I am willing to go bankrupt rather than lose this race.” That shows how high the person who led Alphabet through its halcyon days thinks the stakes are in AI.

Baker went on to describe the leaders of Meta Platforms, Microsoft, and Alphabet as being in a race to create a “Digital God,” or artificial general intelligence (AGI), which is likely to be worth trillions of dollars in value if not tens of trillions or even more. He also explained that the tech giants are counting on the models to scale, or get better as they get bigger, and the tech giants are unlikely to slow down their spending on AI infrastructure until they’re proven otherwise. AGI could be more disruptive than any technology before it, including the internet, and most tech CEOs seem to think this.  OpenAI CEO Sam Altman told Time magazine last December, “I think AGI will be the most powerful technology humanity has yet invented.”
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References:

https://www.forbes.com/sites/hershshefrin/2026/07/2/market-experiences-an-ai-capex-turning-point-with-tipping-point-to-follow/

https://www.fool.com/investing/2024/08/31/thinking-of-selling-nvidia-stock-larry-page-quote/

Curmudgeon: Caveat Emptor: Huge Debt and Circular Financing Deals Dominate AI Build-Outs 

Will billions of dollars big tech is spending on Gen AI data centers produce a decent ROI?

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