Beamforming the future: BeammWave's 6G push signals the rise of orbital-terrestrial wireless networks
Beamforming the future: BeammWave's 6G push signals the rise of orbital-terrestrial wireless networks
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Joakim Axmon
Joakim Axmon
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Beamforming the future: BeammWave's 6G push signals the rise of orbital-terrestrial wireless networks

Wireless networking is moving beyond just terrestrial cellular towers or satellite constellations. The next generation of communications infrastructure is aiming for something much more advanced: a fully integrated system that combines both ground-based and orbital networks. This new ecosystem will be driven by intelligent beamforming, AI-powered spectrum management, and software-defined radio technologies.
 
This transition took a major step forward when BeammWave announced that digital beamforming is now officially being considered in the 3GPP standardization process, following the RAN4#119 meeting in Dalian, China.
 
While the announcement may appear narrowly technical, its implications extend far beyond conventional telecom engineering. The move represents a deeper transformation underway across the global communications landscape, one in which terrestrial 6G systems and low Earth orbit (LEO) satellite constellations increasingly converge into a unified computational network fabric.
 
"Bringing Digital Beamforming to the standardization table is a critical step forward in addressing the reliability and performance of high-frequency FR2 networks," says Joakim Axmon, Senior Expert Systems and Standards at BeammWave. "We look forward to continuing this work alongside the ecosystem to drive the digital evolution of 6G, ensuring future networks are both technically robust and commercially viable."

The digital beamforming inflection point

For decades, high-frequency wireless systems have struggled against the harsh realities of physics.
 
Millimeter-wave (mmWave) frequencies above 24 GHz offer enormous bandwidth potential, but they suffer from:
  • Severe signal attenuation
  • Limited propagation range
  • Sensitivity to environmental obstruction
  • Complex mobility management challenges
Early 5G deployments addressed these issues using analog beamforming, steering radio signals directionally toward users. But analog approaches remain constrained in flexibility and scalability.
 
BeammWave’s proposal pushes the industry toward fully digital beamforming, in which beam steering is dynamically controlled by software rather than hardware-limited.
 
The company’s architecture combines:
  • Integrated radio chips
  • Embedded antennas
  • Proprietary signal-processing algorithms
  • Software-driven beam control
designed specifically for future 5G evolution and 6G deployments operating in Frequency Range 2 (FR2).
 
According to the press release, 3GPP will now formally evaluate whether digital beamforming should become part of the standardized UE RF architecture for future 6G systems.
 
That evaluation may ultimately shape the technological foundation of global wireless infrastructure for the next decade.

Why beamforming matters more than ever

At first glance, beamforming appears to be a radio engineering problem.
 
In reality, it is becoming a computational problem.
 
Modern digital beamforming systems require:
  • Massive real-time signal processing
  • Adaptive multi-user optimization
  • AI-assisted interference mitigation
  • Dynamic spectrum allocation
  • Continuous spatial recalibration
Future 6G networks may involve thousands of simultaneous directional beams operating cooperatively across dense urban environments.
 
This transforms wireless networking into a distributed supercomputing challenge.
 
As a result, future telecommunications infrastructure will increasingly depend on:
  • AI accelerators
  • Edge computing systems
  • Advanced RF semiconductors
  • Real-time optimization algorithms
  • High-performance networking architectures
In many respects, next-generation wireless systems are evolving into planetary-scale distributed computing platforms.

The satellite convergence era

At the same time terrestrial wireless evolves, satellite internet constellations are rapidly reshaping global connectivity.
 
Systems such as:
  • Starlink from SpaceX
  • Amazon’s low Earth orbit (LEO) satellite network
have demonstrated that low Earth orbit satellite networks can deliver broadband-class connectivity with latency low enough for real-time applications.
 
However, despite growing speculation, LEO constellations are unlikely to replace terrestrial 5G or 6G infrastructure outright.
 
Instead, the industry is moving toward convergence.
 
Terrestrial networks remain vastly superior for:
  • Dense urban capacity
  • Indoor connectivity
  • Ultra-low-latency applications
  • High spectral reuse
  • Edge AI integration
LEO systems excel at:
  • Global coverage
  • Rural connectivity
  • Maritime and aviation communications
  • Disaster resilience
  • Universal fallback networking
The future architecture increasingly appears hybrid rather than competitive.

Non-terrestrial networks become core infrastructure

3GPP’s long-term vision for 6G already incorporates the concept of Non-Terrestrial Networks (NTN), an integrated framework in which satellites, terrestrial cells, airborne systems, and edge computing resources operate seamlessly together.
 
Within that vision:
  • Smartphones dynamically switch between terrestrial and orbital links.
  • AI systems optimize routing in real time.
  • Beamforming systems coordinate across ground and space networks.
  • Spectrum becomes software-defined and adaptive.
Digital beamforming becomes central to making this architecture practical.
 
The same adaptive directional communication technologies being explored for terrestrial 6G mmWave deployments are equally essential for:
  • Satellite phased arrays
  • Inter-satellite laser communications
  • Direct-to-device satellite networking
  • Dynamic orbital spectrum reuse
The distinction between “cell tower” and “satellite node” may eventually become largely architectural rather than functional.

Solving the economics of 6G

One of the most important aspects of the BeammWave initiative is its focus on cost and power efficiency.
 
Historically, digital beamforming was considered impractical for mobile systems due to:
  • High power consumption
  • RF front-end complexity
  • Thermal limitations
  • Semiconductor integration challenges
But advances in silicon integration, signal processing efficiency, and AI-driven radio management are beginning to change that equation.
 
The 3GPP evaluation will specifically study:
  • Commercial power envelopes
  • Device implementation costs
  • Base station architecture impacts
  • Radio Resource Management requirements
  • Overall system integration procedures
These studies are crucial because future 6G networks will require unprecedented deployment density and computational coordination.
 
Without breakthroughs in efficiency, the economics of large-scale 6G infrastructure would become difficult to sustain.

Communications as a computational ecosystem

The deeper significance of this moment is philosophical as much as technical.
 
Wireless networking is no longer simply about transmitting signals between devices.
 
It is becoming a unified computational ecosystem spanning:
  • Terrestrial infrastructure
  • Orbital networks
  • AI-driven edge systems
  • Distributed compute resources
  • Software-defined spectrum management
In this emerging architecture, connectivity itself becomes intelligent.
 
Beamforming systems will continuously adapt to user movement, atmospheric conditions, orbital positioning, and network congestion in real time.
 
The network will increasingly think.

The inspirational horizon of 6G

The inclusion of digital beamforming in formal 3GPP discussions signals more than a standards milestone.
 
It reflects an industry beginning to reimagine the very nature of global communications.
 
Future wireless systems may no longer be bound by geography, infrastructure ownership, or even the distinction between Earth and orbit. Instead, they may function as a continuous intelligent fabric connecting satellites, cities, autonomous systems, industrial infrastructure, and billions of devices simultaneously.
 
What BeammWave and the broader 6G ecosystem are helping build is not simply a faster wireless network.
 
It is the foundation for a globally distributed, computationally intelligent communications layer capable of spanning the planet, and eventually, perhaps far beyond it.
The Large Magellanic Cloud has a mass of approximately 41 billion times that of the Sun.
The Large Magellanic Cloud has a mass of approximately 41 billion times that of the Sun.
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Pulsars as galactic scales: Supercomputer simulations reveal a new way to weigh neighboring galaxies

Astronomers at the University of Alabama in Huntsville have developed a new way to measure the mass of nearby dwarf galaxies. Instead of observing these galaxies directly, they track the subtle disturbances these galaxies cause in the Milky Way.
 
Their method, described in recent research, uses pulsars as highly sensitive gravitational sensors to detect tiny accelerations within our galaxy. A key part of this breakthrough was creating advanced supercomputer simulations that model how the Milky Way and its satellite galaxies interact over billions of years.
 
This work shows that modern astrophysics increasingly depends not just on telescopes, but also on powerful computers that can simulate the evolution of entire galaxies.

Pulsars as precision gravitational sensors

Pulsars, rapidly rotating neutron stars emitting highly regular radio pulses, are among the most precise natural clocks in the universe. Tiny changes in their observed timing can reveal equally tiny accelerations caused by gravitational forces.
 
Using these measurements, the researchers detected a vertical acceleration asymmetry near the Sun, evidence that the Milky Way disk is being gravitationally perturbed by nearby dwarf galaxies, particularly the:
  • Large Magellanic Cloud (LMC)
  • Sagittarius Dwarf Spheroidal Galaxy (Sgr dSph)
Rather than relying solely on stellar motions or chemical abundances, the team directly measured how these galaxies influence the Milky Way’s gravitational field in real time.
 
The result is a fundamentally new observational framework for galactic dynamics.

Simulating the Milky Way at the galactic scale

The core of the project depended on extensive N-body dynamical simulations executed on high-performance computing infrastructure. The simulations modeled:
  • A Milky Way-like galaxy
  • Dark matter halos
  • Disk stars and baryonic matter
  • Multiple orbiting dwarf galaxies.
  • Gravitational interactions evolving over billions of years
The researchers varied the masses of the LMC and the Sagittarius dwarf galaxy across numerous simulation runs, then compared the resulting acceleration fields with pulsar timing observations.
 
The computational challenge was immense.
 
Each simulation needed to resolve nonlinear gravitational perturbations propagating throughout the galactic disk while simultaneously tracking orbital evolution, tidal interactions, and dynamical friction effects over cosmological timescales.
 
The simulations revealed that the effects are highly nontrivial: increasing a satellite galaxy’s mass does not simply increase gravitational perturbations in a linear fashion. Instead, the interactions produce evolving waves, warps, and asymmetries across the entire Milky Way disk.

A galaxy in motion

One of the study’s most striking findings is that the Milky Way disk itself is dynamically active rather than gravitationally static.
 
The simulations showed large-scale vertical acceleration patterns sweeping across the disk, including ring-like structures and a measurable galactic tilt induced primarily by the passage of the Large Magellanic Cloud.
 
Researchers found that:
  • One side of the Milky Way disk accelerates upward.
  • The opposite side accelerates downward.
  • Disk warps lag behind the true gravitational acceleration field.
  • Satellite interactions induce global disequilibrium effects throughout the galaxy.
These structures emerged naturally from the simulations without specifically tuning the models to reproduce the observed warp of the Milky Way.
 
The results underscore the importance of supercomputer-based modeling in understanding galactic structure. Observations alone cannot directly visualize these evolving gravitational patterns.

Measuring the mass of neighboring galaxies

By matching simulation outputs to pulsar acceleration data, the researchers constrained the masses of the satellite galaxies with remarkable precision.
 
The simulations estimated that approximately 3 billion years ago:
  • The Large Magellanic Cloud possessed a total mass of approximately 2.0±0.5×10^11M⊙​.
  • The Sagittarius dwarf galaxy possessed a total mass of approximately
The present-day bound masses derived from the simulations were similarly detailed, including tidal radius estimates and enclosed dark matter distributions.
 
Importantly, the researchers demonstrated that pulsar acceleration measurements gathered within only a few kiloparsecs of the Sun can constrain properties of galaxies located tens of kiloparsecs away.
 
That capability emerges because gravitational disturbances propagate throughout the entire galactic structure.

The nonlinear universe

A major computational insight from the work is the deeply nonlinear nature of galactic interactions.
 
The simulations showed that the gravitational effects of the LMC and Sagittarius dwarf do not simply add together. Instead:
  • Tidal forces interact dynamically.
  • Satellite timing alters torque distributions.
  • Disk phase mixing changes over time
  • Dynamical friction reshapes orbital evolution.
As the researchers note, even simulations using identical satellite masses can produce dramatically different acceleration structures depending on orbital timing and relative positioning.
 
Capturing these effects requires precisely the kind of computational power modern supercomputing systems provide.

Supercomputing and the Future of Galactic Science

The study highlights an important evolution in astronomy: the transition from static observational models to real-time dynamical astrophysics.
 
Future pulsar timing datasets, combined with expanding HPC capabilities, could enable researchers to:
  • Map dark matter distributions more precisely.
  • Measure the structure of galactic halos.
  • Detect previously unknown satellite galaxies.
  • Study gravitational disequilibrium across the Milky Way
  • Build fully Bayesian dynamical models of galactic evolution.
The researchers emphasize that direct acceleration measurements offer a fundamentally new source of astrophysical information, one capable of complementing traditional stellar kinematics and chemical surveys.

Listening to gravity

Perhaps the most inspiring aspect of the work is its elegance.
 
By observing tiny variations in the ticking of dead stars, scientists can now weigh entire galaxies and reconstruct the invisible gravitational choreography shaping the Milky Way.
 
It is a reminder that modern supercomputing does more than accelerate calculations. It enables humanity to perceive structures and motions far beyond ordinary intuition.
 
The universe is constantly moving, warping, and interacting.
 
And increasingly, it is through simulation that we are learning how to listen.
A 300-millimeter quantum wafer. (Credit: IBM)
A 300-millimeter quantum wafer. (Credit: IBM)
Featured

IBM’s quantum foundry gamble reveals a troubling reality about the future of computing

The announcement of the United States’ first dedicated quantum foundry might be expected to represent a milestone in hardware engineering.
 
Instead, it reads like a warning.
 
This week, IBM and the U.S. Department of Commerce unveiled plans for a new company called Anderon, backed by a proposed $1 billion award under the CHIPS and Science Act, to build what officials describe as the nation’s first dedicated quantum chip manufacturing facility.
 
On the surface, the initiative appears visionary: a massive federal investment designed to secure American leadership in quantum computing. But beneath the headlines lies a more unsettling reality for the supercomputing industry.
 
The world’s appetite for compute has become so extreme that governments are now funding technologies that may not become commercially viable for years, or even decades.

Classical supercomputing is reaching its limits

For years, the growth of supercomputing followed a relatively predictable path. Faster CPUs, denser GPUs, and larger clusters steadily expanded the capabilities of high-performance computing systems.
 
That model is beginning to fracture.
 
Artificial intelligence training, climate simulation, molecular modeling, national security analytics, and exaflops workloads are consuming computational resources at rates that conventional semiconductor scaling can no longer comfortably sustain. Modern AI models now require millions of GPU-hours and enormous power budgets simply to remain competitive.
 
The compute crisis is no longer theoretical.
 
It is now driving governments and corporations toward increasingly speculative architectures in the desperate search for the next performance leap.
 
IBM’s new quantum foundry initiative reflects that pressure more than technological confidence.

A $2 billion bet born from fear

The broader federal initiative surrounding the IBM announcement includes roughly $2 billion in investments across multiple quantum firms, with the U.S. government taking direct equity stakes in several companies.
 
IBM alone is expected to receive approximately $1 billion in federal support while contributing another $1 billion of its own capital toward the Anderon facility in New Albany, New York.
 
Such investments reveal how seriously policymakers now view the compute bottleneck.
 
Quantum computing is no longer treated as a distant academic experiment. It has become a strategic hedge against the possibility that classical computing may soon be unable to meet future computational demand efficiently enough.
 
That shift should concern the HPC industry.
 
Despite decades of progress in CPUs, GPUs, accelerators, and interconnects, the world’s largest technology firms are effectively admitting that existing architectures may not scale fast enough to support the next generation of AI and scientific computing workloads.

The economics of compute are becoming unsustainable

The rise of exaflops systems has already exposed how fragile the economics of supercomputing have become.
 
Modern HPC facilities consume extraordinary amounts of power and require increasingly complex cooling infrastructure. AI datacenters are now forcing utilities to rethink regional power grids. 
 
Semiconductor fabrication costs continue to climb, while leading-edge process nodes become exponentially more difficult to manufacture.
 
Quantum computing promises an escape route, but one built on uncertainty.
 
Unlike conventional processors, quantum systems remain plagued by instability, decoherence, cryogenic operating requirements, and severe error-correction challenges. Useful fault-tolerant quantum systems still do not exist at a meaningful production scale.
 
Yet governments are investing billions anyway.
 
That is not necessarily a sign of confidence. It may instead reflect anxiety that current computing paradigms are approaching practical limits.

Supercomputing’s identity crisis

The HPC industry now faces a difficult paradox.
 
Demand for compute has never been higher. AI, simulation, and scientific workloads continue expanding at extraordinary rates. Organizations around the world are racing to build larger clusters, deploy more accelerators, and secure more energy capacity.
 
But the harder the industry pushes classical architectures, the clearer the limitations become.
 
This tension is reshaping the meaning of supercomputing itself.
 
Historically, supercomputers were engineering achievements built from deterministic, reliable hardware. Quantum computing introduces a radically different philosophy, probabilistic systems that require constant correction and may only outperform classical systems in highly specialized domains.
 
The danger is that the industry may be chasing quantum not because it is ready, but because it has run out of obvious alternatives.

CHIPS Act funding signals a strategic panic

The CHIPS and Science Act was originally framed to restore semiconductor manufacturing resilience and strengthen domestic supply chains.
 
Now, those same funding mechanisms are increasingly being redirected toward experimental quantum infrastructure.
 
IBM’s announcement makes clear that Washington no longer views quantum research as optional.
 
The concern is geopolitical as much as technological. China, Europe, and other global powers are aggressively pursuing quantum leadership, creating pressure on the United States to invest despite technical uncertainty.
 
That geopolitical urgency is accelerating funding decisions faster than the underlying science may justify.

The harsh reality ahead

Quantum computing may eventually revolutionize chemistry, optimization, cryptography, and scientific simulation. IBM and other researchers have undeniably made important progress toward scalable quantum architectures.
 
But the current investment frenzy also exposes a more uncomfortable truth: the computing industry is running out of easy paths forward.
 
The extraordinary rise of AI has pushed infrastructure demand beyond what conventional scaling strategies comfortably support. Supercomputing centers are consuming unprecedented power, datacenter costs are spiraling upward, and semiconductor development is becoming economically brutal.
 
IBM’s quantum foundry is therefore more than a manufacturing project.
 
It is evidence that the industry increasingly believes the future of computation may require abandoning many of the assumptions that built modern supercomputing in the first place.
 
And that realization carries less optimism than the headlines suggest.
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