1. NYU WIRELESS has delivered a string of research successes over the years — what are some of the new projects being worked on that excite you the most?
Several areas at NYU WIRELESS are particularly exciting right now: satellite–cellular integration, the upper mid-band, and, of course, AI. Satellite connectivity is evolving rapidly with mega-constellations, and we're looking at how terrestrial networks can work seamlessly with them.
The upper mid-band — roughly 6 to 15 GHz — gives you more capacity than traditional cellular bands and better coverage than millimeter-wave. The challenge is that it has to coexist with satellite services, which makes for some interesting research problems.
AI has two aspects: how AI can be used to optimize networks and how networks and mobile devices can be optimized for AI. For network optimization using AI, the key challenge is large-scale realistic simulation, or digital twins, to generate sufficient data for training AI models. Here we need to add radio propagation into visual and 3D models.
For optimizing the network for AI, we need high performance, low power computational platforms for AI to run on mobile devices. AI will also need many more devices, including sensors and wearables, to be connected to aggregate data and connect devices with powerful cloud-based compute. We will have to drive the power consumption for connectivity significantly down which will in turn need innovations in everything from the architecture to the devices.
2. You are leading an academic and industry team that secured nearly $10 million in federal funding for Spectrally Agile Large-Scale Arrays (SALSA), what are the goals and timelines for this project?
SALSA is an ambitious effort to develop spectrally agile wireless arrays that can dynamically adapt across frequencies and support massive MIMO operation in the upper mid-band. The goal is to reduce cost and complexity while improving flexibility and performance, essentially creating the foundation for scalable 6G and Open RAN systems.
It's a multi-year collaboration running through 2028, with testing at Rutgers WINLAB and the COSMOS testbed in New York City. The National Telecommunications and Information Administration is funding it.
3. What partners are involved and what are their roles?
The team brings together academic and industry expertise. At NYU Tandon, I work closely with Hamed Rahmani on radio design and integration. Princeton's Kaushik Sengupta leads complementary chip research.
Rutgers WINLAB provides one of the country's largest Open RAN testing environments. On the industry side, we have Pi-Radio (an NYU WIRELESS spinoff) building prototype hardware, along with Nokia and Analog Devices supporting evaluation and integration for real-world deployment.
4. What trends and applications do you see coming for 6G?
The first key trend is, of course, AI. At the network level that means that many more devices are connected with much higher data rates, particularly in the uplink. Essentially, the network can act as a sensory platform gathering data from multiple sources to drive intelligent decisions for diverse applications. The devices are also changing to support more complex AI models.
The second trend is security. The communication network is vital to the economy, and, as AI evolves, more sensitive and critical data will go over the network. So, we will have to consider the robustness of networks to hostile attacks much more seriously. In addition, as spectrum is scarce, operators will rely on increased sharing of spectrum and other resources, and this trend raises other questions of trust.
A third trend is towards new ways of interaction. In the future, the smartphone may not be the most common way we interact with one another. The industry has seen a lot of investment in immersive AR/VR, both in graphics and devices. If networks can support these devices, we can imagine much richer ways to interact.
Finally, networks have to provide more ubiquitous coverage, particularly for rural areas. Economic participation requires connectivity. This need is, in part, what is driving the satellite revolution.
5. What kind of research are you doing with THz signals and do you see them being used for 6G?
Terahertz bands above 100 GHz provide vast bandwidth, but they face real challenges, with high loss and costly components being the main ones. They're best suited for short-range, ultra-high speed links, backhaul and precision sensing rather than broad coverage.
In contrast, the upper mid-band will likely serve as the backbone for 6G, offering the right combination of capacity, coverage and efficiency.
6. How about joint communications and sensing work for 6G?
JCAS is one of the most promising directions in wireless right now. The idea is using the same hardware and spectrum for both communication and sensing, which enables new applications, from vehicles that can detect obstacles to smart infrastructure that monitors activity while maintaining connectivity. Our SALSA platform is designed to support these dual functions, and the upper mid-band provides a good balance of range and resolution for both.
7. What kind of new devices and circuits are being developed for wireless applications?
We're designing new radio hardware that offers wide frequency agility, fast beam switching and integrated beamforming across many channels. By distributing processing across multiple low-power modules, we can reduce both cost and energy per channel. These advances are helping make large-scale massive MIMO systems commercially viable. There is a lot of great work in our center and elsewhere on mobile AI accelerators, and privacy preserving compute that will be needed for the next generation of devices.
8. Some of the NYU WIRELESS' work is done with the Medical School, what kind of research is being done in the area of healthcare?
Right now, we’re collaborating with NYU Langone on a project to develop assistive navigation technology for people with blindness or low vision. The system has been tested in virtual environments and combines computer vision, wireless localization, spatial audio and haptic feedback to help users safely navigate complex spaces. It's a strong example of how wireless research can directly improve accessibility and quality of life.
9. What kind of work is being done in the area of AI/ML and quantum technologies?
As I said, AI is being used everywhere in wireless, and our center is no exception. We are looking at optimizing virtually every aspect of the network with data and digital twins. A lot of our hardware work is also focused on getting AI working efficiently in mobile devices.
Quantum technologies are less immediate but essential for security. Post-quantum cryptography and quantum-resilient links will shape future standards, and NYU has made significant investments in the area with a new Quantum Institute.
10. What future technologies excite you the most in the area of wireless?
I'm most excited by the convergence of communication, sensing and intelligence. When networks can perceive and adapt to their surroundings, entirely new applications become possible, from autonomous mobility to immersive AR to accessible smart infrastructure.
The upper mid-band offers a strong foundation for these developments. Combined with open architectures, democratized RF tools and inclusive design, we're moving toward wireless systems that are more intelligent, adaptable and human-centered.
NYU WIRELESS has been fortunate to help drive that evolution, from our early millimeter-wave breakthroughs recognized by the IEEE to today's work on 6G and beyond.