Agile Signal Alignment for Congested and Contested Spectrum Access

As we begin to explore novel paradigms for next-generation spectrum access and management, there is growing consensus that non-exclusive spectrum sharing strategies will play a key role in realizing a compelling vision for Spectrum Era 4. Every non-exclusive use system is subject to unintended and unpredictable interference; even exclusive-use systems can suffer from interference due to misbehaving or malicious agents.

Finding more effective ways to deal with interference is of paramount importance on the road towards Spectrum Era 4 wireless prominence, which is needed to sustain the US technological and intellectual leadership and to support a thriving US economy. This project will develop a fundamentally new paradigm for efficient and reliable communication in the presence of unpredictable interference.

It will improve the performance, resilience, and reliability of wireless systems operating in shared, congested, and contested spectrum bands. The project specifically aims to address mitigation and autonomous recovery from harmful interference, service degradation or denial – key new spectrum capabilities that will empower Spectrum Era 4 systems.

The research draws from wireless communications theory and practice (including software radio programming and experimentation), statistical machine learning, signal processing and linear algebra. The findings will make impactful contributions to shared-spectrum wireless communications by introducing novel interference-immune communication modalities, with broader impacts on the above constituent disciplines.

The project will offer exciting educational opportunities and added value in terms of spectrum workforce development. Communications engineers with solid theoretical training and hands-on software radio skills are highly sought-after in Northern Virginia and other wireless industry hubs around the US. As part of this project, the PI will also work to identify and motivate students for undergraduate research, and to support his department’s broadening participation plan through the Allyship program that he helped co-found in 2020.

The PI recently proposed a very simple and practical method for (re)using spectrum occupied by a legacy service (e.g., analog or digital broadcast). The idea is to use repetition coding in a way that induces a common 1-D signal subspace at the multi-antenna receiver, while interference is different and spans distinct subspaces. Thus the signal of interest can be uniquely recovered using subspace intersection, implemented via canonical correlation analysis (CCA).

This signal alignment approach has been demonstrated to work under adverse time-varying interference, without any coordination or channel state information. Signal alignment is well-positioned to address key Spectrum Era 4 challenges, including autonomous recovery from service degradation, denial of service, security and privacy concerns. The project is designed to leverage signal alignment for effective communication in congested and contested environments, with particular focus on the following synergistic thrusts: 1) Streaming Time-Frequency Signal Alignment: Leveraging the algebraic structure of CCA and the shift structure of streaming data to enable computationally lightweight time-frequency signal alignment under unpredictable (e.g., intermittent) and potentially harmful interference; 2) Signal Alignment for Ultra Reliable Low Latency Communications (URLLC): Building on surprising insights obtained recently by the PI to boost CCA performance in the sample-starved (short packet) regime; 3) Full-rate Signal Alignment: Avoiding repetition which halves the transmission rate, this thrust will design and study the performance of signal alignment strategies that operate close to full-rate; and 4) Software radio experiments and validation: Judicious experiments will be conducted at UVA and the COSMOS PAWR testbed at Rutgers/WINLAB to validate the research in practice.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.