The scale, density and traffic demands of mobile network deployments is increasing rapidly. Integrated sensing and communication (ISAC) is considered to be a critical capability for 6G to address this evolution through efficient spectrum sharing and access mechanisms. While several strides to increase spectral efficiency through advanced multiplexing strategies have been made in licensed spectrum, the inability to accurately assess the impact of external interference leads to significant performance degradation during dynamic spectrum access. In one thrust, we aim to mitigate this degradation by leveraging a new notion of “network as a distributed sensor” through scalable learning, and optimal and intelligent algorithms, all without relying on explicit sensing capabilities in the network. In another thrust, we supplement the network with passive intelligent surfaces and corresponding orchestration mechanisms that can readily work with practical mmWave radars and base stations to enhance both the network’s communication and sensing capabilities. More … 

Localization (or Positioning) is a key technology for the next generation 5G wireless systems (both WiFi and cellular) to cater to the needs of interactive, immersive, and robot-human applications. Such applications require not only sub-meter localization accuracy but also highly demanded communication throughput. In this research theme, we explore the intricate problems and challenges that need to be addressed to make the systems have better localization accuracy without sacrificing communication performance even in challenging GPS-denied, sparse-no infrastructure, low SNR environments. More …

This theme explores the design and deployment of sustainable IoT wireless tags that can operate on ultra-low energy budgets while interacting with commodity devices already in our everyday environments to enable various sensing and tracking applications on a large scale. We investigate both RF (link) and acoustic (link) wireless modalities in our tag designs and address fundamental challenges specific to these two modalities to create new capabilities at frugal energy footprints that enable novel IoT applications.

This theme explores the robustness challenges in bringing mmWave sensing to real-world deployments. The sparsity of reflected mmWave signals has been a long-standing challenge for indoor mmWave radar sensing solutions, often limiting them to short range and LoS sensing. We explore various dimensions of diversity in bringing robustness to this environment, ranging from the use of multi-radar diversity complemented by intelligent, data-driven, artifact-agnostic algorithms to the use of passive reconfigurable surfaces with information encoding properties. We aim to enable practical human well-being applications (e.g. remote physical rehabilitation) with commodity mmWave radars for everyday indoor environments. More …