A RadBackCom Approach to Integrated Sensing and Communication: Waveform Design and Receiver Signal Processing

The emerging Internet of Things (IoT) and perceptive mobile networks are envisioned to provide broadband connectivity among a sheer number of connected users/devices and ubiquitous sensing capabilities. The integrated communication and sensing (ISAC) architectures achieve spectrum sharing between communications and sensing by encompassing just one active radio transmitter and two different receiving chains to accommodate the two functions. On the other hand, a promising technology for implementing low-power and low-cost communication is ambient backscatter communication (ABC), where a tag, often not connected to a battery or a power grid, can deliver a message to a reader by simply reflecting and modulating an incident ambient signal emitted by the radio frequency (RF) emitter of an existing legacy system. This project addresses various design aspects of a new ISAC architecture, called the RadBackCom system, which consists of a legacy radar system, and a backscatter communication system with the carrier signal being the radar clutter echoes. This research will significantly advance the state-of-the-art in the fields of ISAC and ABC. Practical use cases may include the exploitation of ground-based radars for air/road traffic control, environmental/weather monitoring, collision avoidance, intrusion detection, and radio imaging.Specifically, data transmission schemes will be developed when the legacy system is either a pure radar system or a dual functional radar communication (DFRC) system. When there are multiple tags transmitting data, transceiver schemes for both pilot-based sourced systems and pilot-free unsourced systems will be developed. Further, when the legacy system is assisted by a reflecting intelligent surface (RIS), several scenarios will be considered where the RIS also plays the role of an information-bearing tag, a one-bit reader, and a helper, respectively, in the RadBackCom system, and the corresponding solutions will be developed. The proposed approaches exploit an array of advanced techniques including compressed sensing, low-rank processing, simulation-based optimization, algebraic coding theory, iterative decoding, and deep neural networks, and will bring significant innovations to the theory and applications of both ISAC and ABC. Both a realistic simulator and a USRP software-defined radio testbed will be developed to validate the proposed algorithms.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.