Distortion-Aware Beamforming for Integrated Sensing and Communication Systems

Abstract

Radar and communication systems have historically operated as separate entities but have gradually evolved toward higher frequency bands, large antenna arrays, and compact hardware designs. This evolution has resulted in converging hardware architectures and signal-processing techniques. This convergence has enabled the development of integrated sensing and communication (ISAC) systems, which integrate sensing and communication functionalities to optimize resource utilization and achieve mutual benefits. ISAC systems also reduce hardware costs, energy consumption, and signaling latency. However, their performance is often limited by transceiver hardware impairments (HWIs), which are unavoidable in practical implementations.

A dual-function radar communication base station (DFBS) is an example of an ISAC system where a single base station conducts both sensing and communication. DFBSs use digital beamforming or precoding to enable simultaneous communication with multiple users and sensing of targets. DFBSs are equipped with multiple radio frequency (RF) chains that include components such as filters, low noise amplifiers (LNAs), power amplifiers (PAs), mixers, local oscillators (LOs), analog to digital converters (ADCs), and phase shifters, among others. Despite using compensation techniques to cater to each of these HWIs, some residual HWIs inevitably remain. These residual HWIs distort the transmitted or the received signal on the antennas of the DFBS, thereby degrading the performance of both communication and sensing functionalities. While the effects of HWIs on communication and sensing systems have been widely studied independently, their combined impact on ISAC systems remains underexplored.

This thesis focuses on the design of transceivers for ISAC systems in the presence of residual HWIs, with the aim of optimizing communication and sensing performance simultaneously. A key component of this research is the use of beamforming techniques to design transmitted and received waveforms that meet specific communication and sensing metrics. By incorporating HWIs into the design process, the study seeks to address two research questions: (1) how can transmit precoders be designed for ISAC systems with residual HWIs to balance communication and sensing performance? (2) how can transmit precoders and receive combiners be jointly designed to achieve optimal performance in ISAC systems with residual HWIs?

The first part of this thesis addresses the design of transmit precoders for DFBS. By formulating an optimization problem that maximizes sensing performance while satisfying communication requirements, we demonstrate the importance of incorporating HWIs into the precoder design process. Numerical experiments reveal that for the same transmit power, distortion-aware design enhances communication system performance with a slight degradation in sensing performance compared to distortion-unaware design.

The second part of this thesis focuses on the joint transmitter-receiver (transceiver) design for ISAC systems with residual HWIs. We formulate the optimization problem to maximize the sensing performance while satisfying communication constraints for the users. We use an alternating optimization approach to iteratively optimize the transmit precoders and combiners at the radar receivers. Numerical results demonstrate that, for the same transmit power, the proposed distortion-aware design leads to better communication system performance with only a marginal decrease in the radar system performance as compared to its distortion-unaware counterpart.

This thesis contributes to the growing body of research on ISAC systems by offering a comprehensive transceiver design under HWIs. By analyzing the impact of residual HWIs and incorporating them into the design process, the study highlights the potential for improving ISAC system performance. The insights gained from this research in distortion-aware ISAC system design address the challenges in next-generation wireless networks.