Separating or Sharing: Tradeoff Oriented Joint Optimization of Beamforming and Reflective Precoding in Active RIS-Enabled ISAC System

Abstract

Integrated sensing and communication (ISAC) is potentially viewed as a key driver in the ubiquitous service of future wireless systems. However, numerous challenges should be solved before the alluring benefits are enjoyed. Although enhancement of sensing capabilities inevitably leads to a reduction in the communication performance, the loss can be compensated through the emerging reconfigurable intelligent surface (RIS). Specifically, active RIS is more favored because the “multiplicative fading” effect existed in passive RIS is overcome, and the manipulation effectiveness of wireless environments can be further enhanced. To this end, this paper investigates the simultaneous optimization of the transmit beamforming at base station (BS) and the precoding at RIS. To fully explore the potential of the active RIS-enabled ISAC system, two antenna deployment strategies, i.e., separated deployment and shared deployment, are designed to maximize the communication users’ sum-rate under the considered constraints including transmission power, probing power and reflection manipulation, etc. Furthermore, an effective algorithm combining fractional programming and semidefinite relaxation is employed to derive a sub-optimal solution through an alternating optimization framework due to the non-convex characteristic of the initial problem. Finally, the simulation results demonstrate that more superior transmit beampatterns can be achieved in the shared deployment in comparison with the separated deployment, and that the sum-rate’s upper bound is significantly enhanced in the active RIS when comparing to traditional passive RIS.