An Efficient Sum-Rate Maximization Algorithm for Fluid Antenna-Assisted ISAC System

TL;DR

This paper proposes an efficient algorithm for optimizing sum-rate and sensing in fluid antenna-assisted ISAC systems, significantly reducing computation time while achieving state-of-the-art performance.

Contribution

It introduces a novel optimization algorithm combining block successive upper bound minimization and majorization-minimization for fluid antenna position and waveform design.

Findings

Achieves at least 60% reduction in computation time compared to existing methods

Attains state-of-the-art sum-rate performance in simulations

Effectively optimizes fluid antenna positions and waveforms for ISAC systems

Abstract

This letter investigates a fluid antenna (FA)-assisted integrated sensing and communication (ISAC) system, with joint antenna position optimization and waveform design. We consider enhancing the sum-rate maximization (SRM) and sensing performance with the aid of FAs. Although the introduction of FAs brings more degrees of freedom for performance optimization, its position optimization poses a non-convex programming problem and brings great computational challenges. This letter contributes to building an efficient design algorithm by the block successive upper bound minimization and majorization-minimization principles, with each step admitting closed-form update for the ISAC waveform design. In addition, the extrapolation technique is exploited further to speed up the empirical convergence of FA position design. Simulation results show that the proposed design can achieve state-of-the-art sum-rate performance with at least 60% computation cutoff compared to existing works with successive convex approximation (SCA) and particle swarm optimization (PSO) algorithms.