BER Performance Optimization for Fluid Antenna-Aided Wireless Communications

This contribution focuses on the optimization of bit error rate (BER) performance in fluid antenna (FA)-aided wireless communication systems, which leverage the new degrees of freedom provided by positional flexibility, thus surpassing the limitations of conventional fixed-position antenna (FPA) systems. In this context, a theoretical analysis identifies key metrics for maximum likelihood (ML) and zero-forcing (ZF) detectors, specifically the minimum singular value and effective rank, as determinants of system performance. Then, for single-input single-output (SISO) channels, the optimization problem is formulated as channel gain maximization constrained by the predefined moving region and then solved using a mixed-integer linear programming (MILP) model. Furthermore, for multiple-input multiple-output (MIMO) channels, an alternating optimization (AO) algorithm incorporating the Frank-Wolfe method is proposed to optimize ML and ZF performances, targeting minimum singular value maximization for ML and singular value balancing for ZF, both subject to moving region and antenna spacing constraints. Finally, numerical results exhibit significant performance gains for the FA system over its conventional FPA alternative. In general, these findings highlight the potential of FA systems for addressing ultra-reliable communication challenges in the sixth generation (6G) wireless communications.