🤖 AI Summary
This work addresses the joint optimization of fluid antenna systems (FAS) and constructive interference (CI)-based precoding for multiuser MIMO downlink, aiming to minimize the maximum symbol error probability (SEP), under the constraint that each antenna’s position is continuously adjustable within non-overlapping intervals. We propose, for the first time, a unified framework that co-designs FAS antenna placement and CI precoding, formulated as a safety-margin maximization problem. To tackle the resulting non-convex optimization efficiently, we develop a low-complexity block coordinate descent algorithm leveraging smoothing techniques. Compared with conventional fixed-antenna arrays and PSO-based FAS designs, the proposed method achieves significant SEP reduction while substantially lowering computational complexity—thereby delivering both performance gains and practical feasibility.
📝 Abstract
The fluid antenna system (FAS) has emerged as a new physical-layer concept to provide enhanced propagation conditions for multiuser multiple-input multiple-output (MIMO) communications over conventional fixed arrays. This work focuses on minimizing the maximum symbol error probability (SEP) under $M$-ary phase shift keying (MPSK) signaling in a multiuser downlink equipped with FAS, where each antenna moves within nonoverlapping intervals. This specific problem of joint SEP minimization with FAS and constructive interference (CI) precoding has not been previously addressed. The resulting problem turns out to be a nonconvex and nonsmooth optimization challenge. We transform the SEP minimization problem into a safety margin maximization problem in constructive interference precoding. Then, we customize a smoothing technique and a block coordinate descent (BCD) algorithm, with emphasis on low computational complexity. Simulation results show that our approach can reduce bit error rate (BER) compared to both the fixed arrays and FAS designed by existing particle swarm optimization (PSO). Also, our approach shows attractively low computational complexity compared to PSO benchmarks.