Movable-Antenna Enabled Robust Vehicular Consumer Networks Under Imperfect CSI

TL;DR

This paper proposes a joint optimization of movable antennas and beamforming in vehicular networks to improve robustness and worst-case throughput under imperfect channel information.

Contribution

It introduces a novel framework for dynamically positioning movable antennas and optimizing beamforming to enhance communication reliability in vehicular networks with uncertain CSI.

Findings

Significant throughput gains over benchmarks in worst-case scenarios.

Effective joint optimization of antenna positions and beamforming.

Robust performance under CSI estimation errors.

Abstract

The accelerating advancement of intelligent transportation systems has established consumer-oriented vehicular networks (CVNs) as a critical infrastructure for next-generation connected mobility. However, the high mobility of vehicular users (VUs) introduces significant channel state information (CSI) uncertainty, which severely undermines the performance of conventional fixed-position antenna systems. To address this, this paper explores the deployment of movable-antennas (MAs) to enhance communication robustness in CVNs under imperfect CSI conditions. We develop a joint optimization framework that dynamically coordinates the spatial positioning of MAs and transmit beamforming at the base station, with the objective of maximizing the worst-case sum rate across all VUs. The problem is formulated as a non-convex max-min optimization problem, subject to bounded CSI estimation errors, transmit power limits, and physical constraints on antenna displacement. By adopting an alternating optimization strategy, the original problem is decomposed into tractable subproblems, solved via techniques including the S-Procedure, Schur complement, and successive convex approximation. Numerical evaluations confirm that the proposed approach achieves substantial gains over existing benchmarks in terms of worst-case throughput.