Rotatable Antenna Enhanced Multicast Communication System

2026-03-27

AI Summary

This work addresses the issue of insufficient user fairness in multi-group downlink multicast communication by proposing a novel joint optimization framework that integrates multicast beamforming with steerable antenna beam orientation. The method maximizes the minimum signal-to-interference-plus-noise ratio (SINR) among all users, subject to transmit power and mechanical rotation constraints. By innovatively incorporating rotatable antennas into the multi-group multicast system, the approach introduces additional spatial degrees of freedom to enhance fairness. The non-convex problem is tackled via a quadratic transformation of the objective function within an alternating optimization framework: the beamforming subproblem is solved using convex optimization techniques, while the antenna orientation is iteratively updated via successive convex approximation. Simulation results demonstrate that the proposed scheme significantly outperforms benchmark methods employing fixed or randomly oriented antennas in terms of user fairness.

Abstract

Rotatable antenna (RA) provides additional spatial degrees of freedom (DoFs) for communication systems by enabling per-antenna dynamic boresight adjustment, which is attractive for fairness-oriented multicast transmission. This letter investigates an RA-enhanced downlink multi-group multicast system. Specifically, we aim to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all users by jointly optimizing the multicast beamforming vectors and the RA boresight directions under transmit power and rotation constraints. To solve this non-convex problem, we first reformulate the max-min SINR objective via quadratic transform. Then, we develop an alternating optimization (AO) algorithm that iteratively updates the multicast beamforming and RA boresight directions. The beamforming vectors are obtained from a convex subproblem, while the boresight directions are refined using a successive convex approximation (SCA) procedure. Simulation results verify that the proposed RA-based scheme substantially enhances the fairness performance compared with fixed antenna-based and random-orientation benchmarks.

Problem

• rotatable antenna
• multicast communication
• max-min SINR
• beamforming
• fairness

Innovation

• Rotatable Antenna
• Multicast Communication
• Max-Min SINR
• Alternating Optimization
• Successive Convex Approximation