Energy Efficiency Optimization for MA-Enabled Hybrid MIMO Communication Networks

Movable antenna (MA) has been recognized as a promising technology to enhance communication network performance by adjusting the antenna position within a confined region. In this article, we consider an energy-efficient MA-enabled multiple-input–multiple-output (MIMO) network with the hybrid analog–digital transceiver, where energy consumption induced by the MA movement is additionally considered to accurately evaluate the system energy efficiency (EE) performance. Under both fully connected and partially connected transceiver structures, we aim to maximize the system EE by jointly optimizing the hybrid beamformers and antenna positions, subject to the unit-modulus constraints and the minimum MA distance constraints. To tackle these two highly nonconvex problems effectively, we propose an efficient two-layer successive convex approximation (SCA)-based iterative algorithm, where we aim to iteratively update the achievable EE in the outer layer and alternately optimize the hybrid beamformers and antenna positions in the inner layer. Furthermore, considering the asymptotically low-SNR and high-SNR regimes, we, respectively, develop two low-complexity algorithms by leveraging the structural properties of their corresponding optimal fully digital beamformers. Simulation results validate the superior EE performance and low-complexity advantage of our proposed algorithms over the existing benchmark schemes.