Hybrid Beamforming for Multi-User Near-Field Ultra-Massive MIMO Capacity Improvement

Ultra-massive multiple-input multiple-output (UM-MIMO) systems with hybrid beamforming architectures are extensively studied to enhance the capacity of future wireless networks. As the number of antennas increases, the near-field property of UM-MIMO systems becomes significant. Unlike the classical far-field line-of-sight (LoS) channel with single available data stream, the near-field LoS channel offers a significantly increased spatial degrees-of-freedom (DoFs) to enable the LoS spatial multiplexing. However, most of the existing literature considered single-user transmission scenarios. Hence, we focus our attention on the more challenging design of hybrid beam-forming for multi-user UM-MIMO systems by leveraging the extra spatial DoFs available in the near-field region. Specifically, the available spatial DoFs and the capacity upper bound of the near-field LoS channel are theoretically analyzed at first. Then, to exploit the near-field property as a new possibility for capacity improvement, a block diagonal geometric mean decomposition (BD-GMD) multi-user near-field hybrid beamforming algorithm is proposed. The key idea of our approach is to allocate specific subarrays for different users to optimize their channel eigenvalue distribution, thereby maximizing multi-user spatial multiplexing performance as well as minimizing inter-user interference. Simulation results demonstrate that the proposed BD-GMD scheme achieves a significant capacity improvement compared to conventional approaches.