Reconfigurable Intelligent Surface Assisted Massive MIMO With Antenna Selection

Antenna selection is capable of reducing the hardware complexity massive multiple-input multiple-output (MIMO) networks at cost certain performance degradation. Reconfigurable intelligent surface (RIS) has emerged as a cost-effective technique that can enhance spectrum-efficiency wireless by reconfiguring propagation environment. By employing RIS to compensate for loss due antenna selection, in this paper we propose new network architecture, i.e., RIS-assisted MIMO system with while enjoying low cost. This achieved maximizing channel capacity via joint and passive beamforming taking into account cardinality constraint active antennas unit-modulus constraints all elements. However, formulated problem turns out be highly intractable non-convex coupled optimization variables, which an alternating framework provided, yielding subproblems. The computationally efficient submodular algorithms are developed solve subproblem under different state information assumptions. iterative based on block coordinate descent further proposed design exploiting unique structures. Moreover, feasible any finite number antennas, thus applicable both ordinary settings. Experimental results will demonstrate algorithmic advantages desirable systems selection.