We investigate a reconfigurable intelligent surface (RIS)-aided multi-user massive multiple-input multi-output (MIMO) system where low-resolution digital-analog converters (DACs) are configured at the base station (BS) in order to reduce the cost and power consumption. An approximate analytical expression for the downlink achievable rate is derived based on maximum ratio transmission (MRT) and additive quantization noise model (AQNM), and the rate maximization problem is solved by particle swarm optimization (PSO) method under both continuous phase shifts (CPSs) and discrete phase shifts (DPSs) at the RIS. Simulation results show that the downlink sum achievable rate tends to a constant with the increase of the number of quantization bits of DACs, and four quantization bits are enough to capture a large portion of the performance of the ideal perfect DACs case.

中文翻译：

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具有低分辨率 DAC 的可重构智能表面辅助大规模 MIMO 系统


我们研究了一种可重构智能表面（RIS）辅助的多用户大规模多输入多输出（MIMO）系统，其中在基站（BS）配置低分辨率数模转换器（DAC）以减少成本和功耗。基于最大比传输（MRT）和加性量化噪声模型（AQNM）推导了下行可达到速率的近似解析表达式，并通过粒子群优化（PSO）方法解决了连续相移（CPS）下的速率最大化问题）和 RIS 处的离散相移 (DPS)。仿真结果表明，随着DAC量化位数的增加，下行总和可达速率趋于恒定，4个量化位数足以捕获理想完美DAC情况下的大部分性能。