We consider the combination of uplink code-domain non-orthogonal multiple access (NOMA) with massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surfaces (RISs). We assume a setup in which the base station (BS) is capable of forming beams towards the RISs under line-of-sight conditions, and where each RIS is covering a cluster of users. In order to support multi-user transmissions within a cluster, code-domain NOMA via spreading is utilized. We investigate the optimization of the RIS phase-shifts such that a large number of users is supported. As it turns out, it is a coupled optimization problem that depends on the detection order under interference cancellation and the applied filtering at the BS. We propose to decouple those variables by using sum-rate optimized phase-shifts as the initial solution, allowing us to obtain a decoupled estimate of those variables. Then, in order to determine the final phase-shifts, the problem is relaxed into a semidefinite program that can be solved efficiently via convex optimization algorithms. Simulation results show the effectiveness of our approach in improving the detectability of the users.
翻译:我们考虑将上链接代码- 代码- 代码- 非垂直多存( NOMA) 与大规模多输入多输出( MIMO) 和可重新配置的智能表面( RIS) 相结合。 我们假设一个设置,使基地台( BS) 能够在视觉线下对RIS形成光束, 并且每个RIS覆盖一组用户。 为了支持集内多用户传输, 使用通过传播的代码- 域域( NOMA) 代码- 代码- NOMA 进行。 我们调查RIS 阶段性变换的优化, 以便支持大量用户。 事实证明, 最优化是一个同时存在的问题, 取决于干扰取消中的探测顺序和BS 应用过滤。 我们提议将这些变量进行调和, 使用以超速优化的阶段变换位法作为初始解决方案, 以便我们获得这些变量的分解估计值。 然后, 为了确定最后的阶段变换位, 问题将缓和成一个半确定程序, 从而可以通过 convex 优化用户的算法来有效解决。 。