In this paper, we consider a reconfigurable intelligence surface (RIS) aided uplink multiuser multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) system, where the receiver is assumed to conduct low-complexity iterative detection. We aim to minimize the total transmit power by jointly designing the precoder of the transmitter and the passive beamforming of the RIS. This problem can be tackled from the perspective of information theory. But this information-theoretic approach may involve prohibitively high complexity since the number of rate constraints that specify the capacity region of the uplink multiuser channel is exponential in the number of users. To avoid this difficulty, we formulate the design problem of the iterative receiver under the constraints of a maximal iteration number and target bit error rates of users. To tackle this challenging problem, we propose a groupwise successive interference cancellation (SIC) optimization approach, where the signals of users are decoded and cancelled in a group-by-group manner. We present a heuristic user grouping strategy, and resort to the alternating optimization technique to iteratively solve the precoding and passive beamforming sub-problems. Specifically, for the precoding sub-problem, we employ fractional programming to convert it to a convex problem; for the passive beamforming sub-problem, we adopt successive convex approximation to deal with the unit-modulus constraints of the RIS. We show that the proposed groupwise SIC approach has significant advantages in both performance and computational complexity, as compared with the counterpart approaches.
翻译:在本文中,我们考虑的是可重新整合的智能表面(RIS), 帮助将多用户多输出多输出产出(MIMO)或多频分多解(OFDM)系统(OFDM)连接起来, 接收者假定在该系统中进行低复现迭代检测。 我们的目标是通过联合设计发报机的预编码器和RIS的被动波束来最大限度地减少总传输力。 这个问题可以从信息理论的角度加以解决。 但是,这种信息理论方法可能涉及极高的复杂程度, 因为指定多用户频道上链接能力区域的费率限制数量在用户数量上呈指数化。 为避免这一困难,我们设计了迭代接收者的设计问题,在最大迭代数和用户目标误差率的限制下,我们的目标是通过联合设计发送信号的连续取消(SICE)优化方法,在用户信号以逐组方式解码和取消时,我们提出了一个超常分类用户组合战略,并采用交替优化技术,在不断更新的单位单位组合下,将我们相对成本的预变变变的组合转换为我们前的组合。