The stringent requirements on reliability and processing delay in the fifth-generation ($5$G) cellular networks introduce considerable challenges in the design of massive multiple-input-multiple-output (M-MIMO) receivers. The two main components of an M-MIMO receiver are a detector and a decoder. To improve the trade-off between reliability and complexity, a Bayesian concept has been considered as a promising approach that enhances classical detectors, e.g. minimum-mean-square-error detector. This work proposes an iterative M-MIMO detector based on a Bayesian framework, a parallel interference cancellation scheme, and a decision statistics combining concept. We then develop a high performance M-MIMO receiver, integrating the proposed detector with a low complexity sequential decoding for polar codes. Simulation results of the proposed detector show a significant performance gain compared to other low complexity detectors. Furthermore, the proposed M-MIMO receiver with sequential decoding ensures one order magnitude lower complexity compared to a receiver with stack successive cancellation decoding for polar codes from the 5G New Radio standard.
翻译:对第五代移动电话网络的可靠性和处理延迟的严格要求($G)对第五代($5G)移动电话网络的可靠性和处理延迟提出了相当大的挑战,在设计大型多投入-多输出接收器方面提出了相当大的挑战。M-MIMO接收器的两个主要组成部分是探测器和解码器。为了改进可靠性和复杂性之间的权衡,一种巴伊西亚概念被认为是一种有希望的方法,可以加强古典探测器,例如最低中位分解器探测器。这项工作提议在巴伊西亚框架、平行干扰取消计划和综合概念的决定统计的基础上,建立一个迭代M-MIMO探测器。然后,我们开发一个高性能M-MIMO接收器,将拟议的探测器与极地码的低复杂顺序解码器结合起来。拟议的探测器的模拟结果表明,与其他低复杂度探测器相比,其性能有很大的提高。此外,拟议的M-MIMO接收器按顺序解码进行分解,其复杂性比5G新电台标准连续取消极地编码的接收器低一等。