Department of Electrical Engineering, National University of Computer and Emerging Science, Islamabad 44000, Pakistan.
Department of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea.
Sensors (Basel). 2020 Sep 17;20(18):5338. doi: 10.3390/s20185338.
Hybrid pre-coding strategies are considered as a potential solution for combating path loss experienced by Massive MIMO systems operating at millimeter wave frequencies. The partially connected structure is preferred over the fully connected structure due to smaller computational complexity. In order to improve the spectral efficiency of a partially connected hybrid pre-coding architecture, which is one of the requirements of future 5G/B5G systems, this work proposes the application of evolutionary algorithms for joint computation of RF and the digital pre-coder. The evolutionary algorithm based scheme jointly evaluates the RF and digital pre-coder for a partially connected hybrid structure by taking into account the current RF chain for computations and therefore it is not based on interference cancellation from all other RF chains as in the case of successive interference cancellation (SIC). The evolutionary algorithm, i.e., Artificial Bee Colony (BEE) based pre-coding scheme outperforms other popular evolutionary algorithms as well as the SIC based pre-coding scheme in terms of spectral efficiency. In addition, the proposed algorithm is not overly sensitive to variations in channel conditions.
混合预编码策略被认为是克服大规模多输入多输出（MIMO）系统在毫米波频率下经历的路径损耗的一种潜在解决方案。由于较小的计算复杂度，部分连接结构优于全连接结构。为了提高部分连接混合预编码架构的频谱效率，这是未来 5G/B5G 系统的要求之一，这项工作提出了应用进化算法来联合计算射频和数字预编码器。基于进化算法的方案通过考虑当前的射频链进行计算，联合评估部分连接混合结构的射频和数字预编码器，因此它不是基于所有其他射频链的干扰消除，如在连续干扰消除（SIC）的情况下。基于进化算法，即基于人工蜂群（BEE）的预编码方案，在频谱效率方面优于其他流行的进化算法以及基于 SIC 的预编码方案。此外，所提出的算法对信道条件的变化不敏感。
