兰州交通大学电子与信息工程学院
国家自然科学基金资助项目（61741113）；甘肃省高等学校创新能力提升项目（2019B-052）
School of Electronic and Information Engineering of Lanzhou Jiaotong University
Gansu Provincial Institutions of Higher Learning Innovation Ability Promotion Project (2019B-052) and National Science Foundation of China with grant No.61741113
基于信道矩阵的维度高以及接收信号复杂这种情况，提出了一种适用于大规模 MIMO系统上行链路信号检测的混合迭代算法，即自适应阻尼雅克比（Damped Jacobi，DJ）算法和共轭梯度（Conjugate Gradient，CG）算法相结合。首先利用共轭梯度算法为自适应阻尼雅克比迭代算法提供有效的搜索方向，随后提出切比雪夫方法消除松弛参数对信号检测的影响，降低算法复杂度的同时，加快收敛速度，最后，通过利用信道编译码中的比特似然比近似求解软信息。仿真结果表明，混合迭代算法在少量迭代次数下快速收敛并近似达到最佳MMSE检测性能，且算法复杂度远低于MMSE算法。
Based on the high dimension of the channel matrix and the complexity of the received signals, a hybrid iterative algorithm signal detection on uplink for large-scale MIMO systems is proposed, which combines adaptive damped Jacobi (DJ) algorithm and conjugate gradient (CG) algorithm. Firstly, conjugate gradient algorithm is used to provide effective search direction for adaptive damped Jacobian iterative algorithm. Then, Chebyshev method is proposed to eliminate the influence of relaxation parameters on signal detection to reduce the complexity of the algorithm and accelerate the convergence speed. Finally, the soft information is approximately solved by using the bit likelihood ratio in channel coding and decoding. The simulation results show that the hybrid iterative algorithm converges quickly and approximately achieves the best MMSE detection performance under a small number of iterations, and the algorithm complexity is far lower than that of MMSE algorithm.
