大规模MIMO系统中基于模等式约束的降维去相干DOA估计
Modulus Equation Constraints Based Decoherent Dimension Reduction 2-D DOA Estimation for Massive MIMO Systems
摘要: 大规模MIMO系统中存在大量相干信号,简单的去相干处理导致二维波达方向(DOA, Direction of Arrival)估计的精度较低。为此,本文提出一种能够大幅度提高相干信号二维DOA估计性能的模等式约束降维MUSIC算法。该算法将二维DOA估计问题转化为优化问题,并采用模等式约束法定义附加条件,对方向矢量施加较强的约束,使优化方程求解更接近最优解。理论分析和仿真实验结果表明,本文提出的去相干DOA算法的可靠性与精度高,满足大规模MIMO系统的DOA估计性能需求,具有较强的可行性和实用性。
Abstract: There are large numbers of coherent signals in massive MIMO system. Simple decoherence pro-cessing leads to the lower accuracy of the 2-D DOA (Two-Dimensional Direction of Arrival). This paper will propose a modulus equation constraints based dimension reduction MUSIC algorithm which can greatly improve the performance of two-dimensional DOA estimation of coherent signals. The algorithm transforms the two-dimensional DOA estimation problem into an optimization problem, and uses the modulus equation constraints to define the additional conditions and impose strong constraints on the direction vector so that the optimization equation is solved more close to the optimal solution. The results of theoretical analysis and simulation experiments show that the proposed DOA algorithm has high reliability and precision. Such algorithm is able to meet the requirements of DOA estimation performance in massive MIMO system, and can also provide high feasibility and practicability.
文章引用:孙鹏帅, 余小游, 林培英, 杜青松, 马和峰, 田丽佳, 蒋娅林. 大规模MIMO系统中基于模等式约束的降维去相干DOA估计[J]. 无线通信, 2018, 8(3): 123-132. https://doi.org/10.12677/HJWC.2018.83014

参考文献

[1] Xu, K., Nie, W., Feng, D., et al. (2016) A Multi-Direction Virtual Array Transformation Algorithm for 2D DOA Estimation. Signal Processing, 125, 122-133.
[2] Tayem, N. and Kwon, H.M. (2005) L-Shape 2-Dimensional Arrival Angle Estimation with Propagator Method. IEEE Transactions on Antennas and Propagation, 53, 1622-1630.
[Google Scholar] [CrossRef
[3] 王伟, 王小萌, 等. 基于MUSIC算法的L型阵列MIMO雷达降维DOA估计[J]. 电子与信息学报, 2014, 36(8): 1954-1959.
[4] Liang, J.L. and Liu, D. (2010) Joint Elevation and Azimuth Direction Finding Using L-Shaped Array. IEEE Transations on Antennas and Propagation, 58, 2136-2141.
[Google Scholar] [CrossRef
[5] Cuangmin, W., Jingmin, X. Nanning, Z., et al. (2011) Computationally Efficient Subspace-Based Method for Two-Dimensional Direction Estimation with L-Shaped Array. IEEE Transactions on Signal Process, 59, 3197-3212.
[Google Scholar] [CrossRef
[6] Nie, X. and Li, L.P. (2014) A Computationally Efficient Subspace Algorithm for 2-D DOA Estimation with L-Shaped Array. IEEE Transactions on Signal Processing Letters, 21, 971-974.
[Google Scholar] [CrossRef
[7] Wei, Y.S. and Guo, X.J. (2014) Pair-Matching Method by Signal Covariance Matrices for 2D-DOA Estimation. IEEE Antennas Wireless Propagaton Letters, 13, 1199-1202.
[8] 杨艳飞, 高健, 张兴敢, 等. 一种基于L型阵列的改进的二维DOA估计方法[J]. 南京大学学报, 2016, 52(5): 953-959.
[9] 梁浩, 崔琛, 代林, 等. 基于ESPRIT算法的L型阵列MIMO雷达降维DOA估计[J]. 电子与信息学报, 2015, 37(8): 1823-1835.
[10] 张艳萍, 赵玉垒, 孙心宇. 一种L型阵列的相干分布降维DOA估计方法[J]. 计算机应用研究, 2016, 33(5): 1477-1480.
[11] 熊波, 李国林, 尚雅玲, 高云剑. 信号相关性与DOA估计[J]. 电子科技大学学报, 2007, 36(5): 907-910.
[12] 张小飞, 汪飞, 陈伟华. 阵列信号处理的理论与应用[M]. 北京: 国防工业出版社, 2013: 22-23.
[13] 景小荣, 刘雪峰. L型阵列的二维DOA估计方法[J]. 重庆邮电大学学报(自然科学版), 2016(1): 24-29.
[14] Zhang, X.F., Xu, L.Y., Xu, L., et al. (2010) Direction of Departure (DOD) and Direction of Arrival (DOA) Estimation in MIMO Radar with Reduced-Dimension MUSIC. IEEE Communication Letters, 14, 1161-1163.
[Google Scholar] [CrossRef
[15] 刘聪锋, 廖桂生. 基于模约束的稳健Capon波束形成算法[J]. 电子学报, 2008, 36(3): 440-445