﻿ 基于大规模MIMO的信道检测算法研究 Research on Channel Detection Algorithm Based on Massive MIMO Communication System

Hans Journal of Wireless Communications
Vol.07 No.02(2017), Article ID:20249,8 pages
10.12677/HJWC.2017.72007

Research on Channel Detection Algorithm Based on Massive MIMO Communication System

Junhui Gao, Mengjiao Zhang, Fan Cao, Jiawei Wang, Feng Ji

School of Information Science and Engineering, Southeast University, Nanjing Jiangsu

Received: Apr. 5th, 2017; accepted: Apr. 21st, 2017; published: Apr. 25th, 2017

ABSTRACT

Channel detection is an indispensable module in massive MIMO communication systems, which often determines the performance of the entire communication system. The main function of channel detection is to deal with the channel matrix obtained by channel estimation to get the signal vector sent by the users. In this paper, we introduce the maximum ratio combining algorithm and the linear minimum mean square error detection algorithm based on QR decomposition, and establish the system model to simulate the uplink data transmission. The simulation results show that the performance of the linear minimum mean square error algorithm based on QR decomposition is superior to the maximum ratio combining algorithm.

Keywords:Massive MIMO, Channel Detection Algorithm, QR Decomposition

1. 引言

2. 系统模型

(2.1)

Table 1. Symbol description

Figure 1. A single-cell multi-user massive MIMO system

3. 大规模MIMO系统中的线性检测算法

3.1. 最大比合并(MRC)检测算法

(3.1)

3.2. 基于QR分解的线性最小均方误差(QR-LMMSE)检测算法

(3.2)

(3.3)

(3.4)

(3.5)

(3.6)

(3.7)

(3.8)

4. 仿真分析

4.1. 仿真参数设置

Table 2. System simulation parameters

Table 3. SCM channel model parameter settings

4.2. 仿真流程

4.3. 仿真结果与分析

;

;

;

Figure 2. Block diagram of uplink data transmission

Figure 3. Numerical results of uplink data transmission with the maximum ratio combining algorithm

Figure4. Numerical results of uplink data transmission with the linear least squares error algorithm

5. 结束语

Research on Channel Detection Algorithm Based on Massive MIMO Communication System[J]. 无线通信, 2017, 07(02): 45-52. http://dx.doi.org/10.12677/HJWC.2017.72007

1. 1. Andrews, J.G., Buzzi, S., Choi, W., et al. (2014) What Will 5G Be? IEEE Journal on Selected Areas in Communications, 32, 1065-1082. https://doi.org/10.1109/JSAC.2014.2328098

2. 2. Marzetta, T.L. (2010) Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas. IEEE Transactions on Wireless Communications, 9, 3590-3600. https://doi.org/10.1109/TWC.2010.092810.091092

3. 3. Larsson, E.G., Edfors, O., Tufvesson, F., et al. (2014) Massive MIMO for Next Generation Wireless Systems. IEEE Communications Magazine, 52, 186-195. https://doi.org/10.1109/MCOM.2014.6736761

4. 4. Verdu, S. (1998) Multiuser Detection. Cambridge University Press, Cambridge.

5. 5. Myllyla, M., Hintikka, J.M., Cavallaro, J.R., et al. (2005) Complexity Analysis of MMSE Detector Architectures for MIMO OFDM Systems. Conference Record of the 39th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 30 October-2 November 2005, 75-81. https://doi.org/10.1109/acssc.2005.1599705

6. 6. Echman, F. and Owall, V. (2005) A Scalable Pipelined Complex Valued Matrix Inversion Architecture. 2005 IEEE International Symposium on Circuits and Systems, 5, 4489-4492.

7. 7. Karkooti, M., Cavallaro, J.R. and Dick, C. (2005) FPGA Implementation of Matrix Inversion Using QRD-RLS Algorithm. Conference Record of the 39th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 30 October-2 November 2005, 1625-1629. https://doi.org/10.1109/acssc.2005.1600043

8. 8. Hassibi, B. (2000) An Efficient Square-Root Algorithm for BLAST. Proceedings of the 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP’00, 2, II737-II740. https://doi.org/10.1109/icassp.2000.859065

9. 9. Bohnke, R., Wubben, D., Kuhn, V., et al. (2003) Reduced Complexity MMSE Detection for BLAST Architectures. Global Telecommunications Conference, GLOBECOM’03, 4, 2258-2262. https://doi.org/10.1109/glocom.2003.1258637

10. 10. Kim, H.S., Zhu, W., Bhatia, J., et al. (2008) A Practical, Hardware Friendly MMSE Detector for MIMO-OFDM-Based Systems. EURASIP Journal on Advances in Signal Processing, 2008, Article ID: 267460. https://doi.org/10.1155/2008/267460

11. 11. (2003) 3GPP: Spatial Channel Model for MIMO Simulations. http://www.3gpp.org/