Damped Jacobi Methods Based on Two Different Matrices for Signal Detection in Massive MIMO Uplink
Keywords:Massive MIMO, iterative Jacobi method, diagonal matrix, stair matrix, damping factor.
For massive multiple-input multiple-output (m-MIMO) uplink, the performances of the linear minimum mean-square error (MMSE) detector are considered near optimal, and they occupy benchmark place for most linear iterative detectors. However, the MMSE algorithm is known by its load computational complexity due to the implication of large-scale matrix inversions, and in other hand, iterative methods are often preferred in signal detection because of its low complexity. In this paper, we propose a New Damped Jacobi (NDJ) detector in order to improve the performance of the classical Jacobi linear algorithm. Starting from the classical Jacobi technique to our new proposal, we go through the development of two variants; one uses a damping factor and the other uses a stair-matrix. However, the NDJ incorporates a damping factor in its construction and basing also on stair matrix instead of diagonal matrix. The performances in terms of convergence and low complexity of each Jacobi variant studied in this paper are analyzed. Finally, some simulation examples are given to illustrate the advantages of the new proposed algorithm.
L. Zhao, H. Zhao, K. Zheng, and W. Xiang, “Massive MIMO in 5G Networks: Selected Applications,” Springer Briefs in Electrical and Computer Engineering, Switzerland, 2018.
J.G. Andrews, S. Buzzi, C. Wan, et al. “What Will 5G Be?,” IEEE J Sel Areas Commun, vol. 32, no. 6, pp. 1065–1082, 2014.
S.P. Kim, J.C. Sanchez, Y.N. Rao, et al. “A Comparison of Optimal MIMO Linear and Nonlinear Models for Brain-Machine Interfaces,” J Neural Eng, vol. 3, no. 2, pp. 145–161, 2006.
M. Mahdavi, O. Edfors, V. Owall, and L. Liu, “A Low Complexity Massive MIMO Detection Scheme Using Angular-Domain Processing,” IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 181–185, Nov 2018.
S. Higuchi, and C.J. Ahn, “Reduced Complexity and Latency for a Massive MIMO System Using a Parallel Detection Algorithm,” ICT Express, vol. 3, no. 3, pp. 119–123, Sept 2017.
T.B. Nguyen, M.T. Le, and V.D. Ngo, “Signal Detection Based on Parallel Group Detection Algorithm for High-Load Massive MIMO Systems,” Wireless Communications and Mobile Computing, pp. 1–12, 2019.
F. Jiang, C. Li, and Z. Gong, “A Low Complexity Soft-Output Data Detection Scheme Based on Jacobi Method for Massive MIMO Uplink Transmission,” IEEE International Conference on Communications (ICC). Paris, France, May 2017.
L. Dai, X. Gao, X. Su, S. Han, and Z. Wang, “Low-Complexity Soft-Output Signal Detection Based on Gauss-Seidel Method for Uplink Multiuser Large-Scale MIMO Systems,” IEEE Trans. Veh. Technol., vol. 64, no.10, pp. 4839–4845, 2015.
X. Gao, L. Dai, Y. Hu, Z. Wang, and Z. Wang, “Matrix Inversion-Less Signal Detection Using SOR Method for Uplink Large-Scale MIMO Systems,” IEEE Global Commun (GLOBECOM), pp. 3291-3295, Austin, TX, Dec 2014.
F. Jin, Q. Liu, H. Liu, and P. Wu, “A Low Complexity Signal Detection Scheme Based on Improved Newton Iteration for Massive MIMO Systems,” IEEE Communications Letters, vol. 23, no. 4, pp. 748-751, 2019.
X. Gao, L. Dai, C. Yuen, and Y. Zhang, “Low-Complexity MMSE Signal Detection Based on Richardson Method for Large-Scale MIMO Systems,” IEEE 80th Vehicular Technology Conference, pp. 1-5, Sept 2014.
M.Wu, B.Yin, A. Vosoughi, C. Studer, J.R. Cavallaro, and C. Dick, “Approximate Matrix Inversion for High Throughput Data Detection in The Large-Scale MIMO Uplink,” IEEE ISCAS Conf, pp. 2155-2158, Beijing, China, May 2013.
J. Minango, and A.C. Flores, “Low-complexity MMSE Detector Based on Refinement Jacobi Method for Massive MIMO Uplink,” Physical Communication, vol. 26, pp. 128–133, 2018.
X. Qin, Z. Yan, and G. He, “A Near-Optimal Detection Scheme Based on Joint Steepest Descent and Jacobi Method for Uplink Massive MIMO Systems,” IEEE Commun. Lett., vol. 20, no. 2, pp. 276–279, 2016.
W. Song, X. Chen, L. Wang, and X. Lu, “Joint Conjugate Gradient and Jacobi Iteration Based on Low Complexity Precoding for Massive MIMO Systems”, IEEE/CIC International Conference on Communications in China (ICCC), pp. 1-5, Chengdu, 2016.
L. Yinman, “Decision-aided Jacobi Iteration for Signal Detection in Massive MIMO Systems,” Electronics Letters, vol. 53, no. 23, pp. 1552–1554, 2017.
H. Lou, “Stair Matrices and Their Generalizations with Applications to Iterative Methods I: A Generalization of the Successive Over-relaxation Method,” SIAM Journal on Numerical Analysis, vol. 37, no. 1, pp. 1–17, 2000.
F. Jiang, C. Li, Z. Gong, and R. Su, “Stair Matrix and its Applications to Massive MIMO Uplink Data Detection,” IEEE Trans. Commun., vol. 66, no. 6, pp. 2437–2455, 2018.