基于Newton迭代算法的低复杂度信号检测算法

doi:10.11959/j.issn.1000-436x.2022035

Abstract

Abstract:

In order to solve the problems of high computational complexity and slow convergence rate of ultra-massive MIMO detection in terahertz communication system, the low complexity signal detection algorithm based on Newton iterative algorithm was proposed.By improving the initial matrix and adding step factor in Newton iteration algorithm, the complexity of the algorithm was reduced, and the convergence speed was increased.By adding adjusting factors, the stability and reliability of the algorithm were guaranteed, and the applicability of the algorithm was also increased.Simulation results show that the proposed algorithm have lower computational complexity and faster convergence speed compared with traditional schemes.When the number of iterations is three, the detection performance is close to MMSE algorithm.

Key words: terahertz communication, ultra-massive MIMO, signal detection, step factor

CLC Number:

TN929.5

Gang LIU, Zengjin LOU, Qinhua LIN, Yi GUO. Low complexity signal detection algorithm based on Newton iterative algorithm[J]. Journal on Communications, 2022, 43(2): 109-117.

Figures/Tables 10

References 19

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算法	初始化复杂度
算法1	NK+K
算法2	NK+ 3K
Newton迭代算法	NK ²+NK+K

迭代次数	算法1	算法2	Newton迭代算法
1	K ²(N+2)+K(N+1)	3NK	NK ²+NK
2	K ²(3N+4)+K(N+2)	7NK	3NK²+NK
3	K ²(7N+6)+K(7N+3)	15 NK	7NK²+7NK
4	K²(15N+8)+K(15N+4)	31NK	15 NK ²+15 NK

迭代次数	算法1	算法2	Newton迭代算法	基于Neumann级数展开的算法	文献[14]算法
1	(N+2)K ²+(2N+2)K	4NK+3K	2NK²+2NK+K	4NK	NK
2	(3N+4)K ²+(2N+3)K	8NK+3K	4NK²+2NK+K	NK ²+NK	2NK
3	(7N+6)K ²+4(2N+1)K	16 NK+3 K	8NK²+8NK+K	²K ³+NK +NK	3NK
4	(15N+8)K ²+(16N+5)K	32 NK+3 K	16 NK ²+16 NK+K	²2K³+NK +NK	4NK

Low complexity signal detection algorithm based on Newton iterative algorithm

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