基于空间交替广义最大似然的低复杂度列表检测

doi:10.11959/j.issn.1000-436x.2016086

摘要/Abstract

摘要：

针对V-BLAST系统，提出了一种低复杂度的空间交替广义最大似然（SAGL）列表检测算法。该算法的子检测器由简化最大似然（SML）检测器和连续干扰抵消（SIC）检测器组成。传统 SIC 算法每次只能对单一符号进行检测，而所提算法则利用相邻符号进行联合滑动检测，可以获得更高的分集增益。此外，所提SAGL算法对检测结果进行迭代修正来进一步提升检测性能。分析与仿真结果表明，与传统列表检测算法相比，所提SAGL列表检测算法以少许复杂度的增加为代价显著提升了检测性能。

关键词: MIMO, 列表检测, SAGL算法, 连续干扰抵消

Abstract:

A space-alternating generalized maximum-likelihood (SAGL) list detection algorithm with lower-complexity for V-BLAST systems was proposed. The sub-detector involved in the proposed list detection algor hm consisted of sim-plified maximum-likelihood (SML) detectors and successive interference cancel ation (SIC) detectors. The proposed al-gorithm could utilize adjacent symbols to realize joint-sliding detection to achieve higher diversity gain, wh le the tradi-tional SIC algorithm was only able to detect a single symbol each time. Moreover, the proposed SAGL algorithm could further iteratively improve the detection results. Ana is and simulation results present the corresponding enhanced per-formance at the cost of slightly increased complexity, compared with the traditional list detection algorithm.

Key words: MIMO, list detection, SAGL algorithm, successive interference cancellation

景常乐,王欣,魏急波,陈彬,吴世奇. 基于空间交替广义最大似然的低复杂度列表检测[J]. 通信学报, 2016, 37(4): 192-198.

Chang-le JING,Xin WANG,Ji-bo WEI,Bin CHEN,Shi-qi WU. Space alternating generalized maximum-likelihood based low-complexity list detection algorithm[J]. Journal on Communications, 2016, 37(4): 192-198.

图/表 6

图1

图2

图3

图4

表1

不同检测算法的复杂度比较"

检测算法	步骤	乘法数量	除法数量	平方根数量
QRM-MLD	QR分解	$8 N_{r} N_{t}^{2}$	$4 N_{r}^{2}$	2N_t
	$\tilde{y} = Q^{H} y$	4N_rN_t	0	0
	路径扩展	$2 M (\| Ω \| N_{t}^{2} + 3 \| Ω \| N_{t} - 4 \| Ω \| + 2)$	0	0
基于列表的SIC检测	信道矩阵H 排序	$4 N_{r} N_{t}^{2} + 2 N_{r} N_{t}$	0	0
	QR分解	$8 N_{r} N_{t}^{2}$	$4 N_{r}^{2}$	2N_t
	$\tilde{y} = Q^{H} y$	4N_rN_t	0	0
	SIC检测器	$2 (N_{t}^{2} - N_{t})$	2(N_t?1)	0
	ML检测	$q (2 N_{t}^{2} + 3 N_{t})$	0	0
基于SAGL的列表检测	信道矩阵H 排序	$4 N_{r} N_{t}^{2} + 2 N_{r} N_{t}$	0	0
	QR分解	$8 N_{r} N_{t}^{2}$	$4 N_{r}^{2}$	2N_t
	$\tilde{y} = Q^{H} y$	4N_rN_t	0	0
	改进的SML-SIC	$2 (N_{t}^{2} + 6 m N_{t} - 6 m - N_{t})$	2m(N_t?1)	0
	SAGE算法	k(4N_rN_t+8N_r?4N_r)	k	0
	SAGL算法	k(4 N _r N _t+16 mN _r?8 N _r)	km	0
	ML检测	$q (2 N_{t}^{2} + 3 N_{t})$	0	0

表1

图5

参考文献 12

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