基于K均值聚类的SPPM分步分类检测算法

doi:10.11959/j.issn.1000-436x.2022010

通信学报 ›› 2022, Vol. 43 ›› Issue (1): 161-171.doi: 10.11959/j.issn.1000-436x.2022010

基于K均值聚类的SPPM分步分类检测算法

王惠琴, 侯文斌, 彭清斌, 曹明华, 黄瑞, 刘玲

兰州理工大学计算机与通信学院，甘肃兰州 730050

修回日期:2021-12-26 出版日期:2022-01-25 发布日期:2022-01-01
作者简介:王惠琴（1971- ），女，甘肃渭源人，博士，兰州理工大学教授、博士生导师，主要研究方向为无线光通信理论与技术
侯文斌（1997- ），男，河南长垣人，兰州理工大学硕士生，主要研究方向为无线光通信理论与系统、机器学习算法
彭清斌（1983- ），男，甘肃兰州人，兰州理工大学博士生、讲师，主要研究方向为无线光通信技术
曹明华（1979- ），男，甘肃平凉人，博士，兰州理工大学教授、博士生导师，主要研究方向为无线光通信理论与技术、光无线融合技术
黄瑞（1973- ），男，宁夏银川人，兰州理工大学高级工程师，主要研究方向为无线光通信理论与技术
刘玲（1997- ），女，甘肃天水人，兰州理工大学硕士生，主要研究方向为光通信理论与技术、阶梯码
基金资助:
国家自然科学基金资助项目(61861026);国家自然科学基金资助项目(61875080);甘肃省自然科学基金资助项目(20JR5RA472)

Step-by-step classification detection algorithm of SPPM based on K-means clustering

Huiqin WANG, Wenbin HOU, Qingbin PENG, Minghua CAO, Rui HUANG, Ling LIU

School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China

Revised:2021-12-26 Online:2022-01-25 Published:2022-01-01
Supported by:
The National Natural Science Foundation of China(61861026);The National Natural Science Foundation of China(61875080);The Natural Science Founda-tion of Gansu Province(20JR5RA472)

摘要/Abstract

摘要：

针对空间脉冲位置调制系统中采用最大似然检测算法时存在计算复杂度高的问题，依据空间脉冲位置调制信号矩阵的特点，提出了一种基于K均值聚类的分步分类检测算法。首先，采用基于信号向量检测算法完成训练样本中光源索引号的检测，利用 K 均值聚类算法对训练样本进行离线训练得到其质心与调制符号间的映射关系。然后，以该映射关系为准则完成在线调制符号的实时检测，以穷搜索方式检测出光源索引号。最后，采用蒙特卡罗方法研究了聚类数目、初始化次数等关键参数对系统误比特率性能的影响。仿真结果表明，所提算法能够取得近似最大似然算法的误比特率性能，同时大幅度降低了信号检测的计算复杂度。与线性译码算法相比，所提算法还可适用于探测器数目小于光源数目的通信场景。

关键词: 无线光通信, 空间脉冲位置调制, K均值聚类, 分步分类检测

Abstract:

In view of the high computational complexity in spatial pulse position modulation systems when using maximum likelihood detection algorithm, a step-by-step classification detection algorithm based on K-means clustering was proposed according to the characteristics of signal matrix with spatial pulse position modulation.The signal vector detection algorithm was utilized to detect the index of light source in the training samples.The on K-means clustering algorithm was utilized to acquire the mapping rule between centroid of samples and modulated symbol by offline training.Subsequently, online detection of modulated symbols was achieved based on the mapping rule, and then the index of light sources was detected by exhaustive search.In addition, Monte Carlo method was used to investigate the effects of key parameters such as the number of clusters and initialization times on the system bit error rate (BER) performance.Simulation results demonstrate that the proposed algorithm can achieve an approximate BER performance as the maximum likelihood algorithm on the basis of greatly reducing the computational complexity.Compared with the linear decoding algorithms, the proposed algorithm is also applicable to scenarios where the number of detectors is less than the number of light sources.

Key words: wireless optical communication, spatial pulse position modulation, K-means clustering, step-by-step classifi-cation detection

中图分类号:

TN929.12

王惠琴, 侯文斌, 彭清斌, 曹明华, 黄瑞, 刘玲. 基于K均值聚类的SPPM分步分类检测算法[J]. 通信学报, 2022, 43(1): 161-171.

Huiqin WANG, Wenbin HOU, Qingbin PENG, Minghua CAO, Rui HUANG, Ling LIU. Step-by-step classification detection algorithm of SPPM based on K-means clustering[J]. Journal on Communications, 2022, 43(1): 161-171.

图/表 11

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表1

各算法复杂度"

检测算法	计算复杂度
ML	$N_{t} L (2 N_{t} N_{r} L + 2 N_{r} L - 1)$
MMSE	$N_{t} (\frac{3}{2} N_{t}^{2} + 2 N_{t} L + 2 N_{t} N_{r} - \frac{3}{2} N_{t} - L + 1)$
ZF	$N_{t} (\frac{3}{2} N_{r} N_{t} - \frac{5}{4} N_{r} - \frac{1}{4} N_{t} + 2 N_{t} L - L)$
CS	$N_{t} (2 N_{r} - 1) (L + 1)$
本文所提算法	$N_{t} (2 N_{t} N_{r} L + 2 N_{r} L - 1) + L (3 N_{r} L - 1)$

表1

图10

参考文献 25

[1]	RENZO M D , HAAS H , GHRAYEB A ,et al. Spatial modulation for generalized MIMO:challenges,opportunities,and implementation[J]. Proceedings of the IEEE, 2014,102(1): 56-103.
[2]	JAISWAL A , BHATNAGAR M R , JAIN V K . Performance of optical space shift keying over Gamma-Gamma fading with pointing error[J]. IEEE Photonics Journal, 2017,9(2): 1-16.
[3]	POPOOLA W O , POVES E , HAAS H . Spatial pulse position modulation for optical communications[J]. Journal of Lightwave Technology, 2012,30(18): 2948-2954.
[4]	OLANREWAJU H G , THOMPSON J , POPOOLA W O . On spatial pulse position modulation for optical wireless communications[C]// Proceedings of 2016 IEEE Photonics Society Summer Topical Meeting Series. Piscataway:IEEE Press, 2016: 44-45.
[5]	?ZBILGIN T , KOCA M . Optical spatial modulation over atmospheric turbulence channels[J]. Journal of Lightwave Technology, 2015,33(11): 2313-2323.
[6]	JAISWAL A , BHATNAGAR M R , SONI P ,et al. Differential optical spatial modulation over atmospheric turbulence[J]. IEEE Journal of Selected Topics in Signal Processing, 2019,13(6): 1417-1432.
[7]	JEGANATHAN J , GHRAYEB A , SZCZECINSKI L . Spatial modulation:optimal detection and performance analysis[J]. IEEE Communications Letters, 2008,12(8): 545-547.
[8]	王惠琴, 宋梨花, 曹明华 ,等. 湍流信道下光空间调制信号的压缩感知检测[J]. 光学精密工程, 2018,26(11): 2669-2674.
	WANG H Q , SONG L H , CAO M H ,et al. Compressed sensing detection of optical spatial modulation signal in turbulent channel[J]. Optics and Precision Engineering, 2018,26(11): 2669-2674.
[9]	LIANG H W , CHANG R Y , CHUNG W H ,et al. A reduced-complexity blind detector for MIMO system using K-means clustering algorithm[C]// Proceedings of 2013 IEEE 77th Vehicular Technology Conference. Piscataway:IEEE Press, 2013: 1-5.
[10]	LIANG H W , CHUNG W H , KUO S Y . Coding-aided K-means clustering blind transceiver for space shift keying MIMO systems[J]. IEEE Transactions on Wireless Communications, 2016,15(1): 103-115.
[11]	YOU L F , YANG P , XIAO Y ,et al. Blind detection for spatial modulation systems based on clustering[J]. IEEE Communications Letters, 2017,21(11): 2392-2395.
[12]	王刚 . 空移键控系统中基于 K-Means 聚类算法的盲检测研究[D]. 合肥:安徽大学, 2018.
	WANG G . Research on blind estimation based on K-means clustering algorithms in space shift keying system[D]. Hefei:Anhui University, 2018.
[13]	ZHANG L J , JIN M L . A constrained clustering-based blind detector for spatial modulation[J]. IEEE Communications Letters, 2019,23(7): 1170-1173.
[14]	YUAN J , ZHANG Q Q , LIANG Y C ,et al. A clustering detector for spatial modulation system[C]// Proceedings of 2018 IEEE International Conference on Communication Systems. Piscataway:IEEE Press, 2018: 50-55.
[15]	ZHANG L J , JIN M L , YOO S J . A clustering detector with graph theory for blind detection of spatial modulation systems[J]. Wireless Networks, 2021,27(2): 1193-1201.
[16]	ZHANG L J , HE Y C , JIN M L . Symmetry-aided clustering blind detection in spatial modulation systems[J]. IEEE Transactions on Vehicular Technology, 2021,70(4): 3354-3370.
[17]	GARCíA-ZAMBRANA A , CASTILLO-VáZQUEZ B , CASTILLO-VáZQUEZ C , . Asymptotic error-rate analysis of FSO links using transmit laser selection over gamma-gamma atmospheric turbulence channels with pointing errors[J]. Optics Express, 2012,20(3): 2096-2109.
[18]	PHAM H T T , DANG N T . Performance improvement of spatial modulation-assisted FSO systems over Gamma-Gamma fading channels with geometric spreading[J]. Photonic Network Communications, 2017,34(2): 213-220.
[19]	HAN P , WANG W Q , SHI Q Y ,et al. A combined online-learning model with K-means clustering and GRU neural networks for trajectory prediction[J]. Ad Hoc Networks, 2021,117:102476.
[20]	ZHANG J F , CHEN W , GAO M Y ,et al. K-means-clustering-based fiber nonlinearity equalization techniques for 64-QAM coherent optical communication system[J]. Optics Express, 2017,25(22): 27570-27580.
[21]	BENMAHDI M B , LEHSAINI M . Greedy forwarding routing schemes using an improved K-means approach for wireless sensor networks[J]. Wireless Personal Communications, 2021,119(2): 1619-1642.
[22]	WANG J T , JIA S Y , SONG J . Signal vector based detection scheme for spatial modulation[J]. IEEE Communications Letters, 2012,16(1): 19-21.
[23]	ELSAYED E E , YOUSIF B B . Performance enhancement of hybrid diversity for M-ary modified pulse-position modulation and spatial modulation of MIMO-FSO systems under the atmospheric turbulence effects with geometric spreading[J]. Optical and Quantum Electronics, 2020,52(12): 1-18.
[24]	ADAMCHIK V S , MARICHEV O I . The algorithm for calculating integrals of hypergeometric type functions and its realization in REDUCE system[C]// Proceedings of the International Symposium on Symbolic and Algebraic Computation.[S.l.:s.n.], 1990: 212-224.
[25]	SUN Y , WANG J T , HE L Z . Iterative zero forcing detection scheme for generalised spatial modulation[C]// Proceedings of 2015 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting. Piscataway:IEEE Press, 2015: 1-4.

基于K均值聚类的SPPM分步分类检测算法

Step-by-step classification detection algorithm of SPPM based on K-means clustering

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