基于人工鱼群的中继卫星多用户检测方法

doi:10.16180/j.cnki.issn1007-7820.2019.10.001

摘要/Abstract

摘要：

随着航天技术的发展,未来的中继卫星系统需要为多个用户航天器提供码分多址通信服务。因此需要采用多用户检测技术来抑制多个用户航天器信号之间的多址干扰。文中将人工鱼群优化算法引入到中继卫星系统多用户检测中,通过模拟人工鱼群觅食过程中的觅食行为、聚集行为以及尾随行为,利用人工鱼群的迭代优化,实现多址干扰的最小化。为加快人工鱼群算法的收敛速度,文中将解相关多用户检测的结果作为人工鱼群算法的迭代初值。结果表明,基于人工鱼群算法的多用户检测方法误码率在信噪比为10 dB时可以达到10 ^-6数量级,在误码率、远近效应以及用户容量等方面的性能优于传统的多用户检测方法。

关键词: 中继卫星, 多址通信, 干扰抑制, 人工鱼群算法, 远近效应, 误码率

Abstract:

With the development of space technology, future relay satellite systems need to provide code division multiple access communication services for multiple user spacecraft. Therefore, multi-user detection techniques were employed to suppress the multiple access interference. In this paper, the artificial fish swarm algorithm was introduced into the multi-user detection of the relay satellite system. By simulating the preying behavior, swarming behavior and following behavior of artificial fishes, the multiple access interference was minimized iteratively. In order to speed up the convergence speed of the artificial fish swarm algorithm, the results of decorrelating multiuser detection were employed as initial values of the artificial fishes. The results showed that the bit error rate of the artificial fish swarm algorithm based multiuser detection method could approach 10 ^-6 at the SNR of 10 dB, and its performance was better than traditional multi-user detection method in terms of bit error rate, near-far effect and user capacity.

Key words: data relay satellite, multiple access communication, interference suppression, artificial fish swarm algorithm, near-far effect, bit error rate

中图分类号:

TN927+.23

陈晓光,吴芝路,蒋旭,张晓军. 基于人工鱼群的中继卫星多用户检测方法[J]. 电子科技, 2019, 32(10): 1-6.

CHEN Xiaoguang,WU Zhilu,JIANG Xu,ZHANG Xiaojun. Artificial Fish Swarm Algorithm Based on Multiuser Detection for Data Relay Satellite System[J]. Electronic Science and Technology, 2019, 32(10): 1-6.

图/表 4

参考文献 17

[1]	翟政安 . 下一代数据中继卫星系统发展思考[J]. 飞行器测控学报, 2016,35(2):89-97.
	Zhai Zhengan . Development of next generation data relay satellite systems[J]. Journal of Spacecraft TT&C Technology, 2016,35(2):89-97.
[2]	孙文超 . 导航接收机的空时抗干扰研究及实现[J]. 电子科技, 2016,29(6):138-142.
	Sun Wenchao . Research and implementation of anti jamming system for navigation receiver[J]. Electronic Science and Technology, 2016,29(6):138-142.
[3]	赵月露, 纪磊 . 导航卫星接收机窄带干扰抑制算法研究[J]. 电子科技, 2016,29(3):53-57.
	Zhao Yuelu, Ji Lei . Research on narrowband interference suppression algorithm for satellite navigation receiver[J]. Electronic Science and Technology, 2016,29(3):53-57.
[4]	赵宏杰, 李常青, 钟育民 , 等. 基于多用户检测的扩频测控多址干扰抑制方法[J]. 遥测遥控, 2017,38(6):30-39.
	Zhao Hongjie, Li Changqing, Zhong Yumin , et al. Multiuser detection techniques for multiple access interference suppression in spread-spectrum TT&C systems[J]. Journal of Telemetry,Tracking and Command, 2017,38(6):30-39.
[5]	杨毅 . 扩频通信系统多用户检测技术[J]. 电子技术与软件工程, 2017(15):38-39.
	Yang Yi . Multiuser detection techniques in spectrum spreading communication systems[J]. Electronic Technology and Software Engineering, 2017(15):38-39.
[6]	陆家明, 汪立新, 祁浩 . 基于最优格拉斯曼序列的多用户检测[J]. 通信技术, 2015,48(8):945-948.
	Lu Jiaming, Wang Lixin, Qi Hao . Multi-user detection based on optimal grassmannian sequence[J]. Communications Technology, 2015,48(8):945-948.
[7]	陈章宝, 崔杨培, 吴杨 . 盲多用户检测技术研究[J]. 广东通信技术, 2015(6):39-42.
	Chen Baozhang, Cui Yangpei, Wu Yang . Research on blind multiuser detection techniques[J]. Guangdong Communication Technology, 2015(6):39-42.
[8]	徐伟, 许庆帅, 国强 , 等. 一种译码纠错反馈的并行干扰消除算法[J]. 无线电工程, 2018,48(8):666-673.
	Xu Wei, Xu Qingshuai, Guo Qiang , et al. A parallel interference cancellation algorithm for decoding error-correcting feedbac[J]. Radio Engineering, 2018,48(8):666-673.
[9]	高洪元, 梁炎松, 刘丹丹 . 基于新量子蜂群算法的鲁棒多用户检测[J]. 计算机工程, 2016,42(9):48-57. doi: 10.3969/j.issn.1000-3428.2016.09.009
	Gao Hongyuan, Liang Yansong, Liu Dandan . Robust multiuser detection based on novel quantum bee colony algorithm[J]. Computer Engineering, 2016,42(9):48-57. doi: 10.3969/j.issn.1000-3428.2016.09.009
[10]	吕先望, 孙泽楠 . 蚁群算法在多用户检测技术中的应用[J]. 无线电工程, 2015,45(10):67-70.
	Lv Xianwang, Sun Zenan . Application of ant colony algorithm in multi-user detection technology[J]. Radio Engineering, 2015,45(10):67-70.
[11]	许晶晶, 杨维, 张琳园 , 等. MC-CDMA粒子群多用户检测在井下带状空间的性能分析[J]. 中国矿业大学学报, 2016,45(3):630-638.
	Xu Jingjing, Yang Wei, Zhang Linyuan , et al. Performance analysis of particle swarm optimization algorithm in multiuser detection for MC-CDMA system in mine tunnel with limited band space[J]. Journal of China University of Mining and Technology, 2016,45(3):630-638.
[12]	梁娜, 晁晖, 张超 . 小波神经网络在MC-CDMA多用户检测技术中应用研究[J]. 中国新通信, 2015(1):72-73.
	Liang Na, Chao Hui, Zhang Chao . Research on applications of wavelet neural network in MC-CDMA multiuser detection techniques[J]. China New Telecommunications, 2015(1):72-73.
[13]	Zubair M . Multiuser detection using soft particle swarm optimization along with radial basis function[J]. Turkish Journal of Electrical Engineering & Computer Sciences, 2015,22(6):1476-1483.
[14]	Zahedi A, Rajamand S, Jafari S , et al. A novel multiuser detector based on restricted search space and depth- first tree search method in DS/CDMA communication systems[J]. Wireless Personal Communications, 2015,82(3):1531-1545.
[15]	Larbi N, Debbat F, Stambouli A B . Multiuser detection for DS-CDMA systems using honeybees mating optimization algorithm[J]. Arabian Journal for Science & Engineering, 2014,39(6):4911-4921.
[16]	Chen Xiaoguang, Jiang Xu, Wu Zhilu , et al. Differential characteristics based iterative multiuser detection for wireless sensor networks[J]. Sensors, 2017,17(2):1-15.
[17]	李晓磊, 钱积新 . 基于分解协调的人工鱼群优化算法研究[J]. 电路与系统学报, 2003,8(1):1-6.
	Li Xiaolei, Qian Jixin . Studies on artificial fish swarm optimization algorithm based on coordination techniques[J]. Journal of Circuits and Systems, 2003,8(1):1-6.