Sphere Decoding Algorithm Based on Wolf Pack Algorithm

LI Rui; BAI Peng; PENG Wei-dong; LIN Zhi-guo; LIN Si-ming

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Sphere Decoding Algorithm Based on Wolf Pack Algorithm

更新时间：2026-09-04

- Sphere Decoding Algorithm Based on Wolf Pack Algorithm
- Vol. 34, Issue 1, Pages: 76-80(2017)
- 作者机构：
  
  1. 空军工程大学机构装备管理与安全工程学院,陕西,西安,710051
  2. 空军工程大学装备发展与运用研究中心,陕西,西安,710051
- 作者简介：
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- Published：2017
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李瑞, 柏鹏, 彭卫东, 林志国, 林思铭. 基于狼群算法的球形译码算法研究[J]. 微电子学与计算机, 2017, 34(1): 76-80.

LI Rui, BAI Peng, PENG Wei-dong, et al. Sphere Decoding Algorithm Based on Wolf Pack Algorithm[J]. 2017, 34(1): 76-80.
李瑞, 柏鹏, 彭卫东, 林志国, 林思铭. 基于狼群算法的球形译码算法研究[J]. 微电子学与计算机, 2017, 34(1): 76-80. DOI：

LI Rui, BAI Peng, PENG Wei-dong, et al. Sphere Decoding Algorithm Based on Wolf Pack Algorithm[J]. 2017, 34(1): 76-80. DOI：

摘要

在信号空间分集(SSD)系统中

使用球形译码算法可以有效降低接收机检测复杂度.但传统的球形译码算法在低信噪比情况下计算复杂度较高

为降低球形译码算法计算复杂度

分析了初始搜索半径设置对球形译码过程的影响

并利用狼群算法的寻优能力来获得最佳的初始搜索半径

在保证译码性能的前提下有效地降低了计算复杂度.仿真结果表明

基于狼群算法的球形译码算法可以获得与传统SD算法相同的性能

同时在低信噪比情况下有效降低了球形译码算法的计算复杂度.

Abstract

In the signal space diversity(SSD) system

the sphere decoding(SD) algorithm can reduces the complexity of the receiver

but it is high that computation complexity of traditional sphere decoding algorithm at low signal to noise ratio. In order to reduce the computation complexity

the influence of the initial search radius on the sphere decoding process is analyzed

and use optimization ability of wolf pack algorithm to obtain the best initial search radius. It can ensure decoding performance and reduce the computation complexity effectively. The simulation results show that the performance of sphere decoding algorithm based on wolf pack algorithm can be the same as that of traditional sphere decoding algorithm

and can reduce the computation complexity at low signal to noise ratio effectively.

关键词

Keywords

references

Boutros J, Viterbi E. Signal space diversity: a power and band width efficient diversity technique for the Rayleigh fading channel[J]. IEEE Transactions on Information Theory, 1998, 44(4): 1453-1467. DOI: 1453

毕晓君, 金风. 基于免疫算法的球形译码算法研究[J]. 哈尔滨工程大学学报, 2009, 30(11): 1301-1305. DOI: 1301

Wu H S, Zhang F M. Wolf pack algorithm for unconstrained global optimization[J]. Mathematical Problems in Engineering, 2014, 46(5): 17. DOI: 17

Qianlei L, Luxi Y. A novel method for initial radius selection of sphere decoding[C]//VTC 2004. Los Angeles: IEEE, 2004.

李金凤. MIMO通信系统中信号检测技术研究[D]. 哈尔滨: 哈尔滨工程大学, 2009.

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Hassibi B, Vikalo H. On the expected complexity of integer least-squares problems[C]//IEEE International Conference on Acoustics, Speech, and Signal Processing. Taipei: IEEE, 2002.

程波, 刘威, 杨宗凯. 一种新的球形解码初始半径确定方法[J]. 小型微型计算机系统, 2008, 29(7): 1357-1361. DOI: 1357

吴虎胜, 张凤鸣, 吴庐山. 一种新的群体智能算法--狼群算法[J]. 系统工程与电子技术, 2013, 35(11): 2430-2438. DOI: 2430

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