An Improved Distributed Multi-User Cooperative Spectrum Sensing Method Based on DCS

Jianwu Zhang; Xiaoyan Chen; Xiaorong Xu

doi:10.3969／j.issn.1000-0801.2013.11.008

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An Improved Distributed Multi-User Cooperative Spectrum Sensing Method Based on DCS

research and development | 更新时间：2024-06-05

- An Improved Distributed Multi-User Cooperative Spectrum Sensing Method Based on DCS
- Telecommunications Science Vol. 29, Issue 11, Pages: 45-51(2013)
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- DOI：10.3969／j.issn.1000-0801.2013.11.008
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- Published Online：2013-11，
  
  Published：20 November 2013
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Jianwu Zhang, Xiaoyan Chen, Xiaorong Xu. An Improved Distributed Multi-User Cooperative Spectrum Sensing Method Based on DCS[J]. Telecommunications science, 2013, 29(11): 45-51.
DOI：

Jianwu Zhang, Xiaoyan Chen, Xiaorong Xu. An Improved Distributed Multi-User Cooperative Spectrum Sensing Method Based on DCS[J]. Telecommunications science, 2013, 29(11): 45-51. DOI： 10.3969／j.issn.1000-0801.2013.11.008.

摘要

分布式压缩感知（DCS）理论扩展了压缩感知理论的应用，将单信号的压缩采样扩展到信号群的压缩采样。协作频谱感知技术利用空间的宏集合弥补了单用户在认知无线电宽带频谱感知过程中可能出现检测错误的问题，但在复杂的信号重构过程中增加了计算量。针对这种情况，提出了一种改进的基于DCS的分布式多用户协作频谱感知方法。该改进方法的重构过程是在原OMP算法的基础上，通过利用上一时刻频谱感知所得到的频谱占用情况减少重构算法的计算量。仿真结果表明，在频谱占用情况变化缓慢的情况下，所提的改进方法不仅具有与原算法相同的重构效果，而且在认知用户数量较多的情况下，重构复杂度明显减小。

Abstract

Distributed compressed sensing theory extends the application of compressed sensing theory

which brings single signal compression sampling to signal group compression sampling. Cooperative spectrum sensing technology uses space set macros to compensate detection error problems during the process of single-user wideband spectrum sensing. However

it increases computational complexity in the process of signal reconstruction. Aiming to this problem

an improved distributed multi-user cooperative spectrum sensing method based on DCS was proposed. On the basis of original OMP algorithm

the improved method reduced reconstruction algorithm's computational complexity through the utilization of previous spectrum occupancy situation. Simulation results indicate that

the proposed method achieves the same effect with the original algorithm under the circumstances of slow spectrum occupancy changes. Meanwhile

in the case of more cognitive users

this method reduces the reconstruction complexity significantly.

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Keywords

references

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