通信学报 ›› 2017, Vol. 38 ›› Issue (3): 165-173.doi: 10.11959/j.issn.1000-436x.2017039

• 学术通信 • 上一篇    下一篇

基于能量检测的异步感知算法

余盼,李斌,赵成林   

  1. 北京邮电大学信息与通信工程学院,北京 100876
  • 修回日期:2016-12-11 出版日期:2017-03-01 发布日期:2017-04-13
  • 作者简介:余盼(1992-),女,湖北武汉人,北京邮电大学硕士生,主要研究方向为无线通信、认知无线电、信号处理等。|李斌(1985-),男,甘肃天水人,博士,北京邮电大学副教授,主要研究方向为无线通信系统、统计信号处理、认知无线电和毫米波通信技术等。|赵成林(1964-),男,河北石家庄人,博士,北京邮电大学教授,主要研究方向为无线通信、数字信号处理及其在通信中的应用等。
  • 基金资助:
    国家自然科学基金资助项目(61471061);国家自然科学基金资助项目(61379016)

Asynchronous perception algorithm based on energy detection

Pan YU,Bin LI,Cheng-lin ZHAO   

  1. School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China
  • Revised:2016-12-11 Online:2017-03-01 Published:2017-04-13

摘要:

在未来异构无线网络中,授权用户(PU)与认知用户(SU)间无法进行协作定时,导致授权用户发射机和认知用户接收机之间存在感知时间差。针对这一异步感知场景,基于贝叶斯统计估计理论提出一种全新的异步感知算法。首先,提出一种统一的动态状态空间模型,来描述可观测能量与动态授权用户状态以及未知时间差之间的关系;然后,利用随机有限集并基于最大后验概率准则设计一种迭代式估计方案;最后,通过粒子滤波以数值逼近方式得到估计结果。仿真结果表明,通过准确获取出感知时间差,所提出的异步感知算法可有效消除接收信号的信息不确定性,从而显著提高频谱感知性能。

关键词: 频谱感知, 异步感知, 动态状态空间模型, 最大后验概率, 联合估计

Abstract:

In the future heterogeneous wireless networks,since primary user (PU) and cognitive secondary user (SU) are not coordinated to be synchronous,it will result in sense timing difference between PU’s transmitter and SU’s receiver.For this asynchronous sense case,a new asynchronous sensing algorithm based on Bayesian estimation theory was proposed.A unified dynamic state space model was first proposed to describe the observable energy relationship with dynamic PU state and unknown timing difference.Then,an iterative estimation scheme was designed using stochastic finite set and the rules of maximum posterior probability.Finally,approximated estimation results were obtained by using a particle filter.The simulation results show that the proposed asynchronous scheme significantly eliminates the uncertainty of the received signal information and thus improves the spectrum sensing performance by obtaining the time difference accurately.

Key words: spectrum sensing, asynchronous perception, dynamic state-space model, maximum posterior probability,joint estimation

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