电子学报 ›› 2016, Vol. 44 ›› Issue (8): 1994-2003.DOI: 10.3969/j.issn.0372-2112.2016.08.032

• 学术论文 • 上一篇    下一篇

基于信号集合势和连续性的认知无线电宽带频谱感知

申滨, 喻俊, 黄琼, 陈前斌   

  1. 重庆邮电大学移动通信技术重点实验室, 重庆 400065
  • 收稿日期:2014-11-20 修回日期:2015-08-26 出版日期:2016-08-25 发布日期:2016-08-25
  • 作者简介:申滨 男,1978年生于贵州兴义,博士,重庆邮电大学教授.研究方向为认知无线电、IR-UWB等.E-mail:shenbin@cqupt.edu.cn;喻俊 男,1987年生于湖北麻城,重庆邮电大学硕士生.研究方向为认知无线电频谱感知.E-mail:yu_jun1988@qq.com
  • 基金资助:
    国家自然科学基金(No.61201205,No.61379159);国家863高技术研究发展计划(No.2014AA01A701)重庆市自然科学基金(No.CSTC2012JJA40043)

Signal Set Cardinality and Contiguity Based Wideband Spectrum Sensing for Cognitive Radio

SHEN Bin, YU Jun, HUANG Qiong, CHEN Qian-bin   

  1. Key Laboratory of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2014-11-20 Revised:2015-08-26 Online:2016-08-25 Published:2016-08-25

摘要: 针对传统感知算法依赖主用户信号与噪声先验信息,以及易受噪声功率估计不确定性影响的缺点,提出了一种基于信号集合势和连续性的宽带频谱感知方案.该方案将宽带频谱感知分为主用户占子带集合势的估计和子带位置判决两步.在两次不同感知结果中利用主用户连续占用子带的特性,有效地实现最终感知性能的提升.理论分析和仿真结果表明,该方案不仅能够解决传统感知方法依赖噪声和主用户信号先验信息的问题,而且对抗噪声功率不确定性具有鲁棒性.特别地,与传统的能量检测频谱感知算法相比,该算法能有效地实现宽带频谱盲感知.

关键词: 认知无线电, 宽带频谱感知, 集合势估计, 能量检测, 谱函数

Abstract: To solve the problem that traditional spectrum sensing methods require a prior knowledge of the noise power and the primary user signal,and are vulnerable to noise uncertainty,signal set cardinality and contiguity based wideband spectrum sensing schemes are proposed for cognitive radios.The proposed schemes perform wideband spectrum sensing in two phases:estimation of the cardinality of occupied subbands set and decisions of the occupied subband location.Through different cardinality estimations,performance can be effectively improved by exploiting occupied subbands continuity feature.Theoretical analysis and simulation results verify that the proposed algorithm demands no a prior knowledge of the noise power and the primary user signal,and is robust against the noise power uncertainty problem.It can effectively discern subbands status blindly,compared with the conventional spectrum sensing methods.

Key words: cognitive radio, wideband spectrum sensing, subspace identification, energy detection, spectrum function

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