系统工程与电子技术
繫統工程與電子技術
계통공정여전자기술
Systems Engineering and Electronics
2015年
12期
2701-2706
,共6页
正交频分复用%脉冲噪声%相关熵%参数估计
正交頻分複用%脈遲譟聲%相關熵%參數估計
정교빈분복용%맥충조성%상관적%삼수고계
orthogonal frequency division multiplexing (OFDM)%impulsive noise%correntropy%parameters estimation
针对传统的正交频分复用(orthogonal frequency division multiplexing,OFDM)时域参数估计方法在Alpha 稳定分布噪声环境下性能退化的问题,该文提出了一种基于相关熵的时域参数估计新方法。相关熵是适用于非高斯信号处理的一种广义相关函数,用于表征随机变量的局部相似性。该方法利用 OFDM 信号时域结构具有局部相似性这一特点以及相关熵对脉冲噪声较好的抑制作用,完成 Alpha 稳定分布噪声下 OFDM 信号有用符号时间和符号周期这两个时域参数的估计。此外,为进一步提高强脉冲噪声下有用符号时间和符号周期的估计性能,该文利用累积法对相关熵进行了改进。仿真结果表明,在 Alpha 稳定分布噪声下,本文提出的基于相关熵的方法具有良好的估计性能,并且在强脉冲噪声下优于基于分数低阶统计量的方法。
針對傳統的正交頻分複用(orthogonal frequency division multiplexing,OFDM)時域參數估計方法在Alpha 穩定分佈譟聲環境下性能退化的問題,該文提齣瞭一種基于相關熵的時域參數估計新方法。相關熵是適用于非高斯信號處理的一種廣義相關函數,用于錶徵隨機變量的跼部相似性。該方法利用 OFDM 信號時域結構具有跼部相似性這一特點以及相關熵對脈遲譟聲較好的抑製作用,完成 Alpha 穩定分佈譟聲下 OFDM 信號有用符號時間和符號週期這兩箇時域參數的估計。此外,為進一步提高彊脈遲譟聲下有用符號時間和符號週期的估計性能,該文利用纍積法對相關熵進行瞭改進。倣真結果錶明,在 Alpha 穩定分佈譟聲下,本文提齣的基于相關熵的方法具有良好的估計性能,併且在彊脈遲譟聲下優于基于分數低階統計量的方法。
침대전통적정교빈분복용(orthogonal frequency division multiplexing,OFDM)시역삼수고계방법재Alpha 은정분포조성배경하성능퇴화적문제,해문제출료일충기우상관적적시역삼수고계신방법。상관적시괄용우비고사신호처리적일충엄의상관함수,용우표정수궤변량적국부상사성。해방법이용 OFDM 신호시역결구구유국부상사성저일특점이급상관적대맥충조성교호적억제작용,완성 Alpha 은정분포조성하 OFDM 신호유용부호시간화부호주기저량개시역삼수적고계。차외,위진일보제고강맥충조성하유용부호시간화부호주기적고계성능,해문이용루적법대상관적진행료개진。방진결과표명,재 Alpha 은정분포조성하,본문제출적기우상관적적방법구유량호적고계성능,병차재강맥충조성하우우기우분수저계통계량적방법。
To address the problem that the conventional algorithms degrade severely in Alpha-stable noise environment,a new time-domain parameters estimation method based on correntropy is proposed for the orthog-onal frequency division multiplexing (OFDM)system.As a generalized correlation function,correntropy is de-fined as a local similarity measure of a random variable.Taking advantage of the feature that the time domain structure of OFDM signals has local similarity,along with the fact that correntropy can effectively suppress the impulsive noise,the proposed method estimates the time-domain parameters of OFDM signals in Alpha-stable noise.To further improve the estimation performance in strong impulsive noise environment,a cumulative algo-rithm is used in this paper.Simulation results show that the proposed method can achieve good performance in Alpha-stable distribution noise and has higher parameter estimation accuracy than the fractional lower order based analysis method in strong impulsive noise environment.