基于概率密度函數(shù)匹配與分?jǐn)?shù)低階矩的并行盲均衡算法
doi: 10.11999/JEIT160841
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1.
(大連理工大學(xué)電子信息與電氣工程學(xué)部 大連 116024) ②(國(guó)家無(wú)線電監(jiān)測(cè)中心 北京 100037)
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(61671105, 61139001, 61172108, 81241059)
Concurrent Blind Equalization Algorithm Based on Probability Density Function Matching and Fractional Lower Order Moments
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1.
(Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China)
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2.
(State Radio Monitoring Center, Beijing 100037, China)
Funds:
The National Natural Science Foundation of China (61671105, 61139001, 61172108, 81241059)
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摘要: 為了提高脈沖噪聲下盲均衡器的性能，該文提出一種基于概率密度函數(shù)匹配與分?jǐn)?shù)低階矩的并行盲均衡算法。首先采用概率密度函數(shù)匹配的思想進(jìn)行盲均衡，充分利用其收斂速度快的優(yōu)勢(shì)。為了解決此均衡過(guò)程中引起的相位信息損失以及抑制脈沖噪聲能力差的問(wèn)題，又以并行的方式結(jié)合判決信號(hào)的分?jǐn)?shù)低階矩，并以此作為代價(jià)函數(shù)來(lái)共同更新盲均衡器的權(quán)向量，進(jìn)一步提高了算法在脈沖噪聲下的收斂速度與收斂精度。仿真實(shí)驗(yàn)表明，所提算法在有效解決相位旋轉(zhuǎn)問(wèn)題的同時(shí)較好地抑制了脈沖噪聲，此外還具有較快的收斂速度和較小的穩(wěn)態(tài)誤差，穩(wěn)健性較強(qiáng)。
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關(guān)鍵詞:
- 盲均衡 /
- 概率密度函數(shù) /
- 并行算法 /
- 分?jǐn)?shù)低階矩
Abstract: In order to improve the performance of the blind equalizer under impulsive noise environments, a novel concurrent blind equalization algorithm based on probability density function matching and fractional lower order moments is presented. This algorithm uses the idea of probability density function matching at the beginning, and makes full use of the advantage of its fast convergence speed. In order to solve the problems of the phase information loss and incapability of suppressing impulse noise, this paper combines the fractional lower order moments of the decision signal in parallel as the cost function to update the weight coefficients of the blind equalizer. The convergence speed and convergence precision is further improved. The simulation experiments results show that the algorithm can effectively solve the problem of phase rotation and better suppress the impulse noise. Moreover, the algorithm has fast convergence speed, small steady-state error and strong robustness. -
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