OFDM系统的信道与脉冲噪声的联合估计方法

doi:10.11959/j.issn.1000-436x.2018047

Abstract

Abstract:

Aiming at the impulsive noise occurring in OFDM systems,an impulsive noise mitigation algorithm based on compressed sensing theory was proposed.The proposed algorithm firstly treated the channel impulse response and the impulsive noise as a joint sparse vector by exploiting the sparsity of both them.Then the sparse Bayesian learning framework was adopted to jointly estimate the channel impulse response,the impulsive noise and the data symbols,in which the data symbols were regarded as unknown parameters.Compared with the existing impulsive noise mitigation methods,the proposed algorithm not only utilized all subcarriers but also did not use any a priori information of the channel and impulsive noise.The simulation results show that the proposed algorithm achieves significant improvement on the channel estimation and bit error rate performance.

Key words: orthogonal frequency division multiplexing, channel estimation, impulsive noise, sparse Bayesian learning, compressed sensing

CLC Number:

TN911.4

Xinrong LYU,Youming LI,Mingchen YU. Joint channel and impulsive noise estimation method for OFDM systems[J]. Journal on Communications, 2018, 39(3): 191-198.

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[1]	LIU S , YANG F , DING W ,et al. Double kill:compressive-sensing-based narrow-band interference and impulsive noise mitigation for vehicular communications[J]. IEEE Transactions on Vehicular Technology, 2016,65(7): 5099-5109.
[2]	SACUTO F , LABEAU F , AGBA B L . Wide band time-correlated model for wireless communications under impulsive noise within power substation[J]. IEEE Transactions on Wireless Communications, 2014,13(3): 1449-1461.
[3]	KUAI X , SUN H , ZHOU S ,et al. Impulsive noise mitigation in underwater acoustic OFDM systems[J]. IEEE Transactions on Vehicular Technology, 2016,65(10): 8190-8202.
[4]	MAHMOOD A , CHITRE M , ARMAND M A . Detecting OFDM signals in alpha-stable noise[J]. IEEE Transactions on Communications, 2014,62(10): 3571-3583.
[5]	JUWONO F H , GUO Q , HUANG D ,et al. Deep clipping for impulsive noise mitigation in OFDM-based power-line communications[J]. IEEE Transactions on Power Delivery, 2014,29(3): 1335-1343.
[6]	DARSENA D , GELLI G , MELITO F ,et al. ICI-free equalization in OFDM systems with blanking preprocessing at the receiver for impulsive noise mitigation[J]. IEEE Signal Processing Letters, 2015,22(9): 1321-1325.
[7]	LIN J , NASSAR M , EVANS B L . Impulsive noise mitigation in powerline communications using sparse Bayesian learning[J]. IEEE Journal on Selected Areas in Communications, 2013,31(7): 1172-1183.
[8]	DUARTE M F , ELDAR Y C . Structured compressed sensing:from theory to applications[J]. IEEE Transactions on Signal Processing, 2011,59(9): 4053-4085.
[9]	AL-NAFFOURI T Y , QUADEER A A , CAIRE G . Impulse noise estimation and removal for OFDM systems[J]. IEEE Transactions on Communications, 2014,62(3): 976-989.
[10]	KORKI M , ZHANG J , ZHANG C ,et al. Block-sparse impulsive noise reduction in OFDM systems-a novel iterative bayesian approach[J]. IEEE Transactions on Communications, 2015,64(1): 271-284.
[11]	PRASAD R , MURTHY C R , RAO B D . Joint approximately sparse channel estimation and data detection in OFDM systems using sparse Bayesian learning[J]. IEEE Transactions on Signal Processing, 2014,62(14): 3591-3603.
[12]	ZHENG Z , HAO C , YANG X . Least squares channel estimation with noise suppression for OFDM systems[J]. Electronics Letters, 2016,52(1): 37-39.
[13]	LIU Y , TAN Z , HU H ,et al. Channel estimation for OFDM[J]. IEEE Communications Surveys ＆ Tutorials, 2014,16(4): 1891-1908.
[14]	CHIEN Y R . Iterative channel estimation and impulsive noise mitigation algorithm for OFDM-based receivers with application to power-line communications[J]. IEEE Transactions on Power Delivery, 2015,30(6): 2435-2442.
[15]	MEHBOOB A , LI Z , KHANGOSSTAR J ,et al. Joint channel and impulsive noise estimation for OFDM based power line communication systems using compressed sensing[C]// IEEE International Symposium on Power Line Communications and ITS Applications. 2013: 203-208.
[16]	NASSAR M , SCHNITER P , EVANS B L . A factor graph approach to joint OFDM channel estimation and decoding in impulsive noise environments[J]. IEEE Transactions on Signal Processing, 2014,62(6): 1576-1589.
[17]	WIPF D P , RAO B D . Sparse Bayesian learning for basis selection[J]. IEEE Transactions on Signal Processing, 2004,52(8): 2153-2164.
[18]	DING W , YANG F , PAN C ,et al. Compressive sensing based channel estimation for OFDM systems under long delay channels[J]. IEEE Transactions on Broadcasting, 2014,60(2): 313-321.
[19]	DONOHO D L . Compressed sensing[J]. IEEE Transactions on Information Theory, 2006,52(4): 1289-1306.
[20]	WIPF D D , . Sparse estimation with structured dictionaries[C]// International Conference on Neural Information Processing Systems. 2011: 2016-2024.
[21]	DING W , LU Y , YANG F ,et al. Spectrally efficient CSI acquisition for power line communications:a Bayesian compressive sensing perspective[J]. IEEE Journal on Selected Areas in Communications, 2016,34(7): 2022-2032.
[22]	ITU-R M. Test environment and deployment models-ANNEX2[S]. ITU-R, 2000:24-30.

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参数名称	参数值
系统子带带宽	15 kHz
OFDM符号持续时间	83.3 μs（保护间隔为16.67 μs）
总子载波数N	256
循环前缀长度	64
导频子载波数P	分别为24、44、64
空子载波数U	分别为20、50、80、100
信道长度L	64
信号调制模式	4-QAM
GMM模型	k=3，p_k={0.9,0.07,0.03}，γ_k={1,100,1 000}

Joint channel and impulsive noise estimation method for OFDM systems

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