STRUCTURED ESTIMATION OF TIME-VARYING NARROWBAND WIRELESS COMMUNICATION CHANNELS

被引:0
作者
Beygi, Sajjad [1 ]
Mitra, Urbashi [1 ]
机构
[1] Univ Southern Calif, Ming Hsieh Dept Elect Engn, Los Angeles, CA 90007 USA
来源
2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2017年
关键词
Narrowband time-varying channels; delay-Doppler leakage estimation; low-rank matrix recovery; atomic norm; convex optimization; SPARSE; GEOMETRY;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
In this paper, the estimation of a narrowband time-varying channel under the practical assumptions of finite block length and finite transmission bandwidth is investigated. It is shown that the signal after passing through a time-varying narrowband channel, under these assumptions, reveals a particular low-rank structure. The rank in this structure is governed by the number of dominant paths in the channel. Moreover, it is shown that this low-rank structure can be represented as a summation of few rank-one atoms (matrix) that are fully described by the channel and leakage key parameters. To estimated the channel, a novel approach based on minimization of atomic norm using measurements of signal at time domain is proposed. Numerical results show that the performance of proposed algorithm is independent of the leakage effect and the new method can achieve significant gains over previously proposed methods.
引用
收藏
页码:3529 / 3533
页数:5
相关论文
共 16 条
[1]   Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels [J].
Bajwa, Waheed U. ;
Haupt, Jarvis ;
Sayeed, Akbar M. ;
Nowak, Robert .
PROCEEDINGS OF THE IEEE, 2010, 98 (06) :1058-1076
[2]  
Beygi Sajjad, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), P4299, DOI 10.1109/ICASSP.2014.6854413
[3]   Nested Sparse Approximation: Structured Estimation of V2V Channels Using Geometry-Based Stochastic Channel Model [J].
Beygi, Sajjad ;
Mitra, Urbashi ;
Strom, Erik G. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2015, 63 (18) :4940-4955
[4]   The Convex Geometry of Linear Inverse Problems [J].
Chandrasekaran, Venkat ;
Recht, Benjamin ;
Parrilo, Pablo A. ;
Willsky, Alan S. .
FOUNDATIONS OF COMPUTATIONAL MATHEMATICS, 2012, 12 (06) :805-849
[5]   Guaranteed Blind Sparse Spikes Deconvolution via Lifting and Convex Optimization [J].
Chi, Yuejie .
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2016, 10 (04) :782-794
[6]  
Choudhary Sunav, 2016, 2016 IEEE INT C AC S
[7]  
Grant M., 2014, CVX: MATLAB software for disciplined convex programming, version 2.0 beta
[8]   Underwater Data Collection Using Robotic Sensor Networks [J].
Hollinger, Geoffrey A. ;
Choudhary, Sunav ;
Qarabaqi, Parastoo ;
Murphy, Christopher ;
Mitra, Urbashi ;
Sukhatme, Gaurav S. ;
Stojanovic, Milica ;
Singh, Hanumant ;
Hover, Franz .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2012, 30 (05) :899-911
[9]  
Jnawali S, 2011, IEEE VTS VEH TECHNOL
[10]   Estimation of rapidly time-varying sparse channels [J].
Li, Weichang ;
Preisig, James C. .
IEEE JOURNAL OF OCEANIC ENGINEERING, 2007, 32 (04) :927-939