Sub-Nyquist rate ADC sampling-based compressive channel estimation
暂无分享,去创建一个
[1] David L Donoho,et al. Compressed sensing , 2006, IEEE Transactions on Information Theory.
[2] Fumiyuki Adachi,et al. New direction of broadband wireless technology , 2007, Wirel. Commun. Mob. Comput..
[3] Fumiyuki Adachi,et al. Improved least mean square algorithm with application to adaptive sparse channel estimation , 2013, EURASIP Journal on Wireless Communications and Networking.
[4] Wotao Yin,et al. Sparse Signal Reconstruction via Iterative Support Detection , 2009, SIAM J. Imaging Sci..
[5] Zhu Han,et al. Compressive Sensing Based High-Resolution Channel Estimation for OFDM System , 2012, IEEE Journal of Selected Topics in Signal Processing.
[6] Fumiyuki Adachi,et al. Improved adaptive sparse channel estimation based on the least mean square algorithm , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).
[7] Franz Hlawatsch,et al. A compressed sensing technique for OFDM channel estimation in mobile environments: Exploiting channel sparsity for reducing pilots , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[8] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[9] Justin K. Romberg,et al. Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals , 2009, IEEE Transactions on Information Theory.
[10] Bhaskar D. Rao,et al. Sparse channel estimation via matching pursuit with application to equalization , 2002, IEEE Trans. Commun..
[11] Hongyang Chen,et al. Distributed Wireless Sensor Network Localization Via Sequential Greedy Optimization Algorithm , 2010, IEEE Transactions on Signal Processing.
[12] R. Marks. Introduction to Shannon Sampling and Interpolation Theory , 1990 .
[13] Shengli Zhou,et al. Sparse channel estimation for multicarrier underwater acoustic communication: From subspace methods to compressed sensing , 2009, OCEANS 2009-EUROPE.
[14] Robert D. Nowak,et al. Compressed channel sensing , 2008, 2008 42nd Annual Conference on Information Sciences and Systems.
[15] Emmanuel J. Cand. REJOINDER: THE DANTZIG SELECTOR: STATISTICAL ESTIMATION WHEN P IS MUCH LARGER THAN N , 2007 .
[16] Joel A. Tropp,et al. Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit , 2007, IEEE Transactions on Information Theory.
[17] Urbashi Mitra,et al. Sparse channel estimation with zero tap detection , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).
[18] Hsiao-Hwa Chen,et al. Energy-Efficient Coverage Based on Probabilistic Sensing Model in Wireless Sensor Networks , 2010, IEEE Communications Letters.
[19] Deanna Needell,et al. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, ArXiv.
[20] Brian M. Sadler,et al. A Sub-Nyquist Rate Sampling Receiver Exploiting Compressive Sensing , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.
[21] H. Vincent Poor,et al. Non-Line-of-Sight Node Localization Based on Semi-Definite Programming in Wireless Sensor Networks , 2009, IEEE Transactions on Wireless Communications.
[22] Jiming Chen,et al. On Optimal Information Capture by Energy-Constrained Mobile Sensors , 2010, IEEE Transactions on Vehicular Technology.
[23] Fumiyuki Adachi,et al. Sparse Multipath Channel Estimation Using Compressive Sampling Matching Pursuit Algorithm , 2010, ArXiv.
[24] Emmanuel J. Candès,et al. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.
[25] Emmanuel J. Cand. The Restricted Isometry Property and Its Implications for Compressed Sensing , 2008 .
[26] Dipankar Raychaudhuri,et al. Frontiers of Wireless and Mobile Communications , 2012, Proceedings of the IEEE.
[27] E. Candès. The restricted isometry property and its implications for compressed sensing , 2008 .
[28] Yonina C. Eldar,et al. From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals , 2009, IEEE Journal of Selected Topics in Signal Processing.