Low complexity norm-adaption least mean square/fourth algorithm and its applications for sparse channel estimation

2016 ◽  
Author(s):  
Yingsong Li ◽  
Yanyan Wang ◽  
Tao Jiang
Keyword(s):  
Channel Estimation ◽  
Low Complexity ◽  
Mean Square ◽  
Least Mean Square ◽  
Sparse Channel Estimation ◽  
Sparse Channel

scholarly journals An Improved Proportionate Normalized Least-Mean-Square Algorithm for Broadband Multipath Channel Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yingsong Li ◽  
Masanori Hamamura
Keyword(s):  
Channel Estimation ◽  
Estimation Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Sparse Channel Estimation ◽  
Normalized Least Mean Square ◽  
Least Mean Square Algorithm ◽  
The Cost ◽  
Sparse Channel ◽  
Steady State Performance

To make use of the sparsity property of broadband multipath wireless communication channels, we mathematically propose anlp-norm-constrained proportionate normalized least-mean-square (LP-PNLMS) sparse channel estimation algorithm. A generallp-norm is weighted by the gain matrix and is incorporated into the cost function of the proportionate normalized least-mean-square (PNLMS) algorithm. This integration is equivalent to adding a zero attractor to the iterations, by which the convergence speed and steady-state performance of the inactive taps are significantly improved. Our simulation results demonstrate that the proposed algorithm can effectively improve the estimation performance of the PNLMS-based algorithm for sparse channel estimation applications.

A Low-Complexity Sparse Channel Estimation Method for OFDM Systems

2010 ◽  
Vol E93-B (8) ◽  
pp. 2211-2214
Author(s):  
Bin SHENG ◽  
Pengcheng ZHU ◽  
Xiaohu YOU ◽  
Lan CHEN
Keyword(s):  
Channel Estimation ◽  
Estimation Method ◽  
Low Complexity ◽  
Ofdm Systems ◽  
Sparse Channel Estimation ◽  
Sparse Channel
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