Frequency-domain channel tracking for MIMO-OFDM systems, validated with an experimental data in 5.2 GHz wireless channel

Author(s):  
A. K. Samingan ◽  
I. Suleiman ◽  
A. A. Abdul Rahman ◽  
Z. Mohd Yusof
2007 ◽  
Vol E90-B (5) ◽  
pp. 1052-1060 ◽  
Author(s):  
Y. ASAI ◽  
W. JIANG ◽  
T. ONIZAWA ◽  
A. OHTA ◽  
S. AIKAWA

Author(s):  
Yusuke Asai ◽  
Wenjie Jiang ◽  
Takeshi Onizawa ◽  
Satoru Aikawa ◽  
Daisei Uchida ◽  
...  

2011 ◽  
Vol 10 (11) ◽  
pp. 3656-3665 ◽  
Author(s):  
Krishna P. Kongara ◽  
Peter J. Smith ◽  
Lee M. Garth

2021 ◽  
Author(s):  
Shoukath Ali k ◽  
Sampath Palaniswami

Abstract The optimal design of hybrid precoder/ combiner for Millimetre Wave (mmWave) Multiple Input and Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM ) system is developed presented. In the frequency domain approach, Sparse Bayesian Learning - Kalman Filter (SBL-KF) algorithm is used to design the optimal hybrid precoder/ combiner in mmWave MIMO OFDM systems. Sparse signal recovery problem for Single Measurement Vector (SMV) is discussed, that is close to the design of ideal digital baseband precoder by maximizing the mutual information from the hybrid precoder. SBL-KF scheme select the minimum number of active Radio Frequency (RF) chains based on the hyper parameter estimator. The minimum number of RF chain is approximate the ideal digital precoder / combiner design. Proposed SBL-KF scheme achieve low power consumption and enhanced spectral efficiency, when compared to the SBL, Orthogonal Matching Pursuit (OMP), Simultaneous OMP (SOMP) and Least Square schemes, which activate a fixed data streams and fixed number of RF chains.


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