Title :
Low Complexity LMMSE Channel Estimation on GPP
Author :
Wei Shi ; Tao Peng ; Rongrong Qian ; Ran Duan ; Kuilin Chen
Author_Institution :
Key Lab. of Universal Wireless Commun., BUPT, Beijing, China
Abstract :
This paper proposes an improved linear minimum mean square error (LMMSE) algorithm of adaptive order determination by taking advantage of the structure characteristics of time domain least square (LS) channel estimation based on general-purpose processor (GPP), which provides the approximate estimation approach of max-time delay and noise power. In addition, this algorithm achieves a practical channel estimation formula which greatly reduces the complexity of the algorithm by decomposing the autocorrelation matrix into some sub-matrixes on the foundation of correlation bandwidth. Then comparisons are made between the simulation performance of improved LMMSE algorithm with those of other estimation methods for further analysis. Finally, a hardware implementation scheme of the proposed algorithm on GPP is given.
Keywords :
Long Term Evolution; approximation theory; channel estimation; computational complexity; delays; estimation theory; least mean squares methods; matrix decomposition; time-domain analysis; wireless channels; GPP; algorithm complexity; approximate estimation approach; autocorrelation matrix decomposition; correlation bandwidth; general-purpose processor-based time domain least square channel estimation; hardware implementation scheme; linear minimum mean square error algorithm; low complexity LMMSE channel estimation; max-time delay; noise power; structure characteristics; submatrixes; time domain LS channel estimation; Algorithm design and analysis; Channel estimation; Complexity theory; Correlation; Estimation; Signal processing algorithms; Signal to noise ratio; GPP; LMMSE; adaptive order determination; algorithm complexity; channel parameter;
Conference_Titel :
Communications and Networking in China (CHINACOM), 2012 7th International ICST Conference on
Conference_Location :
Kun Ming
Print_ISBN :
978-1-4673-2698-8
Electronic_ISBN :
978-1-4673-2697-1
DOI :
10.1109/ChinaCom.2012.6417604