Title :
Vector precoding based on Geometric Mean Decomposition for MIMO transmission system
Author :
Geng, Xuan ; Jiang, Lingge ; He, Chen
Author_Institution :
Dept. of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai
Abstract :
The Geometric Mean Decomposition (GMD) for MIMO channel matrix can obtain identical subbchannel gains, which is a useful property to improve performance gains of precoding. In this paper, we combine the vector precoding with GMD for channel matrix to design the transceiver for MIMO transmission system. Under the proposed transceiver structure, the minimum square error (MSE) of receive symbols are obtained. To minimize the MSE, two schemes in terms of perturbation vector are proposed. In the first scheme, the perturbation vector has only continuous values, thus it is regarded as interference for MSE. In the second scheme, the perturbation vector is generalized to have both continuous and discrete values, so it is partially dealt with as interference after modulo operation. In these two schemes, the optimum perturbation vectors are presented in MMSE criterion respectively.
Keywords :
MIMO communication; least mean squares methods; matrix algebra; precoding; transceivers; vectors; wireless channels; MIMO transmission system; MMSE; channel matrix; geometric mean decomposition; minimum square error method; perturbation vector; transceiver design; vector precoding; MIMO; Matrix decomposition; Neural networks; Performance gain; Performance loss; Radiofrequency interference; Signal processing; Transceivers; Transmitters; Wireless communication; GMD; MIMO; Vector precoding;
Conference_Titel :
Neural Networks and Signal Processing, 2008 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-2310-1
Electronic_ISBN :
978-1-4244-2311-8
DOI :
10.1109/ICNNSP.2008.4590356