DocumentCode :
125957
Title :
Adaptive stream mapping in MIMO-OFDM with linear precoding
Author :
Lei Wang ; Zhongping Zhang
Author_Institution :
Technol. Dept., China Unicom, Beijing, China
fYear :
2014
fDate :
16-23 Aug. 2014
Firstpage :
1
Lastpage :
4
Abstract :
Linear precoding techniques are widely used in emerging MIMO-OFDM standards such as 3GPP LTE and WiMAX. These involve mapping a variable number of streams of transmit data symbols to the transmit antennas using precoding matrices selected from a pre-defined set on the basis of channel state information (CSI) fed back from the receiver. Previous work on these schemes and on selection of precoding matrices has assumed that linear detectors are used, but these cannot exploit the full receive-end diversity when multiple streams are transmitted. This paper presents an adaptive precoding scheme using maximum likelihood (ML) detection with a precoder selection scheme based on minimum BER. It shows that full diversity can be achieved, and that a significant gain is available over adaptive linear precoding using linear detection, over antenna selection, and over spatial multiplexing.
Keywords :
3G mobile communication; Long Term Evolution; MIMO communication; OFDM modulation; WiMax; error statistics; maximum likelihood detection; precoding; radio receivers; space division multiplexing; transmitting antennas; 3GPP LTE; BER; CSI; MIMO-OFDM standards; WiMAX; adaptive linear precoding; adaptive precoding; adaptive stream mapping; antenna selection; channel state information; data symbols; linear detection; linear detectors; maximum likelihood detection; multiple streams; precoding matrices; radio receiver; receive-end diversity; spatial multiplexing; transmit antennas; Bit error rate; OFDM; Receivers; Transmitting antennas; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
General Assembly and Scientific Symposium (URSI GASS), 2014 XXXIth URSI
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/URSIGASS.2014.6929322
Filename :
6929322
Link To Document :
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