Title :
Sphere decoding based on QR decomposition in STBC
Author :
Koudougnon, Herve ; Saadane, Rachid ; Belkasmi, Mostafa
Author_Institution :
Lab. SIME, ENSIAS Rabat, Rabat, Morocco
Abstract :
A multiple-input-multiple-output (MIMO) system using Space-Time Block Coding (STBC) techniques can be implemented to improve the capacity of a wireless link. The optimal decoder used the maximum likelihood(ML). But as the number of the antennas in the system and the data rates increase, the ML detector becomes too complex to use. The detectors the least complex and efficient are Zero-Forcing(ZF), MMSE and especially the Sphere Decoding(SD) that is based on QR Decomposition(QRD). In this paper, we study the Gram-Schmidt, Householder and Givens Rotation decomposition methods and compare their efficiency in terms of computational complexity and error rate performance. The channel coding is added to the chain of transmission in order to improve performance. SD receivers are optimized for coded MIMO. Simulations show that the SD detector based on Gram-Schmidt decomposition with channel encoding gives the best results.
Keywords :
MIMO communication; channel capacity; channel coding; communication complexity; maximum likelihood decoding; radio links; radio receivers; space-time block codes; Givens rotation decomposition methods; Gram-Schmidt decomposition method; Householder methods; MIMO system; ML detector; MMSE; QR decomposition; QRD; SD receivers; STBC; antennas; channel coding; coded MIMO; computational complexity; error rate performance; maximum likelihood decoding; multiple-input multiple-output system; optimal decoder; space-time block coding; sphere decoding; wireless link capacity; zero-forcing; Bit error rate; Channel coding; Detectors; MIMO; Receiving antennas; Signal to noise ratio; QR Decomposition; STBC; Sphere decoding; channel coding;
Conference_Titel :
Multimedia Computing and Systems (ICMCS), 2011 International Conference on
Conference_Location :
Ouarzazate
Print_ISBN :
978-1-61284-730-6
DOI :
10.1109/ICMCS.2011.5945624