DocumentCode
3542046
Title
Research of Sphere Decoding Detection Algorithm in LTE-A System
Author
Xu Ren ; Huahua Wang
Author_Institution
Chongqing Univ. of Posts & Telecommun., Chongqing, China
fYear
2012
fDate
21-23 Sept. 2012
Firstpage
1
Lastpage
4
Abstract
Multi-Input Multi-Output (MIMO) has become a popular technique to increase spectral efficient. Meanwhile, the design of cost-effective receiver for LTE-A system remains a challenging task. The sphere detection algorithm performs exact Maximum Likelihood (ML) detection algorithm, however, its decoding complexity is greatly impacted by the initial radius of decoding. A new type of sphere decoding algorithm based on threshold is proposed in this paper. This new algorithm, considering the influence of signal-to-noise ratio and channel condition number on detection algorithm, has lower sphere decoding complexity and ensures performance of sphere decoding. This algorithm has been applied to the LTE-TDD wireless integrated test instrument and has shown perfect performance.
Keywords
Long Term Evolution; MIMO communication; communication complexity; maximum likelihood decoding; maximum likelihood detection; radio receivers; radio spectrum management; wireless channels; LTE-A system; LTE-TDD wireless integrated test instrument; MIMO; ML detection algorithm; channel condition number; cost-effective receiver design; maximum likelihood detection algorithm; multiinput multioutput; signal-to-noise ratio; spectral efficiency; sphere decoding algorithm; sphere decoding complexity; sphere decoding detection algorithm; sphere detection algorithm; Algorithm design and analysis; Bit error rate; Complexity theory; Maximum likelihood decoding; Signal to noise ratio; Transmitting antennas;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications, Networking and Mobile Computing (WiCOM), 2012 8th International Conference on
Conference_Location
Shanghai
ISSN
2161-9646
Print_ISBN
978-1-61284-684-2
Type
conf
DOI
10.1109/WiCOM.2012.6478645
Filename
6478645
Link To Document