DocumentCode :
2529244
Title :
A family of linear complexity likelihood ascent search detectors for CDMA multiuser detection
Author :
Sun, Yi
Author_Institution :
Dept. of Electr. Eng., City Coll. of New York, NY, USA
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
713
Abstract :
We propose a family of likelihood ascent search (LAS) detectors that achieve maximum likelihood detection in a subset of hypotheses whereas their expected per-bit computational complexity is linear in the number of users. The LAS detectors monotonically increase likelihood at every search step, and thus monotonically decrease error probability, and converge to a fixed point in a finite number of steps with probability one. It is proved that the thresholds set up in the LAS detectors are necessary and sufficient for monotonic likelihood ascent for an arbitrary signature crosscorrelation matrix with probability one. Among the LAS detectors, the set of wide-sense sequential LAS (WSLAS) detectors is shown to be a set of local maximum likelihood (LML) detectors defined with neighborhood size one. The properties of the fixed points and their observation regions are studied. Simulations are carried out and verify analytical results
Keywords :
code division multiple access; computational complexity; error statistics; maximum likelihood detection; multiuser channels; search problems; spread spectrum communication; CDMA multiuser detection; arbitrary signature crosscorrelation matrix; error probability; linear complexity likelihood ascent search detectors; maximum likelihood detection; per-bit computational complexity; simulations; Cities and towns; Computational complexity; Detectors; Educational institutions; Interference cancellation; Limit-cycles; Maximum likelihood detection; Multiaccess communication; Multiuser detection; Sun;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Spread Spectrum Techniques and Applications, 2000 IEEE Sixth International Symposium on
Conference_Location :
Parsippany, NJ
Print_ISBN :
0-7803-6560-7
Type :
conf
DOI :
10.1109/ISSSTA.2000.876527
Filename :
876527
Link To Document :
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