An analysis on partial PIC multi-user detection with LMS algorithms for CDMA

Author

Huang, Yung-Fa ; Wen, Jyh-horng

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Chung Chou Inst. of Technol., Changhua, Taiwan

Volume

1

fYear

2003

fDate

7-10 Sept. 2003

Firstpage

17

Abstract

In the partial parallel interference cancellation (PPIC) scheme for direct-sequence code-division multiple-access (DS-CDMA) communication systems, the partial cancellation weight (PCW) does not give us any idea about the correctness of the bit-decision in the previous stage. However, the PCW can be updated by the least-mean-square (LMS) algorithm and may turn into the negative side as the bit-decision error occurs in the previous stage. Therefore, in this paper, we investigate the property of the PCW based on the LMS algorithms. Furthermore, with the maximum a posteriori probability (MAP) detection criterion, an optimal threshold for the adaptation PCW is found to judge the correctness of the bit-decisions and get a mount performance improvement.

Keywords

cellular radio; code division multiple access; interference suppression; least mean squares methods; maximum likelihood estimation; multiuser detection; probability; radiofrequency interference; spread spectrum communication; DS-CDMA communication systems; LMS algorithms; MAP detection criterion; bit-decision error; direct-sequence code-division multiple-access; least-mean-square; maximum a posteriori probability; partial PIC multiuser detection; partial cancellation weight; partial parallel interference cancellation; Algorithm design and analysis; Amplitude estimation; Computer science; Convergence; Error correction; Interference cancellation; Least squares approximation; Multiaccess communication; Multiple access interference; Multiuser detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003. 14th IEEE Proceedings on

Print_ISBN

0-7803-7822-9

Type

conf

DOI

10.1109/PIMRC.2003.1264223

Filename

1264223