Weight behavior analysis of adaptive two-stage partial PIC receivers

Yu T. Hsieh*, Wen-Rong Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Partial parallel-interference-cancelation (PIC) is a well-known multiuser detection technique for DS/CMDA systems. Conventionally, partial-cancelation- factors (PCFs) are optimally derived and kept constant in a designated interval. Recently, a special kind of partial PIC was proposed. In the approach, PCFs are adaptively trained (chip-by-chip) using the least-mean-square (LMS) algorithm, and PCFs are updated with a bit-by-bit fashion. It has been shown that the adaptive partial PIC detector outperforms conventional partial PIC. Despite its good performance, performance analysis of the approach has not been explored yet. This paper is aimed to fill the gap by conducting the performance analysis of an adaptive two-stage partial PIC detector. We first analyze optimal weights (i.e., PCFs), weight error means, and weight error variances. Simulation results indicates that our analytical results highly agree with empirical ones.

Original languageEnglish
Title of host publication2007 IEEE Wireless Communications and Networking Conference, WCNC 2007
Pages991-996
Number of pages6
DOIs
StatePublished - 27 Nov 2007
Event2007 IEEE Wireless Communications and Networking Conference, WCNC 2007 - Kowloon, China
Duration: 11 Mar 200715 Mar 2007

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
ISSN (Print)1525-3511

Conference

Conference2007 IEEE Wireless Communications and Networking Conference, WCNC 2007
CountryChina
CityKowloon
Period11/03/0715/03/07

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  • Cite this

    Hsieh, Y. T., & Wu, W-R. (2007). Weight behavior analysis of adaptive two-stage partial PIC receivers. In 2007 IEEE Wireless Communications and Networking Conference, WCNC 2007 (pp. 991-996). [4204364] (IEEE Wireless Communications and Networking Conference, WCNC). https://doi.org/10.1109/WCNC.2007.188