Online Bayesian activity detection in DS/CDMA networks

Thanh Ngoc Bui; Vikram Krishnamurthy; H. Vincent Poor

doi:10.1109/TSP.2004.838944

Online Bayesian activity detection in DS/CDMA networks

Thanh Ngoc Bui
, Vikram Krishnamurthy
, H. Vincent Poor

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

An on-line Bayesian based multiple hypotheses Shiryayev Sequential Probability Ratio Test (SSPRT) for the detection/isolation of new active users in a multiuser code division multiple access (CDMA) environment is presented. This SSPRT algorithm makes use of a priori knowledge of the user activity parameter. Comparison by simulation between this SSPRT algorithm and the non-Bayesian Matrix cumulative sum (CUSUM) shows that when Such information is available, the SSPRT algorithm that uses this information can achieve better performance than the non-Bayesian approach.

Original language	English (US)
Pages (from-to)	371-375
Number of pages	5
Journal	IEEE Transactions on Signal Processing
Volume	53
Issue number	1
DOIs	https://doi.org/10.1109/TSP.2004.838944
State	Published - Jan 2005

All Science Journal Classification (ASJC) codes

Signal Processing
Electrical and Electronic Engineering

Keywords

Activity detection
CDMA
Multiuser detection
Sequential probability ratio test

Access to Document

10.1109/TSP.2004.838944

Cite this

@article{2a785b2cbf4d4954a7a6613d533d4d81,

title = "Online Bayesian activity detection in DS/CDMA networks",

abstract = "An on-line Bayesian based multiple hypotheses Shiryayev Sequential Probability Ratio Test (SSPRT) for the detection/isolation of new active users in a multiuser code division multiple access (CDMA) environment is presented. This SSPRT algorithm makes use of a priori knowledge of the user activity parameter. Comparison by simulation between this SSPRT algorithm and the non-Bayesian Matrix cumulative sum (CUSUM) shows that when Such information is available, the SSPRT algorithm that uses this information can achieve better performance than the non-Bayesian approach.",

keywords = "Activity detection, CDMA, Multiuser detection, Sequential probability ratio test",

author = "Bui, \{Thanh Ngoc\} and Vikram Krishnamurthy and Poor, \{H. Vincent\}",

year = "2005",

month = jan,

doi = "10.1109/TSP.2004.838944",

language = "English (US)",

volume = "53",

pages = "371--375",

journal = "IEEE Transactions on Signal Processing",

issn = "1053-587X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "1",

}

TY - JOUR

T1 - Online Bayesian activity detection in DS/CDMA networks

AU - Bui, Thanh Ngoc

AU - Krishnamurthy, Vikram

AU - Poor, H. Vincent

PY - 2005/1

Y1 - 2005/1

N2 - An on-line Bayesian based multiple hypotheses Shiryayev Sequential Probability Ratio Test (SSPRT) for the detection/isolation of new active users in a multiuser code division multiple access (CDMA) environment is presented. This SSPRT algorithm makes use of a priori knowledge of the user activity parameter. Comparison by simulation between this SSPRT algorithm and the non-Bayesian Matrix cumulative sum (CUSUM) shows that when Such information is available, the SSPRT algorithm that uses this information can achieve better performance than the non-Bayesian approach.

AB - An on-line Bayesian based multiple hypotheses Shiryayev Sequential Probability Ratio Test (SSPRT) for the detection/isolation of new active users in a multiuser code division multiple access (CDMA) environment is presented. This SSPRT algorithm makes use of a priori knowledge of the user activity parameter. Comparison by simulation between this SSPRT algorithm and the non-Bayesian Matrix cumulative sum (CUSUM) shows that when Such information is available, the SSPRT algorithm that uses this information can achieve better performance than the non-Bayesian approach.

KW - Activity detection

KW - CDMA

KW - Multiuser detection

KW - Sequential probability ratio test

UR - https://www.scopus.com/pages/publications/11844290696

UR - https://www.scopus.com/pages/publications/11844290696#tab=citedBy

U2 - 10.1109/TSP.2004.838944

DO - 10.1109/TSP.2004.838944

M3 - Article

AN - SCOPUS:11844290696

SN - 1053-587X

VL - 53

SP - 371

EP - 375

JO - IEEE Transactions on Signal Processing

JF - IEEE Transactions on Signal Processing

IS - 1

ER -

Online Bayesian activity detection in DS/CDMA networks

Abstract

All Science Journal Classification (ASJC) codes

Keywords

Access to Document

Other files and links

Fingerprint

Cite this