Average Likelihood Method for Classification of CDMA

Author

Irizarry, Alfredo Vega ; Fam, Adly

Author_Institution

Air Force Res. Lab., Rome, NY, USA

fYear

2014

fDate

6-8 Oct. 2014

Firstpage

760

Lastpage

765

Abstract

A New algorithm for classifying Direct Sequence Code Division Multiple Access (DS-CDMA) signals in additive white Gaussian noise (AGWN) is proposed based on the average likelihood (AL) function. The AL is express in terms of the code length and the number of active users. These parameters constitute the hypothesis under test. While the AL function is expressed in an analytical form, the implementation requires knowledge on the spreading codes that achieve a low Total Squared Correlation (TSC) value. This complexity can be simplified by developing a hard decision scheme which only requires knowledge on matrices that achieve the lowest TSC. Our study cases include binary and multiclass classification using full loaded DS-CDMA with knowledge on the chip period. Code lengths of powers of 2 are used as a proof of concept.

Keywords

AWGN; code division multiple access; codes; matrix algebra; signal classification; spread spectrum communication; AGWN; AL function method; DS-CDMA signal classification; additive white Gaussian noise; average likelihood function method; binary classification; chip period; code length; direct sequence code division multiple access signal classification; hard decision scheme; low total squared correlation value; multiclass classification; number-of-active users; spreading codes; Classification algorithms; Complexity theory; Correlation; Error correction; Error correction codes; Multiaccess communication; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Military Communications Conference (MILCOM), 2014 IEEE

Conference_Location

Baltimore, MD

Type

conf

DOI

10.1109/MILCOM.2014.132

Filename

6956853