A New Decoding Scheme for Errorless Codes for Overloaded CDMA with Active User Detection

TL;DR

This paper introduces an improved decoding algorithm for COWDA codes in overloaded CDMA systems, significantly enhancing error performance by modeling user activity with a Poisson distribution.

Contribution

An advanced decoding algorithm that improves error rates for COWDA codes by incorporating practical user activity models in overloaded CDMA systems.

Findings

Bit-Error-Rate reduced by a factor of 400 in some conditions

Performance improvement over previous ML decoder

Effective under practical user activity assumptions

Abstract

Recently, a new class of binary codes for overloaded CDMA systems are proposed that not only has the ability of errorless communication but also suitable for detecting active users. These codes are called COWDA [1]. In [1], a Maximum Likelihood (ML) decoder is proposed for this class of codes. Although the proposed scheme of coding/decoding show impressive performance, the decoder can be improved. In this paper by assuming more practical conditions for the traffic in the system, we suggest an algorithm that increases the performance of the decoder several orders of magnitude (the Bit-Error-Rate (BER) is divided by a factor of 400 in some Eb/N0's The algorithm supposes the Poison distribution for the time of activation/deactivation of the users.