Almost-Optimum Signature Matrices in Binary-Input Synchronous Overloaded CDMA

TL;DR

This paper introduces a genetic algorithm to design near-optimal signature matrices for binary-input synchronous overloaded CDMA, focusing on maximizing per-user channel capacity with computationally efficient criteria.

Contribution

It proposes a novel genetic algorithm approach for binary CDMA signature matrix design, emphasizing capacity optimization and alternative criteria like BER and constellation measures.

Findings

Matrices outperform traditional WBE codes in capacity.

Alternative criteria speed up matrix design process.

Simulation confirms analytical capacity improvements.

Abstract

The everlasting bandwidth limitations in wireless communication networks has directed the researchers' thrust toward analyzing the prospect of overloaded Code Division Multiple Access (CDMA). In this paper, we have proposed a Genetic Algorithm in search of optimum signature matrices for binary-input synchronous CDMA. The main measure of optimality considered in this paper, is the per-user channel capacity of the overall multiple access system. Our resulting matrices differ from the renowned Welch Bound Equality (WBE) codes, regarding the fact that our attention is specifically aimed at binary, rather than Gaussian, input distributions. Since design based on channel capacity is computationally expensive, we have focused on introducing a set of alternative criteria that not only speed up the matrix formation procedure, but also maintain optimality. The Bit Error Rate (BER) and Constellation measures are our main criteria propositions. Simulation results also verify our analytical justifications.