A Review of Heuristic Near-Optimum MuD for MC-CDMA Systems Nacera Larbi CDS -Satellites Development Centre PB 4065, Ibn Rochd USTO Oran 31130, Algeria nacera73@hotmail.com Fatima Debbat Computer Science Department Faculty of Sciences and technology University of Mascara, Algeria debbat_fati@yahoo.fr A. Boudghene Stambouli Electronics Department Faculty of Electrical and Electronic University of Sciences and Technology of Oran USTO, Algeria stambouli@ssb-foundation.com Abstract—This paper reviews the performances of three heuristic near-optimum Multiuser Detection (MuD) approaches applied to the synchronous Multicarrier Code Division Multiple Access (MC-CDMA) communication systems. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Ant-Colony Optimization (ACO) heuristic MuD detection algorithms are analyzed in details. The simulations show that, the bit error rate (BER) performance reached by all near optimum Heuristic MuD depends on the system operation conditions and the channel used. It was shown also that ACO MuD is capable of reducing significantly the computational complexity in comparison to that of Verdu’s optimum MuD. Keywords-component; MC-CDMA; MuD; Heuristic; GA; PSO; ACO; BER. I. INTRODUCTION In recent years, Multi-Carrier Code Division Multiple Access has been receiving widespread interests for future wireless communications. Combining Orthogonal Frequency Division Multiplex (OFDM) modulation and CDMA, this scheme benefits from the main advantages of both techniques: high spectral efficiency, multiple access capability, robustness in case of frequency selective channels, high flexibility, narrow-band interference rejection [1-7]. The MC-CDMA system enables the realization of powerful detectors due to the avoidance of Inter-Symbol Interference (ISI) and Inter-Carrier Interference (ICI) in the detection process. These detectors can also be classified as either single- user detection or Multiuser Detection (MuD). Optimal and sub- optimal MuD have been proposed for MC-CDMA systems [8- 9]. The Maximum Likelihood (ML) MuD offers the best Bit Error Rate (BER) performance among all multi-user detectors (and is called the optimal MuD receiver). The ML-MuD maximizes the joint probability by evaluating a maximum- likelihood function over the set of all possible users' symbol sequences forming an NP-hard optimization problem. Thus, the optimal MuD has a computational complexity that increases exponentially with the number of users and, hence, is impractical to implement. To overcome this limitation, several suboptimal techniques have been proposed in the literatures that provide reliable performance with reduced complexity. Motivated by this, the main objective of this work is to evaluate the performances of several heuristic MuD detectors for MC-CDMA systems, taking into account their BER and computational complexity as performances criteria. The field of heuristic in combinatorial optimization problems is a rapidly growing field of research [10-11]. A survey of the nowadays most important heuristic applied to MuD for MC-CDMA systems from a conceptual point of view is given. The different components and concepts that are used in the different heuristics, in order to analyze their performances in harsh environment using Rayleigh fading channel and Rayleigh multipath channel, are outlined. These include: Genetic algorithm [12], Particle Swarm Optimization [13] and Ant- Colony Optimization [14]. This paper is organized as follows. In Section II, we provide the problem formulation of MuD for synchronous MC- CDMA system. Section III, highlights the operating principle of the GA assisted MuD designed for a synchronous MC- CDMA system. Section IV, details the PSO MuD algorithm. Section V, illustrates the ACO MuD algorithm. In Section VI, a comparison study is done. Finally, in section VII, conclusions and future work are presented. II. PROBLEM FORMULATION OF MUD FOR SYUNCHRONOUS MC-CDMA SYSTEM The MC-CDMA system model is shown in Fig. 1. Since we are considering synchronous MC-CDMA, we consider only one time slot. Figure 1. MC-CDMA Transmitter