Abstract
We propose two novel and computationally efficient metaheuristic algorithms based on Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) principles for Multiuser Detection (MUD) in Turbo Trellis Coded modulation- (TTCM-) based Space Division Multiple Access (SDMA) Orthogonal Frequency Division Multiplexing (OFDM) system. Unlike gradient descent methods, both ABC and PSO methods ensure minimization of the objective function without the solution being trapped into local optima. These techniques are capable of achieving excellent performance in the so-called overloaded system, where the number of transmit antennas is higher than the number of receiver antennas, in which the known classic MUDs fail. The performance of the proposed algorithm is compared with each other and also against Genetic Algorithm- (GA-) based MUD. Simulation results establish better performance, computational efficiency, and convergence characteristics for ABC and PSO methods. It is seen that the proposed detectors achieve similar performance to that of well-known optimum Maximum Likelihood Detector (MLD) at a significantly lower computational complexity and outperform the traditional MMSE MUD.
Highlights
Multiinput-Multioutput Orthogonal Frequency Division Multiplexing (MIMO-OFDM) [1] is considered as candidates for future 4G broadband wireless services
The Bit Error Rate (BER) performance of the Turbo Trellis Coded modulation- (TTCM-)assisted MinimumMean Squared Error (MMSE)-Artificial Bee Colony (ABC)/Particle Swarm Optimization (PSO)-SDMAOFDM system employing a 4QAM scheme is given in Figure 3, where six users are supported with the aid of six receiver antenna elements
In order to characterize the advantage of the ABC-Multiuser Detection (MUD) scheme in terms of the performance-versus-complexity tradeoff, in Table 3 we summarize the computational complexity imposed by the different MUDs assuming an Eb/No value of 3 dB, where the associated complexity was quantified in terms of the number of complex additions and multiplications imposed by the different MUDs on a peruser basis
Summary
Multiinput-Multioutput Orthogonal Frequency Division Multiplexing (MIMO-OFDM) [1] is considered as candidates for future 4G broadband wireless services. In this paper we propose two computationally efficient metaheuristic algorithms based on ABC [7,8,9,10,11] and PSO [12,13,14,15] for multiuser detection in SDMA-OFDM systems, which provide an effective solution to the multiuser MIMO detection problem in the above-mentioned high-throughput rank-deficient scenario. Our major contributions in this paper are (i) the development of two relatively accurate, computationally efficient metaheuristic algorithm suitable for multi user detection in SDMA-OFDM system; (ii) a thorough analysis of the performance of the proposed algorithms under both fully loaded and overloaded scenario; (iii) computational complexity comparison of the proposed algorithms with existing MUDs such as ML and MMSE.
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