A new hybrid heuristic multiuser detector for DS-CDMA communication systems (original) (raw)
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GA, SA, and TS near-optimum multiuser detectors for s/MIMO MC-CDMA systems
2008 Fourth International Conference on Wireless Communication and Sensor Networks, 2008
This paper analyzes the performance and complexity of four heuristic approaches applied to a synchronous multicarrier multiuser detection (MuD) of single/multiple transmit antennas and multiple receive antennas code division multiple access (S/MIMO MC-CDMA) system. The genetic algorithm (GA), simulation annealing (SA) and Tabu search (TS) heuristic algorithms (HA) in a single-objective optimization form were considered. Monte-Carlo simulations showed that the performances, after convergence, achieved by the four near-optimum HA-MuD S/MIMO MC-CDMA are identical. However, their computational complexities differ depending on the operation system conditions. Therefore, the HA-MuD complexities were carefully analyzed in order to determine which one has the best trade-off between bit error rate (BER) performance and implementation complexity aspects.
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Lecture Notes in Computer Science, 2005
Due to the demand for cellular wireless services, recent interests are in techniques, which can improve the capacity of CDMA systems. On such technique is multi-user detection. Multi-user Detection (MUD) is the intelligent estimation/demodulation of transmitted bits in the presence of Multiple Access Interference (MAI). In this paper, we will show the role of matched filter used as pre-processing tool for MUD in DS-CDMA system.
A low complexity MMSE multiuser detector for DS-CDMA
Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256), 2001
The optimal receiver for detecting direct sequence code division multiple access (DS-CDMA) signals suffers from computational complexity that increases exponentially with the number of users. Several suboptimal multiuser detectors (MUDs) have been proposed to overcome this problem. Due to the nonlinear nature of the decision boundary of the optimal receiver, it is known that nonlinear receivers outperform linear receivers. Radial basis function (RBF) MUD is a nonlinear suboptimal receiver that can perfectly approximate this decision boundary and it needs no training since it is fully determined when the spreading codes of all users and the channel impulse response (CIR) are known. However, the RBF MUD suffers from structural complexity since the number of hidden nodes (center functions) in its structure increases exponentially with the number of users. In this study, we propose a new method to minimize the number of center functions of the RBF MUD using a genetic algorithm (GA) and the least mean squares (LMS) algorithm. With simulations performed in AWGN and multipath channels it is shown that the proposed method immensely reduces the complexity of the RBF MUD with a negligible performance degradation.
International Journal of Computer Applications, 2013
In this paper, a non iterative algorithm for MUD in DS-CDMA system is proposed. The proposed multiuser algorithm is performed based on harmony search algorithm. In the proposed algorithm, a new harmony memory updating is based on the random and mean operation. So, the proposed harmony search algorithm is reduced the complexity and the user information interference. Hence, the bit error rate of the transmitted code reduced. In the enhanced harmony search algorithm, the marginal distribution for each observed and unobserved node are calculated. The proposed multiuser detection algorithm is applicable in run time user identification process, so the MUD complexity and the required time are concentrated. Also, the iteration can be predefined based on the number of users, signal interference and signal to noise ratio. This improves the multiuser efficiency, reduce the information losses and power corruption in CDMA channel. The proposed technique is implemented in MATLAB and the performance is evaluated.
Input Parameters Optimization in Swarm DS-CDMA Multiuser Detectors
2010
In this paper, the uplink direct sequence code division multiple access (DS-CDMA) multiuser detection problem (MUD) is studied into heuristic perspective, named particle swarm optimization (PSO). Regarding different system improvements for future technologies, such as high-order modulation and diversity exploitation, a complete parameter optimization procedure for the PSO applied to MUD problem is provided, which represents the major contribution of this paper. Furthermore, the performance of the PSO-MUD is briefly analyzed via Monte-Carlo simulations. Simulation results show that, after convergence, the performance reached by the PSO-MUD is much better than the conventional detector, and somewhat close to the single user bound (SuB). Rayleigh flat channel is initially considered, but the results are further extend to diversity (time and spatial) channels.
Speed and Accuracy Comparison of Techniques for Multiuser Detection in Synchronous CDMA
IEEE Transactions on Communications, 2004
In this letter, we compare the complexity and efficiency of several methods used for multiuser detection in a synchronous code-division multiple-access system. Various methods are discussed, including decision-feedback (DF) detection, group decision-feedback (GDF) detection, coordinate descent, quadratic programming with constraints, space-alternating generalized EM (SAGE) detection, Tabu search, a Boltzmann machine detector, semidefinite relaxation, probabilistic data association (PDA), branch and bound (BBD), and the sphere decoding (SD) method. The efficiencies of the algorithms, defined as the probability of group detection error divided by the number of floating point computations, are compared under various situations. Of particular interest is the appearance of an "efficient frontier" of algorithms, primarily composed of DF detector, GDF detector, PDA detector, the BBD optimal algorithm, and the SD method. The efficient frontier is the convex hull of algorithms as plotted on probability of error versus computational demands axes: algorithms not on this efficient frontier can be considered dominated by those that are.
A Near-Optimal Multiuser Detector for MC-CDMA systems Using Geometrical Approach
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2005
An efficient sub-optimal algorithm, called HIS (Hyperplane Intersection and Selection) detection algorithm, is proposed to solve the problem of joint detection of K users in a MC-CDMA system. Compared to the existing solutions, the proposed algorithm has three characteristics very attractive for pratical systems. Firstly, it has nearly optimal performance. Secondly, it has a low computational complexity (O(K 2 ) multiplications and O(K 3 ) additions). Third, the algorithm has an inherent parallelism. To our knowledge, the HIS algorithm is not just an add-on to a previous existing algorithm but a rather new decoding technic based on a singular value decomposition of the channel matrix H. After giving the equation of the MC-CDMA multi-user detection problem, the HIS algorithm is described. Its performance is compared to known existing algorithms (ZF, MMSE, PIC and Sphere Decoding). For a BER as low as 10 −4 , the HIS algorithm introduces only 0.2 dB degradation compared to the optimal Sphere Decoding algorithm for K = 16 users againt 3.8 dB for the PIC (with two MMSE stages) algorithm.
Multiple access interference (MAI) limits the capacity of Direct sequence Code Division Multiple Access (DS-CDMA) systems. In CDMA systems MAI is considered as additive noise and matched filter bank is employed. Traditionally, multiuser detectors __ a code matched and a multiuser linear filter are used which increases the complexity of the system due to its nature of operation. Multiuser detection is an approach which uses both these filters for the optimization. However, the main drawback of the multiuser detection is one of the complexity so that suboptimal approaches are being sought. Much of the present research is aimed at finding an appropriate tradeoff between complexity and performance. These suboptimal techniques have linear and non-linear algorithms. In this work, we introduce Successive Interference Cancellation (SIC) which is a nonlinear suboptimal method of MUD and is based upon successively subtracting off the strongest remaining signal. Further analysis is to be carried out and simulations to be done for better understanding of SIC.