Weighting Particle Swarm Optimization SIMO MC-CDMA Multiuser Detectors

Abstract-This paper analyzes the performance of two heuristic approaches applied to a synchronous multicarrier multiuser detection (MUD) of multiple receive antennas code division multiple access (SIMO MC-CDMA) system. The particle swarm optimization (PSO) with weighting particle position based on combining multi-fitness functions (woPSO) is proposed and compared with the conventional PSO SIMO MC-CDMA. The woPSO strategy deal with the multi-objective dilemma imposed by the spatial diversity that results in independent likelihood function for each receive antenna. Additionally, the computational complexity of these algorithms was taken into account in order to show which one has the best trade-off in terms of performance and implementation complexity aspects. Index Terms-MC-CDMA, multiuser detection, particle swarm optimization, single/multiple-objective optimization

A Linear Multi-User Detector for STBC MC-CDMA Systems based on the Adaptive Implementation of the Minimum-Conditional Bit-Error-Rate Criterion and on Genetic Algorithm-assisted MMSE Channel Estimation

The implementation of efficient baseband receivers characterized by affordable computational load is a crucial point in the development of transmission systems exploiting diversity in different domains. In this paper, we are proposing a linear multi-user detector for MIMO MC-CDMA systems with Alamouti’s Space-Time Block Coding, inspired by the concept of Minimum Conditional Bit-Error-Rate (MCBER) and relying on Genetic-Algorithm (GA)-assisted MMSE channel estimation. The MCBER combiner has been implemented in adaptive way by using Least-Mean-Square (LMS) optimization. Firstly, we shall analyze the proposed adaptive MCBER MUD receiver with ideal knowledge of Channel Status Information (CSI). Afterwards, we shall consider the complete receiver structure, encompassing also the non-ideal GA-assisted channel estimation. Simulation results evidenced that the proposed MCBER receiver always outperforms state-of-the-art receiver schemes based on EGC and MMSE criterion exploiting the same degree of channel knowledge (i.e. ideal or estimated CSI)

Multi-user detection for multi-carrier communication systems

Doctor of PhilosophyDepartment of Electrical and Computer EngineeringBalasubramaniam NatarajanWireless broadband communications is a rapidly growing industry. New enabling technologies such as multi-carrier code division multiple access (MC-CDMA) are shaping the future of wireless systems. However, research efforts in improving MC-CDMA receiver performance have received limited attention and there is a need for innovative receiver designs for next generation MC-CDMA. In this thesis, we propose novel multi-user detection (MUD) schemes to enhance the performance of both synchronous and asynchronous MC-CDMA. First, we adapt the ant colony optimization (ACO) approach to solve the optimal MUD problem in MC-CDMA systems. Our simulations indicate that the ACO based MUD converges to the optimal BER performance in relatively few iterations providing more that 95% savings in computational complexity. Second, we propose a new MUD structure specifically for asynchronous MC-CDMA. Previously proposed MUDs for asynchronous MC-CDMA perform the detection for one user (desired user) at a time, mandating multiple runs of the algorithm to detect all users' symbols. In this thesis, for the first time we present a MUD structure that detects all users' symbols simultaneously in one run by extending the receiver's integration window to capture the energy scattered in two consecutive symbol durations. We derive the optimal, decorrelator and minimum mean square error (MMSE) MUD for the extended window case. Our simulations demonstrate that the proposed MUD structures not only perform similar to a MUD that detects one user at a time, but its computational complexity is significantly lower. Finally, we extend the MUD ideas to multicarrier implementation of single carrier systems. Specifically, we employ the novel MUD structure as a multi-symbol detection scheme in CI-CDMA and illustrate the resulting performance gain via simulations

A universal space-time architecture for multiple-antenna aided systems

In this tutorial, we first review the family of conventional multiple-antenna techniques, and then we provide a general overview of the recent concept of the powerful Multiple-Input Multiple-Output (MIMO) family based on a universal Space-Time Shift Keying (STSK) philosophy. When appropriately configured, the proposed STSK scheme has the potential of outperforming conventional MIMO arrangements

Program of the 3rd International Conference on Signal Processing and Communication Systems, Omaha, Nebraska, 28-30 September 2009

10 sessions; 2 poster sessions. Schedule and Table of Contents

Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years

Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions

On Development of Some Soft Computing Based Multiuser Detection Techniques for SDMA–OFDM Wireless Communication System

Space Division Multiple Access(SDMA) based technique as a subclass of Multiple Input Multiple Output (MIMO) systems achieves high spectral efficiency through bandwidth reuse by multiple users. On the other hand, Orthogonal Frequency Division Multiplexing (OFDM) mitigates the impairments of the propagation channel. The combination of SDMA and OFDM has emerged as a most competitive technology for future wireless communication system. In the SDMA uplink, multiple users communicate simultaneously with a multiple antenna Base Station (BS) sharing the same frequency band by exploring their unique user specific-special spatial signature. Different Multiuser Detection (MUD) schemes have been proposed at the BS receiver to identify users correctly by mitigating the multiuser interference. However, most of the classical MUDs fail to separate the users signals in the over load scenario, where the number of users exceed the number of receiving antennas. On the other hand, due to exhaustive search mechanism, the optimal Maximum Likelihood (ML) detector is limited by high computational complexity, which increases exponentially with increasing number of simultaneous users. Hence, cost function minimization based Minimum Error Rate (MER) detectors are preferred, which basically minimize the probability of error by iteratively updating receiver’s weights using adaptive algorithms such as Steepest Descent (SD), Conjugate Gradient (CG) etc. The first part of research proposes Optimization Techniques (OTs) aided MER detectors to overcome the shortfalls of the CG based MER detectors. Popular metaheuristic search algorithms like Adaptive Genetic Algorithm (AGA), Adaptive Differential Evolution Algorithm (ADEA) and Invasive Weed Optimization (IWO), which rely on an intelligent search of a large but finite solution space using statistical methods, have been applied for finding the optimal weight vectors for MER MUD. Further, it is observed in an overload SDMA–OFDM system that the channel output phasor constellation often becomes linearly non-separable. With increasing the number of users, the receiver weight optimization task turns out to be more difficult due to the exponentially increased number of dimensions of the weight matrix. As a result, MUD becomes a challenging multidimensional optimization problem. Therefore, signal classification requires a nonlinear solution. Considering this, the second part of research work suggests Artificial Neural Network (ANN) based MUDs on thestandard Multilayer Perceptron (MLP) and Radial Basis Function (RBF) frameworks fo