Hoang-Yang Lu

Joint Transmit/Receive Antenna Selection in MIMO Systems Based on the Priority-Based Genetic Algorithm

In this letter, a novel genetic algorithm (GA) for joint transmit and receive antenna selection in multiple-input-multiple-output (MIMO) systems is presented. The new GA employs a priority mechanism in the crossover and mutation operations in the evolution process. Computer simulations show that the proposed GA can achieve close performance to the optimum algorithm but with much lower computational complexity.

Soft information assisted space-time multiuser detection for highly loaded CDMA

This letter presents an effective space-time multiuser detector (MUD) with the assistance of soft information in multipath code division multiple access (CDMA) channels. The space-time MUD considered is a simple, separable spatial-temporal filter which consists of a single spatial filter and a single temporal filter. Based on the soft-decision outputs determined in the previous iteration, the soft information is then exchanged in the alternating updates of either the spatial filters or the temporal filters. Furnished simulations show that the proposed scheme can offer substantial performance improvement compared with previous works, especially in highly loaded scenarios.

Joint receive antenna selection and symbol detection for MIMO systems: a heterogeneous genetic approach

This letter presents a joint scheme of receive antenna selection and symbol detection for multiple-input,multiple output (MIMO) systems based on the maximum likelihood (ML) criterion. To mitigate the computational complexity, a novel variant of the genetic algorithm (GA) is addressed to solve the nonlinear optimization involved, where a new heterogenous crossover and a new heterogenous mutation are conducted in the chromosome evolution process. Furnished simulations show that the new approach provides superior performance with substantially lower computational load compared with previous works in both correlated and uncorrelated channels.

Iterative Multiuser Detection with Soft Interference Cancellation for Multirate MC-CDMA Systems

This paper presents an effective multi-rate multiuser detector (MUD) for the uplink of single-input multiple- output (SIMO) multi-carrier code division multiple access (MC- CDMA) systems. The MUD considered is an iterative receiver which utilizes the soft information to refine the estimation of the interference to enhance the interference cancellation capability. More specifically, users with different transmission rates are classified into separate groups and, in each iteration, these groups of users are detected sequentially based on a set of minimum mean-squared error (MMSE) group detectors with the removal of multiple access interferences (MAI) group by group. Furthermore, the estimated interferences in each group, either from the same or the other groups, are refined successively with the assistance of the soft information in the symbol detection process. Conducted simulations show that the proposed MUD, with moderate computational overhead, can effectively suppress the MAI to render superior performance compared with previous works.

Joint Generalized Antenna Combination and Symbol Detection Based on Minimum Bit Error Rate: A Particle Swarm Optimization Approach

In order to reduce hardware cost and achieve superior performance in multi-input multi-output (MIMO) systems, this paper proposes a novel scheme for joint antenna combination and symbol detection. More specifically, the new approach simultaneously determines the transformation weighting for antenna combination to lower the RF chains called for and to design the minimum bit error rate (MBER) detector to effectively mitigate the impairment due to interference. The joint decision statistic, however, is highly nonlinear and the particle swarm optimization (PSO) algorithm is employed to reduce the computational overhead. Conducted simulation results show that the new approach yields satisfactory performance with reduced computational overhead compared with pervious works.

Joint frequency offset estimation and multiuser detection using genetic algorithm in MC-CDMA

In order to combat intercarrier interference (ICI) and multiple access interference (MAI) simultaneously to achieve reliable performance in multi-carrier code division multiple access (MC-CDMA) systems, the paper proposes a new scheme for joint frequency offset estimation and multiuser symbol detection. The new approach is based on the widespread maximum likelihood principle to carry out concurrently frequency offset estimation to alleviate the ICI and multiuser detection to mitigate the MAI. The joint decision statistic, however, is highly nonlinear and conventional linear schemes are not applicable. To reduce the computational complexity without an increase of additional mechanisms, we employ a genetic algorithm (GA) to solve the nonlinear optimization involved. Due to the robustness of the GA, the joint decision statistic can be efficiently solved and near optimum results can be obtained. Simulation results show that the proposed approach offers satisfactory performance in various scenarios.

Decision aided MMSE-SIC multiuser detection for DS-CDMA systems

This work presents a hybrid of the minimum mean square error (MMSE) multiuser detection (MUD) and successive interference cancellation (SIC) in conjunction with an information reuse scheme for direct-sequence code division multiple access (DS/CDMA) systems. The hybrid MUD first divides the users into groups with each group consisting of users with a close power level. The SIC is then used to distinguish users among different groups, while the MMSE MUD is used to detect signals within each group. T further improve the performance impaired by the propagation errors, a decision feedback scheme is added to attain more precise reconstructed outputs. Furthermore, a detailed performance analysis is conducted to provide further insights into the new approach. Furnished simulations show that the performance of the new MUD is very close to that of the MMSE MUD but with substantially lower computational complexity.

Efficient groupwise multiuser detection with iterative soft interference cancellation for multi-rate MC-CDMA

This paper presents an effective multiuser detector (MUD) for the uplink of multi-rate multi-carrier code division multiple access (MC-CDMA) systems. The MUD considered is an iterative receiver which utilizes the soft information to refine the estimation of the interference to enhance the interference cancellation capability. More specifically, users are first classified into separate groups according to their transmission rates. In each iteration, these groups of users are detected sequentially based on a set of group detectors with the removal of multiple access interferences (MAI) group by group, where the estimated interferences in each group, incurred from the users either in the same rate group or in the other rate groups, are refined successively with the assistance of the soft information in the symbol detection process. Moreover, for practical low-complexity implementations, the users in each group are further partitioned into smaller subgroups based on their effective channel correlations and then detected in parallel by a bank of minimum mean-squared error (MMSE) soft detectors to further reduce the computational load. Conducted simulations show that the proposed MUD can effectively suppress the MAI to render superior performance but with reduced computations compared to previous works.

A cross decision feedback gsc-based capon multiuser receiver for space-time block coded CDMA systems

This paper proposes a simple, yet effective generalized sidelobe canceller (GSC)-based Capon multiuser receiver for the Alamouti space-time block coded (STBC) multiple-input multiple-output code-division multiple-access (MIMO CDMA) systems. The new receiver makes full use of the space diversity provided by the antenna array and the time diversity provided by the decision feedback (DF) from the outputs of both of GSCs employed along with the transmit diversity induced in the Alamouti STBC to render superior performance. With an ingenious DF scheme, refer to as the the cross DF (CDF), the desired signals will be blocked more thoroughly after the blocking matrix so that the interference suppression capability can be further enhanced. Performance analysis is also provided to show that that the minimum mean squared error (MMSE) of the receiver using the CDF is indeed lower than those with or without the classical DF scheme. Conducted simulations show that the new receiver can not only provide superior performance compared with previous works, but it can also render faster convergence characteristics.

Joint Generalized Antenna Combination and Symbol Detection Based on Minimum Bit Error Rate : A Particle Swarm Optimization Approach

In order to reduce hardware cost and achieve superior performance in multi-input multi-output (MIMO) systems, this paper proposes a novel scheme for joint antenna combination and symbol detection. More specifically, the new approach simultaneously determines the transformation weighting for antenna combination to lower the RF chains called for and to design the minimum bit error rate (MBER) detector to effectively mitigate the impairment due to interference. The joint decision statistic, however, is highly nonlinear and the particle swarm optimization (PSO) algorithm is employed to reduce the computational overhead. Conducted simulation results show that the new approach yields satisfactory performance with reduced computational overhead compared with pervious works.