Jenn-Kaie Lain

Near-MLD MIMO Detection Based on a Modified Ant Colony Optimization

In wireless multiple-input multiple-output (MIMO) systems, maximum-likelihood detection (MLD), is impractical because it requires an exhaustive search. This letter formulates MIMO MLD as a pathfinding problem shows it can be solved using a modified ant colony optimization. Simulation results demonstrate that the proposed method achieves near-MLD performance with low computational complexity.

Joint Transmit/Receive Antenna Selection for MIMO Systems: A Real-Valued Genetic Approach

This study proposes a new antenna selection (AS) method using the real-valued genetic algorithm (RVGA) to improve the channel capacity of multiple-input/multiple-output (MIMO) systems. By defining a score function based on channel capacity, AS can be formulated as an optimization problem over a multidimensional real space, and solved by implementing the RVGA method. The simulation results show that the performance of the proposed RVGA AS provides approximately the same achievable rates as the optimal exhaustive search (ES) AS, while maintaining a moderate computational load.

PAPR reduction of OFDM signals using PTS: a real-valued genetic approach

The partial transmit sequences (PTS) scheme achieves an excellent peak-to-average power ratio (PAPR) reduction performance of orthogonal frequency division multiplexing (OFDM) signals at the cost of exhaustively searching all possible rotation phase combinations, resulting in high computational complexity. Several researchers have proposed using binary-coded genetic algorithms (BGA) PTS to reduce both the PAPR and computational load. To improve the PAPR statistics of OFDM signals further while still reducing the computational complexity, this paper proposes a new PTS using the real-valued genetic algorithm (RVGA). By defining a cost function based on the amount of PAPR, PTS can be formulated as an optimization problem over a multidimensional real space and solved by implementing the RVGA method. The simulation results show that the performance of the proposed RVGA PTS, along with an extinction and immigration strategy, provides approximately the same PAPR statistic as the exhaustive PTS scheme, while maintaining a low computational load.

Theoretical Analysis and Performance of NC-PRMA Protocol for Multichannel Wireless Networks

In this paper, we analyze the effect of duplexing schemes on the throughput and the average packet dropping probability of a new multichannel wireless access protocol which allows for non-collision packet reservation multiple access with multiple channel (NC-PRMA/MC). NC equal-capacity, orthogonal, traffic channels are shared by M mobile users on the uplink. Transmission attempts on the uplink are made by using time-frequency signaling in every frame, which enables transmission attempts of mobile users to be conveyed to the base station without collisions. Two kinds of duplexing schemes, frequency division duplexing and shared time division duplexing, are considered in the performance analysis. Using a discrete-time Markov chain analysis, we derive the analytic expressions for the average per channel throughput and the average packet dropping probability. Computer simulation results verify the analysis. Analytical evaluation and computer simulation show that NC-PRMA/MC with shared time division duplexing improves the channel capacity, which approaches the theoretical upper bound.

Adaptive neuro-fuzzy power control and rate adaptation for multirate CDMA radio systems

Emerging multimedia services in cellular radio systems introduces a communication scenario with variations in transmission rate and quality of service (QoS) requirement. To tackle this problem, a new application of neuro-fuzzy control to the power control strategy in multirate direct-sequence code-division multiple-access (DS/CDMA) cellular radio systems is introduced in this paper. The simulation results indicate that the neuro-fuzzy power control (NFPC) provides higher average transmission rate, lower probability of unsuccessful transmission, and less outage probability than the previous mechanisms.

On channel estimation of orthogonal frequency-division multiplexing amplify-and-forward cooperative relaying systems

This study investigates channel estimation for amplify-and-forward (AF) relaying systems. For a two-hop relaying system, channel estimation of a relay path (source-relay-destination) with AF relaying is unique because both individual source-to-relay (S-R) and relay-to-destination (R-D) links are necessary at the destination to perform the optimum combination of signals received from the direct path (source-to-destination) and relay path if employing a cooperative diversity transmission. Until now, most literature about channel estimation on relaying systems has focused on the composite channel of the relay path, and not its individual links. Current methods to separate the estimation of both individual links require the relay to either deliver a quantised version of the S-R link estimate through an independent feed-forward channel, or to perform discrete Fourier transform/inverse discrete Fourier transform operations before amplifying the received signals. In this study, the respective channel estimations are done at the destination. First, the destination utilises a relay amble (R-amble) to obtain channel estimation of the R-D link. Next, exploiting the R-D link estimate, a maximum-likelihood estimator is proposed for the S-R link in a decision-directed (DD) way. Simulation results show that the proposed scheme out performs the current relay-assisted methods in most circumstances. In addition, numerical results reveal that the mean-square error can be significantly reduced in a DD way for symbol error rates of interest.

Low-complexity fuzzy filter-assisted turbo equalization for dispersive Rayleigh-fading channels

Turbo equalisation (TEQ) is an iterative detection and decoding technique that has been shown to be successful in mitigating the effects of intersymbol interference (ISI) introduced by partial response modems and by dispersive channels. In this paper, we propose a fuzzy filter-assisted decision-feedback equaliser (DFE)-based TEQ scheme that not only is comparable in performance to the Jacobian radial basis function (RBF) DFE-based TEQ but also is low-complexity. The per iteration computation of both the fuzzy filter DFE TEQ using product inference and maximum defuzzification and the fuzzy filter DFE TEQ using minimum inference and maximum defuzzification is much lower than that of the Jacobian RBF DFE TEQ for binary phase-shift keying (BPSK) modulation, 4 quadrature amplitude modulation (QAM), and 16 QAM. Notably, the computational complexity of the Jacobian RBF DFE TEQ is exponentially related to the feedforward order, but the fuzzy filter DFE TEQ using minimum inference and maximum defuzzification is independent of that. Previous TEQ research has shown that the Jacobian RBF DFE TEQ considerably reduces the computational complexity compared to the logarithmic maximum a posteriori (Log-MAP) TEQ with similar performance. In this present study, the proposed fuzzy filter DFE TEQ further reduces the computational complexity with slight performance degradation in contrast to the Jacobian RBF DFE TEQ. With this, the materialisation of the TEQ scheme becomes more feasible. Copyright

A Low-Complexity Channel Estimator for MIMO-OFDM Systems

In this paper, a low complexity channel estimator for MIMO OFDM systems is proposed. A frequency domain filtering scheme based on the concept of temporal windowing for noise power reduction outside the window is developed to enhance the performance of the simple least square estimator. This approach can eliminate the extra FFT/IFFT operations required in the conventional time domain scheme. A temporal Hamming window is adopted to further reduce the computing complexity of the frequency domain filtering. Simulation results indicate the proposed scheme can significantly improve both the NMSE and BER performance of the LS channel estimator. Compared with the time domain most significant tap (MST) scheme, the proposed scheme has comparable performance but requires much less computing complexity. The proposed scheme also has the advantage in hardware implementation over the MST scheme

Cross‐entropy‐based joint carrier frequency offset estimation and multiuser detection for multicarrier code division multiple access systems

SUMMARY This paper presents a joint carrier frequency offset estimation and multiuser detection based on a maximum likelihood approach in multicarrier code division multiple access systems. With the definition of a score function based on the log-likelihood, the joint carrier frequency offset estimation and multiuser detection can be formulated as a nonlinear optimization problem over the joint of a multidimensional real space and a multidimensional discrete space. To reduce the computational complexity required by the joint decision statistic, while still obtaining a desirable performance, a new method using cross-entropy optimization is proposed to solve the nonlinear optimization problem. Because of the robustness of the cross-entropy optimization, the joint decision statistic can be efficiently solved, and, as shown by the furnished simulation results, the proposed approach can achieve satisfactory performance in various scenarios. Copyright

A modified energy-efficient routing algorithm for wireless sensor networks

Rapid growth in sensor technology and wireless communication has led to the development of wireless sensor networks (WSNs). Due to cost and environment concerns, the battery of sensor is not always rechargeable particularly when the network operates in an inhospitable or hostile field. This study proposed a Lifetime-Extended Uniform Distribution (LEUD) algorithm to provide ubiquitous communication in large-scale networks for a longer duration and a Modified Relative Direction-based Sensor Routing (MRDSR) scheme to solve the routing loop problem in RDSR.