Cooperative relaying exploits the broadcast nature of wireless channel and extracts spatial diversity in distributed manner. In this paper, we investigate the performance of an infrastructure-based multi-antenna relay network in absence of direct link. A closed-form expression of outage probability has been derived when the cooperating relays coherently combine the received signals and destination select the best copy of the received signals. The effect of number of relay antennas and relay placement on the system performance has also been studied.

This paper proposes a harmonic elimination technique for online reducing harmonics in voltage source inverters. In the presented method, in order to provide required fundamental voltage and eliminate specified harmonics simultaneously, the value of the switching angles are determined using a new efficient optimization algorithm named Enhanced Teaching-learning-based Optimization (ETLBO). The efficiency of the presented strategy is validated on three-phase seven-level diode-clamped inverter while other structures of multi-level inverters (MLIs) can be employed. The aim is to reduce the Total Harmonic Distortion (THD) in multilevel converter. In this paper, a new optimization algorithm named ETLBO has been successfully implemented to achieve optimal switching angles in order to harmonic elimination in MLIs. A three-phase seven-level diode-clamped MLI has been selected as a test case to validate the effectiveness of the proposed method. The simulation results demonstrated the ETLBO method not only is in preference to the Genetic Algorithm and Particle Swarm Optimization for including no user-defined parameter and simple implementation, but also for providing higher quality solutions. Moreover, in order to verify the superiority of the ETLBO algorithm over conventional methods for harmonic elimination, the Newton-Raphson (NR) method was implemented to find optimal switching angles. The results obtained by the NR method compared with those of the ETLBO and the superiority of the ETLBO in terms of the both computational time and the resulted %THD was concluded. As a whole, the results show that the ETLBO algorithm is expected to become widespread in power systems where on-line updating harmonics is needed since it provide accurate and high-quality solution in extremely short time.

Sequence alignment is a computationally expensive activity in bioinformatics that can benefit significantly from Field Programmable Gate Array-based high-performance computing systems. This paper evaluates the performance of such systems for bioinformatics sequence alignment applications considering various parameters like data bus width (W), the number of processing elements, and the maximum operating frequency.

In this paper, we present novel schemes for video quality maximization in the context of H.264 scalable video coding-based 4G wireless broadcast and multicast video transmission to heterogeneous multimedia wireless clients. In the first part, we address the issue of optimal frame rate allocation when the multimedia server is constrained by the processing overheads required for tasks such as video encoding, bit-stream extraction, packetization, etc. We demonstrate that the above problem of perceptual quality maximization is well represented by a constrained optimization framework. Based on the system model, we present a closed-form solution for frame rate allocation and a comprehensive algorithm for sum quality maximization. In the second part, we propose a novel rate partitioning-based optimal scalable video (RPSV) transmission framework. A typical wireless multicast group comprises of multimedia clients with varying wireless link qualities. Conventional multicast video transmission is constrained by the broadcast/multicast group (BMG) subscriber with the worst link capacity. Hence, we propose the RPSV scheme for optimal partitioning of the multicast group for transmission of the H.264-coded base and enhancement scalable video layers. We demonstrate that the optimal wireless link quality-based BMG partition and the associated quantization, time-fraction parameters can be computed by solving a series of convex objective minimization problems and derive a closed-form solution for the convex problem at each step. We compare the results obtained using the above mentioned optimal frame rate allocation and quantization parameter selection schemes with the results obtained using conventional schemes and demonstrate the superiority of the proposed algorithms in both unicast and multicast scenarios.

This paper proposes a robust H-infinity control strategy for a differential drive Tractor with a single Trailer unit. This articulated vehicle being a complicated non holonomic system, the number of control inputs is less compared to the number of generalized coordinates. A linearized nominal model for this system is obtained by combining the kinematics and dynamics. A robust H-infinity output feedback control is designed using mu synthesis for the nominal plant when subjected to model uncertainties in unstructured form and output disturbances. Analysis on the robust uncertain closed-loop system is performed in both time and frequency domains. The simulation results indicating satisfactory stability and performance are presented. The step response and reference tracking are also found to be satisfactory.

Rapid advancement in the world of microprocessor necessitates solving the bus contention in a most efficient manner. The major challenge is to reduce the latency of the system and to achieve a fair bandwidth allocation using maximum CPU utilization. Combination of Adaptive Arbitration (AA) algorithm and the processors according to their traffic behavior can be one of the feasible options to tackle the aforesaid problems due to its fair bandwidth allotment and low system latency. This article provides a comprehensive picture of the global scenario of AA algorithm for fair bandwidth allocation so as to enable researchers to decide the direction of further investigation. Some of the works published so far in this area are reviewed, classified according to their objectives, and presented in an organized manner with general conclusion.

In general, most of the Biomedical signals such as Electrocardiogram (ECG), Electroencephalogram, and Electro-oculogram are nonstationary signals, suffers from different interferences like power line interference (PLI) and with other biomedical signals that gets added with it. Analysis of these signals means the extraction of useful information from the signal, and in this paper it is carried out using a new nonlinear and nonstationary data analysis method called Empirical Mode Decomposition (EMD). The key feature of this method is that it can decompose the signal into different IMFs and makes the analysis simple. Compared with other tools like Fourier analysis and wavelet methods, EMD is purely a data-driven and adaptive technique. Thus, it is well suited to analyze nonstationary signals like biosignals. This paper foregrounds an EMD-based, two-weight adaptive filter structure to reduce the PLI in ECG signals. Two methodologies are studied based on EMD and the simulations are carried out in a MATLAB environment. The denoised signals are visually impressive and the methodologies are well suited for real-time implementation.

In this paper, a random bit sequence generator based on chaotic maps is introduced and implemented. In this generator, two chaotic map functions with two different keys are used. The Bifurcation diagram is used to calculate the initial state of the chaotic maps in order to produce the output random bit sequence. Chaotic Logistic and Tent maps classically are defined in an analogue space. In order to implement these chaotic maps on a hardware digital platform, these chaotic maps are modified. Digital chaotic Logistic and Tent maps are introduced. A design for implementation of these modified chaotic maps is also presented. The output bits of two chaotic maps are EX-ORed to produce a random sequence of 1 000 000 bits. These designs are implemented on Field Programmable Gate Array, and the results are reported. The proposed designs are tested by producing 100 samples of 1 000 000 bits, and they pass the standard Federal Information Processing Standard 140-1 and National Institute of Standards and Technology statistical tests for random bit generators.

The inherent sensitivity of orthogonal frequency division multiplexing (OFDM) systems to any frequency shift in the signal makes their design very challenging. In OFDM systems, the frequency shift may be due to instability of transmitter/receiver oscillators or because of fading channel. The frequency shift in the signal destroys the orthogonality among subcarriers and results in intercarrier interference (ICI), which affects the system performance severely. A number of solutions are available to mitigate the effect of ICI. The existing ICI mitigation techniques include frequency equalization, time domain windowing, ICI self-cancellation, coding, etc., Among several ICI reduction methods, ICI self-cancellation scheme has received much attention due to its simplicity. The ICI mitigation schemes that depend on carrier frequency offset (CFO) correction at the transmitter are effective under high signal-to-noise ratio (SNR) scenario and those that depend on CFO estimation and correction at the receiver have additional computational complexity and some sort of data symbol redundancy. In this paper, a bandwidth-efficient ICI reduction method for M-ary QAM signals is proposed. The present method is effective in low SNR environment. This method reduces the effect of ICI and improves the performance of the system in terms of bit error rate. It is shown that the proposed ICI cancellation method considerably outperforms the existing ICI self-cancellation schemes in the presence of small CFO while maintaining the throughput level.