Roslina Mohamad

Maximizing Network Lifetime with Energy Efficient Routing Protocol for Wireless Sensor Networks

In the research field of Wireless Sensor Networks, how to reduce the energy consumption of WSN so that the lifetime of WSN can be prolonged is one of the hottest spots. Wireless sensor networks (WSN) lifetime is either superficial or impractical, which prevents us from thoroughly understanding the efficiency of these proposed routing protocols. Routing protocols have significant impact on the overall energy consumption of sensor networks. This project present variety of maximizing system lifetime wireless sensor networks with different energy consumption. Energy consumption for three routing protocols had been analyzed which are direct communication, minimum transmission energy and low adaptive energy clustering hierarchy. The energy consumption for Low Energy Adaptive Clustering Hierarchy (LEACH) routing protocol give the maximum lifetime compared to the others. Clustering is an energy efficient and scalable way to organize the WSN. The main objective of this research is to maximize the lifetime of the wireless sensor (WSN). Simulation via Matlab shows that by applying energy consumption for LEACH routing protocol had increase the network lifetime by as much as 65.2% compared to DC and MTE.

Evaluation of Stable Cluster Head Election (SCHE) routing protocol for Wireless Sensor Networks

Wireless sensor networks (WSN) will enable the reliable monitoring of a variety environment for both civil and military applications. Routing protocols have significant impact on the overall energy dissipation of sensor networks. This project present the development of an energy efficient routing protocol which consumes significantly less power compared to existing routing protocol for wireless sensor network. The design was developed based on low energy adaptive clustering hierarchy (LEACH) routing protocol. Clustering is an energy efficient and scalable way to organize the WSN. The main objective is to minimize the energy dissipation of each sensor node and reduces the energy dissipation for the whole network. Stable cluster head election (SCHE) analyzes the cluster head selection to find the optimal probability of becoming a cluster head. Simulation of Matlab shows that this design reduces communication energy by as much as 95% compared to LEACH, due to stable cluster head election.

Implementation of M-ary Phase Shift Keying (PSK) baseband modem on Texas instrument digital signal processor TMS320C6713

This paper presents the implementation of Phase Shift Keying (PSK) baseband modem on Digital Signal Processor (DSP). Different level of PSK modulation schemes were used which were 16-psk, 32-psk, 64-psk, 128-psk and 256-psk. MATLAB simulink software was used in this project to simulate the system. The system model consisted of modulator, demodulator, noise channel and channel coding. Noise channel that was used in the system is Addittive White Gaussian Noise (AWGN). After the simulation, a Matlab file was created to get the Bit Error Rate (BER) graph for all 6 level of modulation scheme. Then, the system was implemented on the DSP TMS320C6713 board. From the simulation, the result that was obtained was constellation point for all M-ary PSK before and after adding channel coding and AWGN. The BER graph that was obtained also follows the theory.

Performance analysis of convolutional interleaver on TMS320C6711 Digital Signal Processing Kit

The work presented in this paper is aimed at designing an optimized convolutional interleaver for realtime application using Digital Signal Processor. Interleaving is a simple and effective means to improve the performance of an error correction scheme on a bursty channel. Convolutional interleaver is considered as one of the best option for researchers besides of block and helical interleaver. In non-real-time application, there have been many examples or simulations of convolutional interleaver, written in C language but the problem is, most of them requires many loops to execute and hence, cause timing problem. Thus, this is not suitable for real-time application. Therefore, this research proposed the solutions to the latency problem by satisfying several requirements simultaneously: 1) using DSP-BIOS Scheduling module such as SWI and PIPE to increase performance and make sure sample data are in packed, 2) removing loop algorithm in interleaver function with look-up table method and 3) using compiler optimization that was provided in Code Composer Studio. Finally, the optimized codes are implemented on TMS320C6711 DSK and the codes performances are collected through DSP/BIOS analysis modules. From the implementation results, it shows that the proposed algorithm promising a good performance compare to the original algorithm in terms of speed and memory size.

Robustness analysis of the improved minimum descriptive length stopping criterion

Most of the turbo decoding stopping criteria assume perfect channel reliability available at the receiver since they require a threshold based on signal-to-noise ratio (SNR) information. However, operational environments can vary according to frame sizes, code structures and channel reliability requirements, further aggravating the difficulty in threshold determination and convergence or non-convergence detection. This paper aims to provide a robustness analysis of improved minimum descriptive length (IMDL) stopping criterion peculiar to these factors: the frame sizes, the channel reliability requirements, the code structures, and the code rate. The robustness analysis is benchmarked to the well-known Genie stopping criterion based on the average iteration number (AIN) and bit error rate (BER) performance.

Enhanced Cross-Entropy Based Stopping Criteria at Low Signal-to-Noise Ratio Regions

This paper presents an enhancement of Cross-Entropy (CE)-based stopping criteria at a low signal-to-noise ratios (SNRs) region. The existing CE-based stopping criteria fail to stop the iteration and cause the maximum iteration at low SNRs. Intuitively, this work enhances the CE stopping criterion by combining with the Average-Entropy (AE) stopping criteria. The work also proposes a set of a stopping rule to distinguish the SNR between low and high region. These approaches are then thoroughly analyses in terms of the required average iteration number (AIN), as well as its bit-error-rate (BER) performance. The simulation results show that the enhanced CE able to reduce the AIN compared to existing CE-based stopping criteria while the BER is maintained. Hence, the enhanced CE-based stopping criterion make the decoder more efficient, in terms of reduction in the time delay while increasing turbo codes performance.

Enhancement of cross-entropy based stopping criteria via turning point indicator

Cross-entropy (CE) based stopping criteria is known for its early termination capability of the turbo decoding iterations without scarifying its performance, in terms of bit error rate (BER). This advantage, however, performs well in high signal-to-noise ratio (SNR) albeit requiring infinite iterations at low SNR, thereby resulting in more unwanted computations and decoding delays. In this paper, a simple turning point (TP) measurement from the BER and average iteration number (AIN) graphs of the Genie stopping criterion has been introduced. The motivation is twofold; to terminate the iteration at the early stage in low SNR and maintaining the same level of performance of the existing method in high SNR, by using the proposed TP measurement. From the simulation results, the enhanced CE-based stopping criteria improve the early termination in low SNR and maintain the BER performance for various frame sizes compared to existing stopping criteria.

Threshold-Based Bit Error Rate for Stopping Iterative Turbo Decoding in a Varying SNR Environment

Abstract Online bit error rate (BER) estimation (OBE) has been used as a stopping iterative turbo decoding criterion. However, the stopping criteria only work at high signal-to-noise ratios (SNRs), and fail to have early termination at low SNRs, which contributes to an additional iteration number and an increase in computational complexity. The failure of the stopping criteria is caused by the unsuitable BER threshold, which is obtained by estimating the expected BER performance at high SNRs, and this threshold does not indicate the correct termination according to convergence and non-convergence outputs (CNCO). Hence, in this paper, the threshold computation based on the BER of CNCO is proposed for an OBE stopping criterion (OBEsc). From the results, OBEsc is capable of terminating early in a varying SNR environment. The optimum number of iterations achieved by the OBEsc allows huge savings in decoding iteration number and decreasing the delay of turbo iterative decoding.

An efficient constructive heuristic for optimizing frequency allocation in cellular network

Managing resources in wireless communication is a crucial task to ensure demand is satisfied at a minimal operational cost. This includes managing constraints such as co-frequency, adjacent frequency and co-site so that interference is avoided. Any occurrence of interference will affect the quality of communication conducted between parties involved. Therefore, a good and efficient method is required to achieve this objective. In this paper, a simple randomized constructive heuristic was investigated for good quality solutions. The proposed method was utilized on new problem instances; varying in difficulties and complexity environment. Two hundred problem instances were generated for this purpose. The results obtained demonstrate the efficiency of the proposed method on this problem domain.

On the performance of SVD estimation in Saleh-Valenzuela channel for UWB system

This paper describes the performance of singular value decomposition (SVD) estimation techniques for multiband orthogonal frequency-division multiplexing (OFDM) of ultra-wideband (UWB) system in Saleh-Valenzuela channel modelling. The performance of SVD estimation is compared against LS and MMSE methods corresponding to zero-padded of a UWB system. The crucial limitation in UWB system is strictly low power transmission leads to many challenges in designing the system. However, most of the conventional channel estimation in frequency domain requires either pre-storing a large matrix or performing real-time matrix inversion, which should be avoided for UWB low complexity implementation. The intuition of this paper is to analyse further the complexity of SVD techniques against least squares (LS) and minimum mean square error (MMSE) estimation method. Consequently, this work implies that the SVD method gives an improvement of 3-5 dB if compared to the LS method while a significant complexity reduction of 57.8% as compared to MMSE methods.