Abdul Hadi Fikri Abdul Hamid

Efficient In-Band Spectrum Sensing Using Swarm Intelligence for Cognitive Radio Network

Spectrum sensing mechanisms enable cognitive radio networks to detect primary users (Upsi) and utilize spectrum holes for secondary user (SU) transmission. However, precise PU detection leads to longer sensing time and lower achievable throughput. In this paper, we propose a particle swarm optimization (PSO)-based scheme for an in-band local spectrum sensing to address the tradeoff between sensing time and throughput. Using methodological analysis, a fast convergence PSO (FC-PSO) scheme is derived by implementing a distribution-based stopping criterion subject to detection performance, optimization time, and SU gain. At the target probability of detection of at least 90%, the results show significant improvements of ~45% for sensing time, 70% for the probability of false alarm, and 12% for achievable throughput compared with nonoptimal sensing scheme at signal-to-noise ratio of 0 dB. FC-PSO also outperforms other optimization schemes in terms of convergence speed. The proposed scheme is proved to be an energy-efficient solution for practical implementation as it outperforms the other algorithms in terms of lower computational complexity as well as providing the best tradeoff values in meeting the objective function of sufficient opportunistic access for an SU under optimized sensing time for maximized throughput, while providing high protection to the PU.

Testbed design for Wireless Biomedical Sensor Network (WBSN) application

In wireless sensor network (WSN), a collection of nodes interacts with each other to gather information from the surveillance area. Some of the applications that WSN are currently being used are habitat monitoring, health care system and building automation, to name a few. Wireless Biomedical Sensor Network (WBSN) allows capturing of physiological signals, continuous monitoring and updating of a patients medical status remotely. This paper focuses on the development of a wireless sensor node testbed for WBSN application which complies with IEEE 802.15.4 standard and operates in 2.4 GHz ISM (industrial, scientific and medical) band. The initial state of WBSN development is the design of the wireless sensor node called TelG. The main features of TelG include low power consumption, wearable, flexible and small size. It is then embedded with a self-built operating system called WiseOS to support customized operations. A pulse oximeter is then integrated with TelG for the purpose of experimentation. The testbed performance is analyzed in terms of packet reception rate (PRR) and end-to-end delay. The results exhibit a decrease in PRR as distance increases and increasing network delay with increasing number of hops. It is also observed that received signal using the testbed is satisfactory for distances less than 10 meters per hop.

Modelling of application-centric IoT solution for guard touring communication network

Internet of Things (IoT) enables advance digital services by utilizing data acquisition and controlling device remotely across wireless network infrastructure. It is a primary catalyst for an increasing numbers of application in the fields of cyber-physical systems. In this project, an IoT based guard touring system is proposed. A traditional guard touring system devices lacks the abilities to provide a real-time data acquisition, integration of security related functionalities, summoning features and also a low cost to benefit ratio. Therefore, the proposed IoT based guard touring system provides a solution to the existing systems’ pitfalls at a cost effective price. The system consists of an Android based application for real-time interaction and also an admin monitoring webpage for communication management. The proposed system provides the smart connection and data to information conversion that could be used easily for data mining and subsequent data cognition process.