Nik Noordini Nik Abdul Malik

Reduced size microstrip fractal filter with suppressed second harmonic

This paper presents the design of a reduced size microstrip fractal filter. It has an added capability of suppressing the undesired second harmonic, located at twice the fundamental frequency. The basic configuration is the conventional parallel-coupled filter (CPC). It suffers from undesired spurious responses located at the second harmonic, which causes asymmetry in the upper skirt band. The undesired second harmonic can be harmful to components in a communication system. A CPC filter is first designed. Then, Koch fractal shape is applied, forming the KF filter. Finally, a reduced size fractal shaped, RKF, filter is designed by realigning the fractal sections. All three filters have been simulated and measured. It can be concluded that the employed fractal shape can improve harmonic suppression by a factor of 2. RKF is comparable to KF, but exhibits size reduction of more than half.

Energy efficient protocol in wireless sensor networks using mobile base station

A wireless sensor network is made up of battery operated devices that have sensing, processing and transmitting capabilities. The design constraint of a wireless sensor network is its network lifetime. In order to prolong the network lifetime, the sensor nodes must be able to use the minimal energy to transmit data to the base station. Hence, an efficient protocol is needed. One method to reduce the energy consumption among sensor nodes is to use mobile base station instead of static base station. This approach allows the base station to move closer to sensor nodes in order to reduce the communication distance between them. Consequently, it decreases the energy utilisation of the network. Another approach is by using the clustering method in which the sensor nodes in a network are grouped into clusters and only the cluster heads relay the aggregated data to the base station. However, this approach would be a burden to the cluster heads. Hence, the task of the cluster head could be alternated among sensor nodes so that the energy load among all sensor nodes is balanced. This paper proposes an energy efficient protocol for wireless sensor networks using mobile base station which is based on the clustering approach with role rotation.

Load distributed routing protocol for wireless mesh networks

This paper presents a routing protocol called Load Distributed Mesh Routing (LDMR) that is developed for Wireless Mesh Network (WMN) with IEEE 802.11 standard. The LDMR protocol decides on the potential next hop nodes based on a quadrant and distance information. Then, the Next Hop Forwarding (NHF) decision is used to select the best next hop nodes based on Packet Success Rate (PSR) and maximum velocity of a packet. The proposed LDMR protocol has been implemented and verified through simulation in Network Simulator 3 (NS3) for both randomly distributed and grid network topologies. The network performance of LDMR is compared with the existing routing protocols, which are Ad Hoc on Demand Distance Vector (AODV) and Hybrid Wireless Mesh Protocol (HWMP). Simulation results show that the throughput of LDMR is improved when compared to HWMP and AODV in most of the simulated cases. The LDMR protocol also maintains a low average end-to-end delay which is lower than 0.01s in almost all cases when compared with AODV and HWMP protocols.

Hybrid Backtracking Search Optimization Algorithm and K-Means for Clustering in Wireless Sensor Networks

Rapid technology evolvement in the area of wireless sensor networks (WSNs) has led to many application-specific protocols that are particularly developed to cover different fields of usage and various network scenarios. Energy efficiency is one of the apparent challenges facing WSNs which has impacted immensely on the network performance. Hence, clustering protocols that eliminate energy inefficiencies in the network is essential. As finding an optimal set of cluster heads is an NP-hard problem, the application of heuristic algorithm is required to produce good clustering. In this paper, we propose a clustering solution for WSNs using a hybrid algorithm based on Backtracking Search Optimization Algorithm (BSA) and K-Means. A fitness function that incorporates aspects such as expected energy consumption in the network and maximum intra-cluster distance is utilized to address the problem of energy efficiency. Performance comparison against well-known clustering protocols such as LEACH and LEACH-C reveals that the hybrid of BSA and K-Means clustering algorithm is able to deliver more data to the base station and extends the network lifetime.

Process noise parameters of beamforming nodes in wireless sensor networks (WSNs)

Signals from collaborative beamforming (CB) nodes are always arriving out of phase at the intended receiver due to unsynchronized clock frequencies of different oscillators of these nodes. Beamforming nodes have to synchronize their carrier frequencies in order to eliminate any phase offset of the received signal. To do this, estimation, correction and prediction of phase offsets due largely to these drifts needs be carried out on Software Defined-Radio (SDR) while employing non-linear filters like the Extended Kalman Filter (EKF) so as to obtain a near zero (0) phase offset. This paper presents a method of computing the NI USRP-2920 process noise parameters of the phase noise (dBc/Hz) data obtained with keysight N9320B spectrum analyzer (SA). The effects of phase offset measurements at various offset frequencies of the carrier are shown. Power-law noise model is applied to compute the Allan variance and later the process noise parameters that will be applied with the EKF. It will be noticed that the Allan variance curve truly depicts the standard slope characteristics of white frequency and random walk frequency noises which are special considerations when dealing with USRPs oscillators.