No abstract

In a Wireless sensor network, the energy hole problem is a severe issue that forces the nodes near the sink to exhaust their energy sooner than the nodes deployed in the outer region, resulting the reduced the network lifetime. To overcome this problem, a novel clustering scheme with load balancing is proposed for a corona model network, where the coronas are divided into sector and form homogenous clusters. In the homogenous cluster, some nodes inside the circular centroid region (CR) forms cluster head (CH) to control network operation. It is important that the Load handled by the cluster heads are to be balanced by means of mixed routing strategy together with data aggregation. It is seen that this technique balances the energy in the network. The simulation result shows that this technique out performs other clustering scheme in terms of network lifetime and energy dissipation.

Transmission power control is an important issue in wireless ad hoc networks due to its dependency on battery power. It is a tendency of ad hoc nodes to transmit at their maximum power level to ensure successful delivery of their packets which causes interference to other neighboring nodes. In response, the other nodes also increase their power level which creates a situation of cascading effect where all nodes drain their battery power. In this paper, the cascading effect of interference caused by neighboring nodes and its impact on battery power in wireless ad hoc networks is analyzed and a non cooperative power control game is proposed to obtain an optimum power at which the nodes can maximize their utility without compromising the quality of services. The concept of game theory is also applied to determine an optimum SNIR that is the same value for all the nodes in networks for their mutual benefit. Through the numerical examples it is shown that the proposed concept obtains the maximum utility by minimizing the transmission power.

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This paper introduces a significant special situation where the noise is a collection of D-plane interference signals and the correlated noise of D+1 is less than the number of array components. An optimal beamforming processor based on the minimum variance distortionless response (MVDR) generates and combines appropriate statistics for the D+1 model. Instead of the original space of the N-dimensional problem, the interference signal subspace is reduced to D+1. Typical antenna arrays in many modern communication networks absorb waves generated from multiple point sources. An analytical formula was derived to improve the signal to interference and noise ratio (SINR) obtained from the steering errors of the two beamformers. The proposed MVDR processor-based beamforming does not enforce general constraints. Therefore, it can also be used in systems where the steering vector is compromised by gain. Simulation results show that the output of the proposed beamformer based on the MVDR processor is usually close to the ideal state within a wide range of signal-to-noise ratio and signal-to-interference ratio. The MVDR processor-based beamformer has been experimentally evaluated. The proposed processor-based MVDR system significantly improves performance for large interference white noise ratio (INR) in the sidelobe region and provide an appropriate beam pattern.