RSSI and AoA Combination using PSO-Based Clustering for Localization in WSN
Dipak W. Wajgi, Jitendra V. Tembhurne and Rakhi D. Wajgi
Localization in wireless sensor network is attracting many researchers because of its significance in many real-time applications to identify the origin of events. Many applications such as battlefield, environment monitoring, habitat monitoring, and forest fire detection, etc. wherein origin of event occurrence is very important. Hence, researchers has proposed different algorithms for location identification of the sensor nodes in wireless sensor network, utilizing simulations or by creating the real-time scenarios. This paper presents the comprehensive review of localization algorithms based on soft computing techniques. This paper also presents the Particle Swarm Optimization (PSO) based clustering to find the location of the sensor nodes using the combination of Received Signal Strength Indicator (RSSI) and the Angle of Arrival (AoA). This combination of RSSI and AoA makes the clustering algorithm more efficient to achieve better accuracy in location estimation with less computational complexity. The lifetime of the sensor network which is mainly dependent on the energy dissipation of the sensor nodes is also considered in the proposed approach. The energy dissipation in the proposed approach can be reduced by adopting the density control strategy during cluster formation and reducing the communication among the sensor nodes and hence increasing the lifetime of the network.
Keywords: Wireless sensor network, localization, PSO, RSSI, AoA