In this paper, we propose binary particle swarm optimization (BPSO) algorithm for distributed node localization in wireless sensor networks (WSNs). Each unknown node performs localization under the measurement of distances from three or more neighboring anchors. The node that gets localized during iteration will be used as a reference for remaining nodes. A comparison of the performances of PSO, basic BPSO and modified BPSO in terms of localization error and computation time is presented using simulation in Matlab.

In this paper, we propose a binary particle swarm optimization (BPSO) algorithm for distributed node localization in wireless sensor networks (WSNs). Each unknown node performs localization under the distance measurement from three or more neighboring anchors. The node that gets localized will be used as a reference for remaining nodes. A comparison of the performances of PSO and BPSO in terms of localization error and computation time is presented using simulations in Matlab.

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In this paper, we investigate the coverage of Geo-Clustering Algorithm (GCA) in heterogeneous networks where pico cells are added to complement the coverage holes by macro cell based layout. GCA is considered to plan the cellular network based on geographical elements. Coverage probability is used as the performance metric and compared with GCA without pico cells.