Distributed Algorithms for Beamforming in Wireless Sensor Networks

Sensor nodes in a wireless sensor network (WSN) can establish a link with a UAV by using beamforming techniques to form a random array with position errors. The position errors’ effect in the array performance is examined using a MATLAB-based simulation model. In order to spread the processing and communication load among the nodes, two new distributed algorithms for beamforming in WSN, based on the least squares (LS) approximation of the desired array response, are proposed. The first is a distributed implementation of the QR decomposition, and the second is an iterative method for solving the LS problem. Results indicate that the processing load is effectively shared among the nodes. Especially, in the second approach, the processing load can be lower than that of the centralized approach, depending on the algorithm’s convergence. For both algorithms, the tradeoff for the ability to spread the processing load is the increased communication cost, which could cause an overall increase in the total power consumption in the network. However, the average power per participating sensor node is still lower than that required by the cluster head in the centralized approach. Consequently, the network’s susceptibility to failures due to excessive power consumption is greatly reduced.