Distributed Algorithms For Beamforming In Wireless Sensor Network

A wireless sensor network (WSN) consists of a large number of microsensors,each havinglimited battery lifetime and, therefore, restricted communication andcomputing capabilities. Recentadvances in the integrated circuit technology have allowed the production of lightweight andinexpensive sensor nodes. If they are properly networked and programmed, these sensor nodes canform an antenna array and then establish a communication link with a UAV by using beamformingtechniques in order to perform complex signal processing functions. The main issue for a WSN is toprolong its operational lifetime as much as possible, taking into account the sensors’ powerconsumption requirements.In order to spread the processing and communication load among the nodes, two newdistributed algorithms for beamforming are proposed. The first is based on the well known QRfactorization, and the second is based on the iterative method. The presented algorithms wereevaluated in terms of the processing cost, the communication cost and the total power consumptionand then compared to the centralized implementation. A simulation model was developed in theMATLAB environment to analyze algorithms. The simulations show that the processing load iseffectively shared among the nodes. In the first approach, the processing cost is the same as in thecentralized approach. However, in the second approach, the processing load can be lower than thatof the centralized approach, depending on the algorithm’s convergence. For both algorithms, thetradeoff for the ability to spread the processing load is the increased communication cost, whichcould cause an overall increase in the total power consumption in the network. However, theaverage power per sensor node is still lower than that required by the cluster head in the centralizedapproach. Consequently, the algorithms increase the network’s scalability and robustness.