Distributed beamforming for randomly distributed sensors using bisection method and dynamic programming technique

Beamforming is being used in sensor networks to enhance its communication range.The sensors in networks use their own clock adjustment for distributed beamforming by coordinating with other sensors. For this, the Channel State Information(CSI) is required. Since the CSI is not available at the transmitter side, the Channel Phase tracking is used. A novel bisection based phase tracking method is proposed for compensation of channel propagation delay.This eliminates the probability based method which has more computational complexity. The problem of phase tracking is modeled as a minimization problem. The phase is adjusted iteratively similar to finding roots for an algebraic equation using bisection method. Further, the problem of phase adjustment is simplified by considering phase adjustment of single participating sensor in each time slot using Dynamic Programming Technique, instead of collectively adjusting the phase of all participating sensors. This technique is compared with bilateral uniform, Gaussian and Laplacian distribution function. The initial time delay is considered as bilateral uniform distributed and channel propagation delay is modeled as Rayleigh distributed variables. A computationally efficient algorithm is developed for distributed beamforming and results show 66% reduction in computation complexity.