An integrated framework for optimizing power consumption of Smart Antennas

In this paper, we propose a framework for optimizing power consumption in Smart Antenna. A Smart Antenna (SA) consists of an antenna array and a smart processor at the back end. We have considered the power expended in the radio unit and the computation unit of the smart antenna system. We have established that in power limited applications, operating at 'small' distances, both computation power and radio power influence the battery life. The proposed framework explores the SA design space for the Beamforming application, taking into account the related parameters like distance, bit error rate, path loss exponent and the modulation scheme. Specifically, we have evaluated beamforming algorithms, Least Mean Square, Recursive Least Square, Constant Modulus algorithms. The power consumed by each of the algorithms is estimated and the total power in each case for SA is compared. It is found that the gain provided by a specific algorithm is counteracted by the power required to run the algorithm. We have analytically derived the 'crossover distance' where one algorithm becomes more power efficient with respect to another. Simulations have been carried out for a StrongARM SA-1100 processor platform. Simulations suggest that Least Mean Square algorithm is the most power efficient algorithm for distances below 600m.