Title: POPULATION MEAN ESTIMATE FOR ADAPTIVE MODULATION UNDER LARGE PHASE ERROR IN SINGLE BEAMFORMING SENSOR ARRAY

Issue Number: Vol. 5, No. 2
Year of Publication: 2015
Page Numbers: 82-94
Authors: G. Vaikundam, G.F.Sudha
Journal Name: International Journal of Digital Information and Wireless Communications (IJDIWC)
- Hong Kong
DOI:  http://dx.doi.org/10.17781/P001644

Abstract:


Beamforming is a signal processing technique to focus the transmitted energy so that maximum energy is radiated in the intended destination and communication range is enhanced. Data rate improvement in Transmit beamforming can be achieved with adaptive modulation. Though modulation adaptation is possible under zero-mean phase error, it is difficult to adapt it under non-zero mean Gaussian distributed phase error conditions. Phase errors occur due to channel estimation inaccuracies, delay in estimation, sensor drift, quantized feedback etc resulting in increased outage probability and Bit error rate. Preprocessing of beamforming weights adjusted by Sample Mean Estimate (SME) solves the problem of adaptive modulation. However, under large phase error variation, the SME method fails. Hence, in this paper, Population Mean Estimate (PME) approach is proposed to resolve these drawbacks for a Rayleigh flat fading channel with White Gaussian Noise. To correct the population mean error if any, Least Mean Square correction algorithm is proposed and is tested up to 80% error in PME and the corrected error fall within 10% error. Simulation results for a distributed beamforming sensor array indicate that the proposed method performs better than the SME based existing methods under worst-case phase error distribution.