Adaptive distributed beamforming for relay networks based on local channel state information

Zhang, L. , Liu, W., Quddus, A. u., Dianati, M. and Tafazolli, R. (2015) Adaptive distributed beamforming for relay networks based on local channel state information. IEEE Transactions on Signal and Information Processing over Networks, 1(2), pp. 117-128. (doi: 10.1109/TSIPN.2015.2463076)

Abstract

Most of the existing distributed beamforming algorithms for relay networks require global channel state information (CSI) at relay nodes and the overall computational complexity is high. In this paper, a new class of adaptive algorithms is proposed which can achieve a globally optimum solution by employing only local CSI. A reference signal based (RSB) scheme is first derived, followed by a constant modulus (CM) based scheme when the reference signal is not available. Considering individual power transmission constraint at each relay node, the corresponding constrained adaptive algorithms are also derived as an extension. An analysis of the overhead and stepsize range for the derived algorithms are then provided and the excess mean square error (EMSE) for the RSB case is studied based on the energy reservation method. As demonstrated by our simulation results, a better performance has been achieved by our proposed algorithms and they have a very low computational complexity and can be implemented on low cost and low processing power devices.

• Item Type: Articles
• Additional Information: The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 619563.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zhang, Professor Lei
• Authors: Zhang, L., Liu, W., Quddus, A. u., Dianati, M., and Tafazolli, R.
• College/School: College of Science and Engineering > School of Engineering
• Journal Name: IEEE Transactions on Signal and Information Processing over Networks
• Publisher: IEEE
• ISSN: 2373-7778
• ISSN (Online): 2373-7778
• Published Online: 30 July 2015
• Copyright Holders: Copyright © 2015 IEEE
• First Published: First published in IEEE Transactions on Signal and Information Processing over Networks 1(2): 117-128
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher