Grab-n-Pull: An optimization framework for fairness-achieving networks
Mojtaba Soltanalian, Ahmad Gharanjik, M. R. Bhavani Shankar, Björn E. Ottersten
Abstract
In this paper, we present an optimization framework for designing precoding (a.k.a. beamforming) signals that are instrumental in achieving a fair user performance through the networks. The precoding design problem in such scenarios can typically be formulated as a non-convex max-min fractional quadratic program. Using a penalized version of the original design problem, we derive a simplified quadratic reformulation of the problem in terms of the signal (to be designed). Each iteration of the proposed design framework consists of a combination of power method-like iterations and the Gram-Schmidt process, and as a result, enjoys a low computational cost. Moreover, the suggested approach can handle various types of signal constraints such as total-power, per-antenna power, unimodularity, or discrete-phase requirements - an advantage which is not shared by other existing approaches in the literature.
BibTeX
@inproceedings{icassp2016_grabnpullanoptim,
title = {Grab-n-Pull: An optimization framework for fairness-achieving networks},
author = {Mojtaba Soltanalian and Ahmad Gharanjik and M. R. Bhavani Shankar and Björn E. Ottersten},
booktitle = {ICASSP 2016},
year = {2016}
}