Energy Optimization across Training and Data for Multiuser Minimum Sum-MSE Linear Precoding
Information Theory
2010-01-19 v1 math.IT
Abstract
This paper considers minimum sum mean-squared error (sum-MSE) linear transceiver designs in multiuser downlink systems with imperfect channel state information. Specifically, we derive the optimal energy allocations for training and data phases for such a system. Under MMSE estimation of uncorrelated Rayleigh block fading channels with equal average powers, we prove the separability of the energy allocation and transceiver design optimization problems. A closed-form optimum energy allocation is derived and applied to existing transceiver designs. Analysis and simulation results demonstrate the improvements that can be realized with the proposed design.
Cite
@article{arxiv.1001.3118,
title = {Energy Optimization across Training and Data for Multiuser Minimum Sum-MSE Linear Precoding},
author = {Adam J. Tenenbaum and Raviraj S. Adve},
journal= {arXiv preprint arXiv:1001.3118},
year = {2010}
}
Comments
Submitted to CISS 2010(6 pages, 4 figures). Uses IEEEtran.cls V1.7a