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Energy Optimization across Training and Data for Multiuser Minimum Sum-MSE Linear Precoding
 

Summary: Energy Optimization across Training and Data for
Multiuser Minimum Sum-MSE Linear Precoding
Adam J. Tenenbaum and Raviraj S. Adve
Dept. of Electrical and Computer Engineering, University of Toronto
10 King's College Road, Toronto, Ontario, M5S 3G4, Canada
Email: {adam,rsadve}@comm.utoronto.ca
Abstract--This paper considers minimum sum mean-squared
error (sum-MSE) linear transceiver designs in multiuser down-
link systems with imperfect channel state information. Specifi-
cally, 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.
I. INTRODUCTION
Transceiver designs that minimize the sum of mean squared
errors (sum-MSE) under a sum power constraint in the mul-

  

Source: Adve, Raviraj - Department of Electrical and Computer Engineering, University of Toronto

 

Collections: Engineering