DocumentCode :
266494
Title :
AMMSE optimization for multiuser MISO systems with imperfect CSIT and perfect CSIR
Author :
Joudeh, Hamdi ; Clerckx, Bruno
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK
fYear :
2014
fDate :
8-12 Dec. 2014
Firstpage :
3308
Lastpage :
3313
Abstract :
In this paper, we consider the design of robust linear precoders for MU-MISO systems where users have perfect Channel State Information (CSI) while the BS has partial CSI. In particular, the BS has access to imperfect estimates of the channel vectors, in addition to the covariance matrices of the estimation error vectors. A closed-form expression for the Average Minimum Mean Square Error (AMMSE) is obtained using the second order Taylor Expansion. This approximation is used to formulate two fairness-based robust design problems: a maximum AMMSE-constrained problem and a power-constrained problem. We propose an algorithm based on convex optimization techniques to address the first problem, while the second problem is tackled by exploiting the close relationship between the two problems, in addition to their monotonie natures.
Keywords :
MIMO communication; channel estimation; convex programming; covariance matrices; least mean squares methods; multi-access systems; wireless channels; AMMSE optimization; BS; MU-MISO system; average minimum mean square error; channel estimation; channel state information; convex optimization technique; covariance matrix; error vector estimation; imperfect CSIT; linear precoder; multiuser MISO system; perfect CSIR; power-constrained problem; second order Taylor expansion; Approximation algorithms; Approximation methods; Channel estimation; Receivers; Robustness; Signal processing algorithms; Vectors; AMMSE; Imperfect CSIT; Robust Design;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Communications Conference (GLOBECOM), 2014 IEEE
Conference_Location :
Austin, TX
Type :
conf
DOI :
10.1109/GLOCOM.2014.7037317
Filename :
7037317
Link To Document :
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