AMMSE optimization for multiuser MISO systems with imperfect CSIT and perfect CSIR

Hamdi Joudeh; Bruno Clerckx

doi:10.1109/GLOCOM.2014.7037317

AMMSE optimization for multiuser MISO systems with imperfect CSIT and perfect CSIR

Hamdi Joudeh, Bruno Clerckx

Research output: Contribution to journal › Conference article › peer-review

6 Citations (Scopus)

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.

Original language	English
Article number	7037317
Pages (from-to)	3308-3313
Number of pages	6
Journal	Proceedings - IEEE Global Communications Conference, GLOBECOM
DOIs	https://doi.org/10.1109/GLOCOM.2014.7037317
Publication status	Published - 2014
Event	2014 IEEE Global Communications Conference, GLOBECOM 2014 - Austin, United States Duration: 2014 Dec 8 → 2014 Dec 12

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

AMMSE
Imperfect CSIT
Robust Design

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Hardware and Architecture
Signal Processing

Access to Document

10.1109/GLOCOM.2014.7037317

Cite this

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title = "AMMSE optimization for multiuser MISO systems with imperfect CSIT and perfect CSIR",

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.",

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AU - Joudeh, Hamdi

AU - Clerckx, Bruno

PY - 2014

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AB - 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.

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KW - Robust Design

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DO - 10.1109/GLOCOM.2014.7037317

M3 - Conference article

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JO - Proceedings - IEEE Global Communications Conference, GLOBECOM

JF - Proceedings - IEEE Global Communications Conference, GLOBECOM

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AMMSE optimization for multiuser MISO systems with imperfect CSIT and perfect CSIR

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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