QoS-aware optimal power allocation with channel inversion regularization precoding in MU-MIMO

Xin Jin; Yubo Yang; Lin Tian; Di Pang; Jinglin Shi; Eryk Dutkiewicz

doi:10.1109/ICC.2009.5199380

QoS-aware optimal power allocation with channel inversion regularization precoding in MU-MIMO

Xin Jin^*, Yubo Yang, Lin Tian, Di Pang, Jinglin Shi, Eryk Dutkiewicz

^*Corresponding author for this work

School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

4 Citations (Scopus)

Abstract

In multiuser MIMO systems, the Channel Inversion Regularization (CIR) precoding outperforms Zero-Forcing (ZF) in the case of a small number of users and low SNR. However, unlike the zero-interference ZF, the optimal power allocation issue using CIR is a nonconvex optimization problem which will become more intractable with nonconvex QoS constraints. In this paper we focus on the challenging QoS-aware optimal power allocation problem, aiming to maximize the system sum rate and guarantee the users' minimum data rates. As a result, an "Iterative Geometric Programming" (IGP) strategy is proposed which transforms the underlying problem to a series of tractable Geometric Programming (GP) problems through an iterative convex approximation. Extensive simulations have been conducted and the results indicate that IGP is quite suitable to tackle the problem, which can achieve a good balance between the system sum rate and the individual QoS requirements.

Original language	English
Title of host publication	Proceedings - 2009 IEEE International Conference on Communications, ICC 2009
Place of Publication	Piscataway, N.J.
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1-5
Number of pages	5
ISBN (Print)	9781424434350
DOIs	https://doi.org/10.1109/ICC.2009.5199380
Publication status	Published - 2009
Event	2009 IEEE International Conference on Communications, ICC - 2009 - Dresden, Germany Duration: 14 Jun 2009 → 18 Jun 2009

Other

Other	2009 IEEE International Conference on Communications, ICC - 2009
Country/Territory	Germany
City	Dresden
Period	14/06/09 → 18/06/09

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10.1109/ICC.2009.5199380

Cite this

Jin, X., Yang, Y., Tian, L., Pang, D., Shi, J., & Dutkiewicz, E. (2009). QoS-aware optimal power allocation with channel inversion regularization precoding in MU-MIMO. In Proceedings - 2009 IEEE International Conference on Communications, ICC 2009 (pp. 1-5). Article 5199380 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICC.2009.5199380

@inproceedings{23a88a5b701040ef8c9ec671749e8313,

title = "QoS-aware optimal power allocation with channel inversion regularization precoding in MU-MIMO",

abstract = "In multiuser MIMO systems, the Channel Inversion Regularization (CIR) precoding outperforms Zero-Forcing (ZF) in the case of a small number of users and low SNR. However, unlike the zero-interference ZF, the optimal power allocation issue using CIR is a nonconvex optimization problem which will become more intractable with nonconvex QoS constraints. In this paper we focus on the challenging QoS-aware optimal power allocation problem, aiming to maximize the system sum rate and guarantee the users' minimum data rates. As a result, an {"}Iterative Geometric Programming{"} (IGP) strategy is proposed which transforms the underlying problem to a series of tractable Geometric Programming (GP) problems through an iterative convex approximation. Extensive simulations have been conducted and the results indicate that IGP is quite suitable to tackle the problem, which can achieve a good balance between the system sum rate and the individual QoS requirements.",

author = "Xin Jin and Yubo Yang and Lin Tian and Di Pang and Jinglin Shi and Eryk Dutkiewicz",

year = "2009",

doi = "10.1109/ICC.2009.5199380",

language = "English",

isbn = "9781424434350",

pages = "1--5",

booktitle = "Proceedings - 2009 IEEE International Conference on Communications, ICC 2009",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2009 IEEE International Conference on Communications, ICC - 2009 ; Conference date: 14-06-2009 Through 18-06-2009",

}

Jin, X, Yang, Y, Tian, L, Pang, D, Shi, J & Dutkiewicz, E 2009, QoS-aware optimal power allocation with channel inversion regularization precoding in MU-MIMO. in Proceedings - 2009 IEEE International Conference on Communications, ICC 2009., 5199380, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, N.J., pp. 1-5, 2009 IEEE International Conference on Communications, ICC - 2009, Dresden, Germany, 14/06/09. https://doi.org/10.1109/ICC.2009.5199380

QoS-aware optimal power allocation with channel inversion regularization precoding in MU-MIMO. / Jin, Xin; Yang, Yubo; Tian, Lin et al.
Proceedings - 2009 IEEE International Conference on Communications, ICC 2009. Piscataway, N.J.: Institute of Electrical and Electronics Engineers (IEEE), 2009. p. 1-5 5199380.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - QoS-aware optimal power allocation with channel inversion regularization precoding in MU-MIMO

AU - Jin, Xin

AU - Yang, Yubo

AU - Tian, Lin

AU - Pang, Di

AU - Shi, Jinglin

AU - Dutkiewicz, Eryk

PY - 2009

Y1 - 2009

N2 - In multiuser MIMO systems, the Channel Inversion Regularization (CIR) precoding outperforms Zero-Forcing (ZF) in the case of a small number of users and low SNR. However, unlike the zero-interference ZF, the optimal power allocation issue using CIR is a nonconvex optimization problem which will become more intractable with nonconvex QoS constraints. In this paper we focus on the challenging QoS-aware optimal power allocation problem, aiming to maximize the system sum rate and guarantee the users' minimum data rates. As a result, an "Iterative Geometric Programming" (IGP) strategy is proposed which transforms the underlying problem to a series of tractable Geometric Programming (GP) problems through an iterative convex approximation. Extensive simulations have been conducted and the results indicate that IGP is quite suitable to tackle the problem, which can achieve a good balance between the system sum rate and the individual QoS requirements.

AB - In multiuser MIMO systems, the Channel Inversion Regularization (CIR) precoding outperforms Zero-Forcing (ZF) in the case of a small number of users and low SNR. However, unlike the zero-interference ZF, the optimal power allocation issue using CIR is a nonconvex optimization problem which will become more intractable with nonconvex QoS constraints. In this paper we focus on the challenging QoS-aware optimal power allocation problem, aiming to maximize the system sum rate and guarantee the users' minimum data rates. As a result, an "Iterative Geometric Programming" (IGP) strategy is proposed which transforms the underlying problem to a series of tractable Geometric Programming (GP) problems through an iterative convex approximation. Extensive simulations have been conducted and the results indicate that IGP is quite suitable to tackle the problem, which can achieve a good balance between the system sum rate and the individual QoS requirements.

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BT - Proceedings - 2009 IEEE International Conference on Communications, ICC 2009

PB - Institute of Electrical and Electronics Engineers (IEEE)

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T2 - 2009 IEEE International Conference on Communications, ICC - 2009

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ER -

QoS-aware optimal power allocation with channel inversion regularization precoding in MU-MIMO

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