Compressive sensing for feedback reduction in MIMO broadcast channels

Mohammed E. Eltayeb; Tareq Y. Al-Naffouri; Hamid Reza Talesh Bahrami

doi:10.1109/TCOMM.2014.2347964

Compressive sensing for feedback reduction in MIMO broadcast channels

Mohammed E. Eltayeb, Tareq Y. Al-Naffouri, Hamid Reza Talesh Bahrami

Research output: Contribution to journal › Article › peer-review

45 Scopus citations

Abstract

In multi-antenna broadcast networks, the base stations (BSs) rely on the channel state information (CSI) of the users to perform user scheduling and downlink transmission. However, in networks with large number of users, obtaining CSI from all users is arduous, if not impossible, in practice. This paper proposes channel feedback reduction techniques based on the theory of compressive sensing (CS), which permits the BS to obtain CSI with acceptable recovery guarantees under substantially reduced feedback overhead. Additionally, assuming noisy CS measurements at the BS, inexpensive ways for improving post-CS detection are explored. The proposed techniques are shown to reduce the feedback overhead, improve CS detection at the BS, and achieve a sum-rate close to that obtained by noiseless dedicated feedback channels.

Original language	English (US)
Pages (from-to)	3209-3222
Number of pages	14
Journal	IEEE Transactions on Communications
Volume	62
Issue number	9
DOIs	https://doi.org/10.1109/TCOMM.2014.2347964
State	Published - Sep 2014

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The work of T. Y. Al-Naffouri was supported by King Abdulaziz City for Science and Technology (KACST) through the Science and Technology Unit at King Fahd University of Petroleum and Minerals (KFUPM) under Project AR-29-79. The editor coordinating the review of this paper and approving it for publication was A. Tajer.

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/TCOMM.2014.2347964

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title = "Compressive sensing for feedback reduction in MIMO broadcast channels",

abstract = "In multi-antenna broadcast networks, the base stations (BSs) rely on the channel state information (CSI) of the users to perform user scheduling and downlink transmission. However, in networks with large number of users, obtaining CSI from all users is arduous, if not impossible, in practice. This paper proposes channel feedback reduction techniques based on the theory of compressive sensing (CS), which permits the BS to obtain CSI with acceptable recovery guarantees under substantially reduced feedback overhead. Additionally, assuming noisy CS measurements at the BS, inexpensive ways for improving post-CS detection are explored. The proposed techniques are shown to reduce the feedback overhead, improve CS detection at the BS, and achieve a sum-rate close to that obtained by noiseless dedicated feedback channels.",

author = "Eltayeb, {Mohammed E.} and Al-Naffouri, {Tareq Y.} and Bahrami, {Hamid Reza Talesh}",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: The work of T. Y. Al-Naffouri was supported by King Abdulaziz City for Science and Technology (KACST) through the Science and Technology Unit at King Fahd University of Petroleum and Minerals (KFUPM) under Project AR-29-79. The editor coordinating the review of this paper and approving it for publication was A. Tajer.",

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AU - Bahrami, Hamid Reza Talesh

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: The work of T. Y. Al-Naffouri was supported by King Abdulaziz City for Science and Technology (KACST) through the Science and Technology Unit at King Fahd University of Petroleum and Minerals (KFUPM) under Project AR-29-79. The editor coordinating the review of this paper and approving it for publication was A. Tajer.

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N2 - In multi-antenna broadcast networks, the base stations (BSs) rely on the channel state information (CSI) of the users to perform user scheduling and downlink transmission. However, in networks with large number of users, obtaining CSI from all users is arduous, if not impossible, in practice. This paper proposes channel feedback reduction techniques based on the theory of compressive sensing (CS), which permits the BS to obtain CSI with acceptable recovery guarantees under substantially reduced feedback overhead. Additionally, assuming noisy CS measurements at the BS, inexpensive ways for improving post-CS detection are explored. The proposed techniques are shown to reduce the feedback overhead, improve CS detection at the BS, and achieve a sum-rate close to that obtained by noiseless dedicated feedback channels.

AB - In multi-antenna broadcast networks, the base stations (BSs) rely on the channel state information (CSI) of the users to perform user scheduling and downlink transmission. However, in networks with large number of users, obtaining CSI from all users is arduous, if not impossible, in practice. This paper proposes channel feedback reduction techniques based on the theory of compressive sensing (CS), which permits the BS to obtain CSI with acceptable recovery guarantees under substantially reduced feedback overhead. Additionally, assuming noisy CS measurements at the BS, inexpensive ways for improving post-CS detection are explored. The proposed techniques are shown to reduce the feedback overhead, improve CS detection at the BS, and achieve a sum-rate close to that obtained by noiseless dedicated feedback channels.

UR - http://hdl.handle.net/10754/563745

UR - http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6878421

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DO - 10.1109/TCOMM.2014.2347964

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EP - 3222

JO - IEEE Transactions on Communications

JF - IEEE Transactions on Communications

IS - 9

ER -

Compressive sensing for feedback reduction in MIMO broadcast channels

Abstract

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