Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback
We consider a multi-antenna broadcast channel with more single-antenna receivers than transmit antennas and partial channel state information at the transmitter (CSIT). We propose a novel type of CSIT representation for the purpose of user selection, coined as ranking-based feedback. Each user calcu...
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2008-04-01
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Series: | EURASIP Journal on Advances in Signal Processing |
Online Access: | http://dx.doi.org/10.1155/2008/854120 |
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doaj-e127f21136614cd5b80e45fede8ee24e2020-11-25T01:43:12ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802008-04-01200810.1155/2008/854120Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based FeedbackDavid GesbertThomas SälzerMarios KountourisWe consider a multi-antenna broadcast channel with more single-antenna receivers than transmit antennas and partial channel state information at the transmitter (CSIT). We propose a novel type of CSIT representation for the purpose of user selection, coined as ranking-based feedback. Each user calculates and feeds back the rank, an integer between 1 and W + 1, of its instantaneous channel quality information (CQI) among a set of W past CQI measurements. Apart from reducing significantly the required feedback load, ranking-based feedback enables the transmitter to select users that are on the highest peak (quantile) with respect to their own channel distribution, independently of the distribution of other users. It can also be shown that this feedback metric can restore temporal fairness in heterogeneous networks, in which users' channels are not identically distributed and mobile terminals experience different average signal-to-noise ratio (SNR). The performance of a system that performs user selection using ranking-based CSIT in the context of random opportunistic beamforming is analyzed, and we provide design guidelines on the number of required past CSIT samples and the impact of finite W on average throughput. Simulation results show that feedback reduction of order of 40â€Â50% can be achieved with negligible decrease in system throughput.http://dx.doi.org/10.1155/2008/854120 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
David Gesbert Thomas Sälzer Marios Kountouris |
spellingShingle |
David Gesbert Thomas Sälzer Marios Kountouris Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback EURASIP Journal on Advances in Signal Processing |
author_facet |
David Gesbert Thomas Sälzer Marios Kountouris |
author_sort |
David Gesbert |
title |
Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback |
title_short |
Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback |
title_full |
Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback |
title_fullStr |
Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback |
title_full_unstemmed |
Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback |
title_sort |
scheduling for multiuser mimo downlink channels with ranking-based feedback |
publisher |
SpringerOpen |
series |
EURASIP Journal on Advances in Signal Processing |
issn |
1687-6172 1687-6180 |
publishDate |
2008-04-01 |
description |
We consider a multi-antenna broadcast channel with more single-antenna receivers than transmit antennas and partial channel state information at the transmitter (CSIT). We propose a novel type of CSIT representation for the purpose of user selection, coined as ranking-based feedback. Each user calculates and feeds back the rank, an integer between 1 and W + 1, of its instantaneous channel quality information (CQI) among a set of W past CQI measurements. Apart from reducing significantly the required feedback load, ranking-based feedback enables the transmitter to select users that are on the highest peak (quantile) with respect to their own channel distribution, independently of the distribution of other users. It can also be shown that this feedback metric can restore temporal fairness in heterogeneous networks, in which users' channels are not identically distributed and mobile terminals experience different average signal-to-noise ratio (SNR). The performance of a system that performs user selection using ranking-based CSIT in the context of random opportunistic beamforming is analyzed, and we provide design guidelines on the number of required past CSIT samples and the impact of finite W on average throughput. Simulation results show that feedback reduction of order of 40â€Â50% can be achieved with negligible decrease in system throughput. |
url |
http://dx.doi.org/10.1155/2008/854120 |
work_keys_str_mv |
AT davidgesbert schedulingformultiusermimodownlinkchannelswithrankingbasedfeedback AT thomass228lzer schedulingformultiusermimodownlinkchannelswithrankingbasedfeedback AT marioskountouris schedulingformultiusermimodownlinkchannelswithrankingbasedfeedback |
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1725032752500178944 |