Low-complexity Scheduling Algorithms for Multi-channel Downlink Wireless Networks

This paper considers the problem of designing scheduling algorithms for multi-channel (e.g., OFDM) wireless downlink networks with n users/OFDM sub-channels. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (form...

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Published in:2010 Proceedings IEEE INFOCOM pp. 1 - 9
Main Authors: Bodas, Shreeshankar, Shakkottai, Sanjay, Lei Ying, Srikant, R
Format: Conference Proceeding
Language:English
Published: IEEE 01.03.2010
Subjects:
Algorithm design and analysis
Analytical models
Buffer overflow
Computational complexity
Computational modeling
Downlink
OFDM
Scheduling algorithm
Throughput
Wireless networks
ISBN:1424458366, 9781424458363
ISSN:0743-166X
Online Access:Get full text
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Abstract This paper considers the problem of designing scheduling algorithms for multi-channel (e.g., OFDM) wireless downlink networks with n users/OFDM sub-channels. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, we show it has zero rate function in our setting). To address this, we propose a class of algorithms called iHLQF (iterated Heaviest matching with Longest Queues First) that is shown to be throughput optimal for a general class of arrival/channel processes, and also rate-function optimal (i.e., exponentially small buffer overflow probability) for certain arrival/channel processes. iHLQF however has higher complexity than MaxWeight (n 4 vs. n 2 respectively). To overcome this issue, we propose a new algorithm called SSG (Server-Side Greedy). We show that SSG is throughput optimal, results in a much better per-user buffer overflow performance than the MaxWeight algorithm (positive rate function for certain arrival/channel processes), and has a computational complexity (n 2 ) that is comparable to the MaxWeight algorithm. Thus, it provides a nice trade-off between buffer-overflow performance and computational complexity. These results are validated by both analysis and simulations.
AbstractList This paper considers the problem of designing scheduling algorithms for multi-channel (e.g., OFDM) wireless downlink networks with n users/OFDM sub-channels. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, we show it has zero rate function in our setting). To address this, we propose a class of algorithms called iHLQF (iterated Heaviest matching with Longest Queues First) that is shown to be throughput optimal for a general class of arrival/channel processes, and also rate-function optimal (i.e., exponentially small buffer overflow probability) for certain arrival/channel processes. iHLQF however has higher complexity than MaxWeight (n 4 vs. n 2 respectively). To overcome this issue, we propose a new algorithm called SSG (Server-Side Greedy). We show that SSG is throughput optimal, results in a much better per-user buffer overflow performance than the MaxWeight algorithm (positive rate function for certain arrival/channel processes), and has a computational complexity (n 2 ) that is comparable to the MaxWeight algorithm. Thus, it provides a nice trade-off between buffer-overflow performance and computational complexity. These results are validated by both analysis and simulations.
Author Srikant, R
Shakkottai, Sanjay
Lei Ying
Bodas, Shreeshankar
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  givenname: Sanjay
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  surname: Lei Ying
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Snippet This paper considers the problem of designing scheduling algorithms for multi-channel (e.g., OFDM) wireless downlink networks with n users/OFDM sub-channels....
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SubjectTerms Algorithm design and analysis
Analytical models
Buffer overflow
Computational complexity
Computational modeling
Downlink
OFDM
Scheduling algorithm
Throughput
Wireless networks
Title Low-complexity Scheduling Algorithms for Multi-channel Downlink Wireless Networks
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