Low-Complexity Scheduling Algorithms for Multichannel Downlink Wireless Networks
This paper considers the problem of designing scheduling algorithms for multichannel (e.g., OFDM-based) wireless downlink networks, with a large number of users and proportionally large bandwidth. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-...
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| Vydáno v: | IEEE/ACM transactions on networking Ročník 20; číslo 5; s. 1608 - 1621 |
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| Jazyk: | angličtina |
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01.10.2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1063-6692, 1558-2566 |
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| Abstract | This paper considers the problem of designing scheduling algorithms for multichannel (e.g., OFDM-based) wireless downlink networks, with a large number of users and proportionally large bandwidth. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, it is shown that it has zero rate function in our setting). To address this, a class of algorithms called iterated Heaviest matching with Longest Queues First (iHLQF) is proposed. The algorithms in this class are 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 versus n 2 , respectively). To overcome this issue, a new algorithm called Server-Side Greedy (SSG) is proposed. It is shown 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 tradeoff between buffer-overflow performance and computational complexity. These results are validated by both analysis and simulations. |
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| AbstractList | This paper considers the problem of designing scheduling algorithms for multichannel (e.g., OFDM-based) wireless downlink networks, with a large number of users and proportionally large bandwidth. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, it is shown that it has zero rate function in our setting). To address this, a class of algorithms called iterated Heaviest matching with Longest Queues First (iHLQF) is proposed. The algorithms in this class are 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 ([Formula Omitted] versus [Formula Omitted], respectively). To overcome this issue, a new algorithm called Server-Side Greedy (SSG) is proposed. It is shown 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 [Formula Omitted] that is comparable to the MaxWeight algorithm. Thus, it provides a nice tradeoff between buffer-overflow performance and computational complexity. These results are validated by both analysis and simulations. This paper considers the problem of designing scheduling algorithms for multichannel (e.g., OFDM-based) wireless downlink networks, with a large number of users and proportionally large bandwidth. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, it is shown that it has zero rate function in our setting). To address this, a class of algorithms called iterated Heaviest matching with Longest Queues First (iHLQF) is proposed. The algorithms in this class are 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 versus n 2 , respectively). To overcome this issue, a new algorithm called Server-Side Greedy (SSG) is proposed. It is shown 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 tradeoff between buffer-overflow performance and computational complexity. These results are validated by both analysis and simulations. |
| Author | Lei Ying Srikant, R. Bodas, S. Shakkottai, S. |
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| SubjectTerms | Algorithm design and analysis Algorithms Arrivals Buffers Channels Complexity Complexity theory Downlink Large deviations low complexity Mathematical analysis Mathematical models Resource management Scheduling Scheduling algorithms Servers small buffer Studies Throughput Wireless networks |
| Title | Low-Complexity Scheduling Algorithms for Multichannel Downlink Wireless Networks |
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