Distributed traffic estimation and throughput optimization in random access networks

Due to the shared nature of the wireless channel in a random access network, the wireless nodes in a network naturally interact with each other and thus affect the throughput performance and energy consumption of each other. The aim of this thesis is to illustrate the use of local information for th...

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Main Author: Xie, Shuanglong
Other Authors: Low Kay Soon
Format: Theses and Dissertations
Language:English
Published: 2016
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Online Access:https://hdl.handle.net/10356/68831
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-688312023-07-04T16:31:16Z Distributed traffic estimation and throughput optimization in random access networks Xie, Shuanglong Low Kay Soon School of Electrical and Electronic Engineering Satellite Engineering Centre DRNTU::Engineering::Electrical and electronic engineering Due to the shared nature of the wireless channel in a random access network, the wireless nodes in a network naturally interact with each other and thus affect the throughput performance and energy consumption of each other. The aim of this thesis is to illustrate the use of local information for the traffic estimation and the throughput optimization in random access networks. Specifically, this thesis investigates various key issues on the design of random access networks, including transmission strategy in a slotted ALOHA network, distributed traffic characterization and throughput optimization in a CSMA network and optimum backoff protocol design in a non-persistent CSMA network. The traditional use of channel state information (CSI) in a slotted ALOHA network will lead to Braess Paradox, i.e., more information resulting in worse throughput performance. This thesis first proposes a new method to exploit the CSI named adaptive CSI method to eliminate the Braess Paradox and thus to improve the throughput performance. The use of acknowledgement is explored to estimate the transmission probabilities of other nodes in the network. It thus enables the distributed implementation of the proposed method. Moreover, this research generalizes two simple yet effective guidelines to determine the best transmission strategy under different system scenarios. Secondly, two novel distributed algorithms are proposed to estimate the on-going traffic in a heterogeneous CSMA network. In contrast to centralized Markov chain models, the proposed methods are able to characterize the traffic without prior information. They are also able to detect changes in the traffic. With the use of the traffic estimation method, a throughput adjustment algorithm is also proposed to tune the transmission rate of each node with respect to a desired throughput demand. Finally, the throughput performance of a non-persistent CSMA network under imperfect sensing is thoroughly examined. It is discovered that the traditional binary exponent backoff protocol accounts for the throughput inefficiency in CSMA networks. A novel backoff protocol named probabilistic backoff CSMA (PB-CSMA) is proposed, which is able to achieve optimum throughput performance regardless of the number of nodes as well as the level of sensing errors. Using the clear channel assessment results, the distributed implementation of PB-CSMA is also introduced. Simulation and experimental studies have been conducted to evaluate the proposed algorithms in terms of accuracy, convergence speed and computational complexity. The results show that with proper use of local information, the traffic intensity can be accurately estimated, the throughput can be significantly improved and the energy consumption can be further reduced for random access networks in a distributed manner. DOCTOR OF PHILOSOPHY (EEE) 2016-06-08T07:32:48Z 2016-06-08T07:32:48Z 2016 Thesis Xie, S. (2016). Distributed traffic estimation and throughput optimization in random access networks. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/68831 10.32657/10356/68831 en 153 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Xie, Shuanglong
Distributed traffic estimation and throughput optimization in random access networks
description Due to the shared nature of the wireless channel in a random access network, the wireless nodes in a network naturally interact with each other and thus affect the throughput performance and energy consumption of each other. The aim of this thesis is to illustrate the use of local information for the traffic estimation and the throughput optimization in random access networks. Specifically, this thesis investigates various key issues on the design of random access networks, including transmission strategy in a slotted ALOHA network, distributed traffic characterization and throughput optimization in a CSMA network and optimum backoff protocol design in a non-persistent CSMA network. The traditional use of channel state information (CSI) in a slotted ALOHA network will lead to Braess Paradox, i.e., more information resulting in worse throughput performance. This thesis first proposes a new method to exploit the CSI named adaptive CSI method to eliminate the Braess Paradox and thus to improve the throughput performance. The use of acknowledgement is explored to estimate the transmission probabilities of other nodes in the network. It thus enables the distributed implementation of the proposed method. Moreover, this research generalizes two simple yet effective guidelines to determine the best transmission strategy under different system scenarios. Secondly, two novel distributed algorithms are proposed to estimate the on-going traffic in a heterogeneous CSMA network. In contrast to centralized Markov chain models, the proposed methods are able to characterize the traffic without prior information. They are also able to detect changes in the traffic. With the use of the traffic estimation method, a throughput adjustment algorithm is also proposed to tune the transmission rate of each node with respect to a desired throughput demand. Finally, the throughput performance of a non-persistent CSMA network under imperfect sensing is thoroughly examined. It is discovered that the traditional binary exponent backoff protocol accounts for the throughput inefficiency in CSMA networks. A novel backoff protocol named probabilistic backoff CSMA (PB-CSMA) is proposed, which is able to achieve optimum throughput performance regardless of the number of nodes as well as the level of sensing errors. Using the clear channel assessment results, the distributed implementation of PB-CSMA is also introduced. Simulation and experimental studies have been conducted to evaluate the proposed algorithms in terms of accuracy, convergence speed and computational complexity. The results show that with proper use of local information, the traffic intensity can be accurately estimated, the throughput can be significantly improved and the energy consumption can be further reduced for random access networks in a distributed manner.
author2 Low Kay Soon
author_facet Low Kay Soon
Xie, Shuanglong
format Theses and Dissertations
author Xie, Shuanglong
author_sort Xie, Shuanglong
title Distributed traffic estimation and throughput optimization in random access networks
title_short Distributed traffic estimation and throughput optimization in random access networks
title_full Distributed traffic estimation and throughput optimization in random access networks
title_fullStr Distributed traffic estimation and throughput optimization in random access networks
title_full_unstemmed Distributed traffic estimation and throughput optimization in random access networks
title_sort distributed traffic estimation and throughput optimization in random access networks
publishDate 2016
url https://hdl.handle.net/10356/68831
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