The Experts below are selected from a list of 13323 Experts worldwide ranked by ideXlab platform
Maryam Amiri Nezhad - One of the best experts on this subject based on the ideXlab platform.
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Utility based Channel Assignment: A centralized Channel Assignment mechanism for multi radio multi Channel wireless mesh networks
Scientific Research and Essays, 2012Co-Authors: Maryam Amiri Nezhad, Llorenccedil, Cerdagrave, Alabern, Manel Guerrero ZapataAbstract:In this paper, we address the Channel Assignment problem in a multi-radio mesh network that involves assigning Channels to radio interfaces for eliminating the effect of wireless interference. Due to the insufficient number of frequency Channels and available radios per node, interference is still present which limits the available bandwidth on wireless links and eventually decreases the achievable throughput. In this paper, we investigate the effect of considering the diverse delivery probability of the wireless links on the Channel Assignment solutions. We show that it is possible to classify the wireless links and omit some of them to benefit from a more diverse-Channel solution. We propose a new Channel Assignment mechanism aiming to minimize the interference over high performance links. Finally, a performance study is carried out to assess the effectiveness of our proposed algorithm. Evaluations show that the multi-Channel network obtained from our proposed algorithm achieves significant improvement in terms of reducing the interference and increasing the network capacity. Key words: Wireless mesh network, Channel Assignment, multi-radio, multi-Channel.
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Adaptive Channel Assignment for Wireless Mesh Networks using Game Theory
2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems, 2011Co-Authors: Maryam Amiri Nezhad, Llorenc Cerda-alabernAbstract:Channel Assignment has been extensively researched for multi-radio wireless mesh networks, but it is still very challenging when it comes to its implementation. In this paper we propose a semi-dynamic and distributed Channel Assignment mechanism called SICA that uses game theory. To the best of our knowledge this is the first game formulation of Channel Assignment which takes the co-Channel interference into account. SICA is an interference aware, distributed Channel Assignment which preserves the network connectivity without relying on a common Channel nor central node for coordination between mesh routers. SICA applies an on-line learner algorithm which assumes that nodes do not have perfect information. We have simulated SICA and compared against another interference-aware Channel Assignment mechanism proposed in the literature called Urban-X. Simulation results show that SICA outperforms Urban-X, even using fewer radio interfaces per node.
Llorenc Cerda-alabern - One of the best experts on this subject based on the ideXlab platform.
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Adaptive Channel Assignment for Wireless Mesh Networks using Game Theory
2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems, 2011Co-Authors: Maryam Amiri Nezhad, Llorenc Cerda-alabernAbstract:Channel Assignment has been extensively researched for multi-radio wireless mesh networks, but it is still very challenging when it comes to its implementation. In this paper we propose a semi-dynamic and distributed Channel Assignment mechanism called SICA that uses game theory. To the best of our knowledge this is the first game formulation of Channel Assignment which takes the co-Channel interference into account. SICA is an interference aware, distributed Channel Assignment which preserves the network connectivity without relying on a common Channel nor central node for coordination between mesh routers. SICA applies an on-line learner algorithm which assumes that nodes do not have perfect information. We have simulated SICA and compared against another interference-aware Channel Assignment mechanism proposed in the literature called Urban-X. Simulation results show that SICA outperforms Urban-X, even using fewer radio interfaces per node.
S.-h. Gary Chan - One of the best experts on this subject based on the ideXlab platform.
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CCNC - A Distributed Channel Assignment Algorithm for Uncoordinated WLANs
2010 7th IEEE Consumer Communications and Networking Conference, 2010Co-Authors: Cn Wong, S.-h. Gary ChanAbstract:IEEE 802.11 WLANs are becoming more and more popular in homes and urban areas. As opposed to traditional WLANs, the access points (APs) in these networks are often deployed by network non-specialists in an uncoordinated manner, leading to unplanned topology, interference and unsatisfactory throughput performance. We consider in this paper a distributed Channel Assignment algorithm for uncoordinated WLANs, where APs can self-configure their operating Channels to minimize interference. We propose an efficient, simple and distributed algorithm termed CACAO (Client-Assisted Channel Assignment Optimization). In CACAO, an AP makes use of the traffic information fed back by its clients to make Channel Assignment decision. This leads to better knowledge on network environment and better Channel Assignment decision at the APs. We conduct extensive simulation study and comparisons using Network Simulator 2 (NS2). Our results show that CACAO out-performs other traditional and recent schemes in terms of throughput with similar level of fairness. Furthermore, it converges quite fast to reduce interference to a low level.
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A Distributed Channel Assignment Algorithm for Uncoordinated WLANs
2010 7th IEEE Consumer Communications and Networking Conference, 2010Co-Authors: Chi-fai Wong, S.-h. Gary ChanAbstract:IEEE 802.11 WLANs are becoming more and more popular in homes and urban areas. As opposed to traditional WLANs, the access points (APs) in these networks are often deployed by network non-specialists in an uncoordinated manner, leading to unplanned topology, interference and unsatisfactory throughput performance. We consider in this paper a distributed Channel Assignment algorithm for uncoordinated WLANs, where APs can selfconfigure their operating Channels to minimize interference. We propose an efficient, simple and distributed algorithm termed CACAO (client-assisted Channel Assignment optimization). In CACAO, an AP makes use of the traffic information fed back by its clients to make Channel Assignment decision. This leads to better knowledge on network environment and better Channel Assignment decision at the APs. We conduct extensive simulation study and comparisons using network simulator 2 (NS2). Our results show that CACAO out-performs other traditional and recent schemes in terms of throughput with similar level of fairness. Furthermore, it converges quite fast to reduce interference to a low level.
Long Bao Le - One of the best experts on this subject based on the ideXlab platform.
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WCNC - Channel Assignment for throughput maximization in cognitive radio networks
2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012Co-Authors: Le Thanh Tan, Long Bao LeAbstract:In this paper, we consider the Channel allocation problem for throughput maximization in cognitive radio networks with hardware-constrained secondary users. Specifically, we assume that secondary users exploit spectrum holes on a set of Channels where each secondary user can use at most one available Channel for communication. We develop two Channel Assignment algorithms that can efficiently utilize spectrum opportunities on these Channels. In the first algorithm, secondary users are assigned distinct sets of Channels. We show that this algorithm achieves the maximum throughput limit if the number of Channels is sufficiently large. In addition, we propose an overlapping Channel Assignment algorithm, that can improve the throughput performance compared to the non-overlapping Channel Assignment algorithm. In addition, we design a distributed MAC protocol for access contention resolution and integrate the derived MAC protocol overhead into the second Channel Assignment algorithm. Finally, numerical results are presented to validate the theoretical results and illustrate the performance gain due to the overlapping Channel Assignment algorithm.
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Channel Assignment With Access Contention Resolution for Cognitive Radio Networks
IEEE Transactions on Vehicular Technology, 2012Co-Authors: Long Bao LeAbstract:In this paper, we consider the Channel Assignment problem for cognitive radio networks with hardware-constrained secondary users (SUs). In particular, we assume that SUs exploit spectrum holes on a set of Channels where each SU can use at most one available Channel for communication. We present the optimal brute-force search algorithm to solve the corresponding nonlinear integer optimization problem and analyze its complexity. Because the optimal solution has exponential complexity with the numbers of Channels and SUs, we develop two low-complexity Channel Assignment algorithms that can efficiently utilize the spectrum holes. In the first algorithm, SUs are assigned distinct sets of Channels. We show that this algorithm achieves the maximum throughput limit if the number of Channels is sufficiently large. In addition, we propose an overlapping Channel Assignment algorithm that can improve the throughput performance compared with its nonoverlapping Channel Assignment counterpart. Moreover, we design a distributed medium access control (MAC) protocol for access contention resolution and integrate it into the overlapping Channel Assignment algorithm. We then analyze the saturation throughput and the complexity of the proposed Channel Assignment algorithms. We also present several potential extensions, including the development of greedy Channel Assignment algorithms under the max-min fairness criterion and throughput analysis, considering sensing errors. Finally, numerical results are presented to validate the developed theoretical results and illustrate the performance gains due to the proposed Channel Assignment algorithms.
Chi-fai Wong - One of the best experts on this subject based on the ideXlab platform.
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A Distributed Channel Assignment Algorithm for Uncoordinated WLANs
2010 7th IEEE Consumer Communications and Networking Conference, 2010Co-Authors: Chi-fai Wong, S.-h. Gary ChanAbstract:IEEE 802.11 WLANs are becoming more and more popular in homes and urban areas. As opposed to traditional WLANs, the access points (APs) in these networks are often deployed by network non-specialists in an uncoordinated manner, leading to unplanned topology, interference and unsatisfactory throughput performance. We consider in this paper a distributed Channel Assignment algorithm for uncoordinated WLANs, where APs can selfconfigure their operating Channels to minimize interference. We propose an efficient, simple and distributed algorithm termed CACAO (client-assisted Channel Assignment optimization). In CACAO, an AP makes use of the traffic information fed back by its clients to make Channel Assignment decision. This leads to better knowledge on network environment and better Channel Assignment decision at the APs. We conduct extensive simulation study and comparisons using network simulator 2 (NS2). Our results show that CACAO out-performs other traditional and recent schemes in terms of throughput with similar level of fairness. Furthermore, it converges quite fast to reduce interference to a low level.
