Channel Assignment for Throughput Optimization in Multichannel Multiradio Wireless Mesh Networks Using Network Coding

Chieochan, Surachai; Hossain, Ekram

doi:10.1109/tmc.2011.252

Cited by 48 publications

(31 citation statements)

References 34 publications

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“…By the worked out scheduling factor, transmission method and transmission power in Section 3, we can determine the corresponding transmission methods in Configuration s, where the activated links inside the link combination are interference free in single-channel single-radio transmission. In this section, we consider the case that each node is equipped with a number of wireless interfaces, which can be tuned onto one of the orthogonal channels, and switch quickly from one channel to another with a negligible switching delay (Chieochan and Hossain, 2013).…”

Section: Heuristic Methods Based Channel Assignment Schemementioning

confidence: 99%

“…The study on CA in MC-MR network has become a hot topic after these pioneer works. Chieochan and Hossain (2013) formulated the joint problem of NC, CA and link scheduling, and developed a suboptimal, auction-based solution to obtain the overall network throughput. A practical NC scheme in MC-MR network was implemented by Chi and Agrawal (2012), where the authors demonstrated this scheme can improve network performance not only on network throughput, but also on end-to-end delay.…”

Section: Related Workmentioning

confidence: 99%

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A novel adaptive spectrum allocation scheme for multi-channel multi-radio wireless mesh networks

Ning

Song

Guo

et al. 2015

Journal of Network and Computer Applications

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Section: Heuristic Methods Based Channel Assignment Schemementioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A novel adaptive spectrum allocation scheme for multi-channel multi-radio wireless mesh networks

Ning

Song

Guo

et al. 2015

Journal of Network and Computer Applications

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“…With Dynamic Spectrum Accessing (DSA), spectrum trading is proposed to solve the problem of spectrum scarcity [12,20]. Nevertheless, the implementation of spectrum trading faces several challenges because of the fluctuating nature of the available spectrum and the changes in the spectrum demand.…”

Section: Related Workmentioning

confidence: 99%

“…Hence, WMNs are predicted to be a key technology that offer ubiquitous connectivity to the end users [12,13,21]. Although WMNs provide better services in term of flexible network architectures, easy deployment and configuration, and fault tolerance, still the limited available spectrum and the inefficiency in the spectrum usage degrade the network performance significantly.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, beside the dramatic increase in the access to the limited bandwidth, fixed spectrum assignment policies prevent users from dynamically utilizing the unused spectrum, which results in very poor utilization of spectrum. To overcome spectrum scarcity problem, Federal Communications Commission (FCC) allows SUs to access unutilized spectrum if they do not interfere with PUs [12,13,21].…”

Section: Introductionmentioning

confidence: 99%

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Optimizing Spectrum Sharing in Wireless Mesh Network Using Cognitive Technology

Alsarhan

Quttoum

Kilani

2017

Wireless Pers Commun

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In cognitive wireless networks, spectrum owners (primary users, PUs) may lease the unused spectrum to unlicensed users (secondary users, SUs). This spectrum is used to establish a secondary network that serves real time connections. The size of leased spectrum influences both the admitted traffic of SUs and the cost of spectrum. For this spectrum market, we present unsupervised learning paradigm as a means for extracting the optimal control policy for spectrum trading. This policy gives spectrum owner the opportunity to maximize its profit by adapting network resources to the changes in the network status and the market conditions. To meet different requirements, the problem is formulated as reward maximization with penalty for delay. The numerical results show that the proposed machine learning method is able to find an efficient trade-off between profit loss, and average delay for SUs.

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An adaptive interference‐aware and traffic‐aware channel assignment strategy for backhaul networks

Iqbal

Abdullah

Qureshi

2019

Concurrency and Computation

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With the introduction of service-centric applications, the provision of quality of service (QoS) would be a challenge in both classical as well as IoT Networks. 1 The value can be added by monitoring these networks in priority areas and spontaneously levelling the traffic, so that network congestion could be avoided. 2,3 Wireless Mesh Networks (WMNs) are gaining in attraction for metropolitan operations as well as being considered successful for IoT communication. Typically, a wireless mesh network is composed of access points, called Mesh Routers (MRs), which interwork hops to hop to form a larger backhaul network.However, these MRs perform additional functionalities as compared to traditional routers, eg, self-healing. The MRs are usually statically placed and of fixed transmission power in contrast to the classical routers used in ad-hoc networks, which typically vary. Hence, in WMNs', interference can be more controlled. [4][5][6][7][8][9] Similarly, MRs in WMN can have multiple radios and thus interference estimation should be based on all radios, which does not usually pose a difficulty in ad hoc networks as routers are equipped with only a single radio. 10 Hence, a comparatively better performance and throughput can be achieved in WMN against ad-hoc networks. However, MRs equipped with multiple radios can also experience some complexities as parallel transmissions in close proximity cannot occur on the same channel at the same time. Assigning each radio, a different channel is practically not possible as this may result in logical disconnection of the network topology. 11There are 3 non-overlapping channels in IEEE 802.11b that are least interfered eg, channels 1, 6, and 11. [12][13][14][15] Besides the fact that the number of available channels is usually less than the number of radios in proximity, this paper discusses the problem of assigning a limited number of Concurrency Computat Pract Exper. 2020;32:e5650.wileyonlinelibrary.com/journal/cpe

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Channel Assignment for Throughput Optimization in Multichannel Multiradio Wireless Mesh Networks Using Network Coding

Cited by 48 publications

References 34 publications

A novel adaptive spectrum allocation scheme for multi-channel multi-radio wireless mesh networks

A novel adaptive spectrum allocation scheme for multi-channel multi-radio wireless mesh networks

Optimizing Spectrum Sharing in Wireless Mesh Network Using Cognitive Technology

An adaptive interference‐aware and traffic‐aware channel assignment strategy for backhaul networks

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