Fair Bandwidth Allocation in Wireless Mesh Networks With Cognitive Radios

Tang, Jian; Hincapié, Roberto; Xue, Guoliang; Zhang, Weiyi; Ramírez, Bustamante

doi:10.1109/tvt.2009.2038478

Cited by 47 publications

(6 citation statements)

References 33 publications

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“…To maximize throughput, the total bandwidth allocated to non gateway nodes is as large as possible and, to provide fairness, the allocated bandwidth is as even as possible. This solution was later adapted in [19] for CWMNs. Instead of allocating bandwidth to routes, our solution schedules channel access of all MPs, including gateways, to prevent bandwidth wastage and improve throughput.…”

Section: Schedulingmentioning

confidence: 99%

Adaptive multihop scheduling for IEEE 802.11s multiradio cognitive wireless mesh networks

Roy

Grégoire

Dziong

2013

Proceedings of the 8th ACM Workshop on Performance Monitoring and Measurement of Heterogeneous Wireless and Wired Networks

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Wireless mesh networks (WMN) are efficient and low cost solutions for the deployment of broadband access in various environments. To support real-time applications such as multimedia and emergency services throughout the network, WMNs must provide appropriate quality of service (QoS). While the capacity and the bandwidth availability of single radio WMNs may severely limit QoS for such traffic, multiradio cognitive WMNs (CWMN) can overcome these restrictions and provide better QoS mechanisms. This paper describes a scheduling algorithm with an integrated backpressure mechanism for CWMN. This algorithm ensures that the available bandwidth is properly shared considering the type of traffic to forward, the distance of the clients from the portal and the fluctuating conditions of the links. The performance of our new scheduling algorithm is evaluated in a simulated environment. We show that, while increasing throughput, our algorithm not only achieves nearly perfect fairness, but can also prevent bandwidth wastage.

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Section: Schedulingmentioning

confidence: 99%

Adaptive multihop scheduling for IEEE 802.11s multiradio cognitive wireless mesh networks

Roy

Grégoire

Dziong

2013

Proceedings of the 8th ACM Workshop on Performance Monitoring and Measurement of Heterogeneous Wireless and Wired Networks

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“…Subcarrier and power allocation optimization is formulated as a multi-dimensional 0-1 knapsack problem (MDKP) and a greedy max-min algorithm is proposed to solve it. In [11], two fair bandwidth-allocation problems based on a simple max-min fairness model and lexicographical max-min (LMM) fairness model are proposed to achieve the tradeoff between fairness and throughput in wireless mesh networks. In [12], two distributed algorithms to optimally allocate subcarriers and power in OFDMA ad hoc cognitive radio network have been proposed to offer either throughput maximization or energy efficiency subject to tolerable interference introduced to the primary network, and a joint subcarrier and power allocation method has been derived by Lagrange dual algorithm to maximize the capacity of the cognitive radio networks.…”

Section: Related Workmentioning

confidence: 99%

“…where 0 N is the one-side PSD of AWGN. To sum up, the total interferences to th m PU on subcarrier k introduced by th n source node can be expressed as (11) where k  is the probability that a subcarrier k is truly occupied. Given that the cognitive network identified subcarrier k is vacant, k  can be expressed as…”

Section: Problem Formulationmentioning

confidence: 99%

Joint Subcarriers and Power Allocation with Imperfect Spectrum Sensing for Cognitive D2D Wireless Multicast

2013

KSII TIIS

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Wireless multicast is considered as an effective transmission mode for the future mobile social contact services supported by Long Time Evolution (LTE). Though wireless multicast has an excellent resource efficiency, its performance suffers deterioration from the channel condition and wireless resource availability. Cognitive Radio (CR) and Device to Device (D2D) are two solutions to provide potential resource. However, resource allocation for cognitive wireless multicast based on D2D is still a great challenge for LTE social networks. In this paper, a joint sub-carriers and power allocation model based on D2D for general cognitive radio multicast (CR-D2D-MC) is proposed for Orthogonal Frequency-Division Multiplexing (OFDM) LTE systems. By opportunistically accessing the licensed spectrum, the maximized capacity for multiple cognitive multicast groups is achieved with the condition of the general scenario of imperfect spectrum sensing, the constrains of interference to primary users (PUs) and an upper-bound power of secondary users (SUs) acting as multicast source nodes. Furthermore, the fairness for multicast groups or unicast terminals is guaranteed by setting a lower-bound number of the subcarriers allocated to cognitive multicast groups. Lagrange duality algorithm is adopted to obtain the optimal solution to the proposed CR-D2D-MC model. The simulation results show that the proposed algorithm improves the performance of cognitive multicast groups and achieves a good balance between capacity and fairness.

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“…The literature on cooperative communication mostly emphasizes fair allocation of bandwidth [16,17], optimal allocation of power [6,[18][19][20][21] or energy efficiency of the network [3,22]. However, the physical layer fairness measured by fair dissipation of the battery power of the relays taking part in the cooperation has not been thoroughly addressed [23,24].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Smartphone Relay Selection Based on Fair Power Utilization for Network Coverage Extension

Ayub

Rakocevic

2019

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This paper presents a relay selection algorithm based on fair battery power utilization for extending mobile network coverage and capacity by using a cooperative communication strategy where mobile devices can be utilized as relays. Cooperation improves the network performance for mobile terminals, either by providing access to out-of-range devices or by facilitating multi-path network access to connected devices. In this work, we assume that all mobile devices can benefit from using other mobile devices as relays and investigate the fairness of relay selection algorithms. We point out that signal strength based relay selection inevitably leads to unfair relay selection and devise a new algorithm that is based on fair utilization of power resources on mobile devices. We call this algorithm Credit based Fair Relay Selection (CF-RS) and in this paper show through simulation that the algorithm results in fair battery power utilization, while providing similar data rates compared with traditional approaches. We then extend the solution to demonstrate that adding incentives for relay operation adds clear value for mobile devices in the case they require relay service. Typically, mobile devices represent self-interested users who are reluctant to cooperate with other network users, mainly due to the cost in terms of power and network capacity. In this paper, we present an incentive based solution which provides clear mutual benefit for mobile devices and demonstrate this benefit in the simulation of symmetric and asymmetric network topologies. The CF-RS algorithm achieves the same performance in terms of achievable data rate, Jain’s fairness index and utility of end devices in both symmetric and asymmetric network configurations.

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Fair Bandwidth Allocation in Wireless Mesh Networks With Cognitive Radios

Cited by 47 publications

References 33 publications

Adaptive multihop scheduling for IEEE 802.11s multiradio cognitive wireless mesh networks

Adaptive multihop scheduling for IEEE 802.11s multiradio cognitive wireless mesh networks

Joint Subcarriers and Power Allocation with Imperfect Spectrum Sensing for Cognitive D2D Wireless Multicast

Cooperative Smartphone Relay Selection Based on Fair Power Utilization for Network Coverage Extension

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