Competition-based channel selection for cognitive radio networks

Yao, Yong; Ngoga, Said Rutabayiro; Erman, David; Popescu, Adrian

doi:10.1109/wcnc.2012.6214006

Cited by 9 publications

(71 citation statements)

References 9 publications

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“…−η 1 r i in the min-expression above is the cost of stopping. Thus, denoting D (1) −η1 by α (1) , whenever the state is of the form (r i , t) an optimal policy is as follows:…”

Section: B Characterization Of Neppsmentioning

confidence: 99%

“…We are concerned in this paper with a class of resource allocation problems in wireless networks, in which competing nodes need to acquire a resource, such as a physical radio relay (see the geographical forwarding example later in Section III) or a channel (as in a cognitive radio network [1], [2]), when a sequence of such resources "arrive" over time, and are available only fleetingly for acquisition. In this paper, formulating such a problem for two nodes as a stochastic game, we consider the completely observable and partially observable cases, and provide characterizations of the Nash Equilibrium Policy Pairs (NEPP).…”

Section: Introductionmentioning

confidence: 99%

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Competitive Selection of Ephemeral Relays in Wireless Networks

Naveen

Altman

Kumar

2017

IEEE J. Select. Areas Commun.

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Abstract-We consider a setting in which two nodes (referred to as forwarders) compete to choose a relay node from a set of relays, as they ephemerally become available (e.g., wake up from a sleep state). Each relay, when it arrives, offers a (possibly different) "reward" to each forwarder. Each forwarder's objective is to minimize a combination of the delay incurred in choosing a relay and the reward offered by the chosen relay.As an example, we develop the reward structure for the specific problem of geographical forwarding over a network of sleepwake cycling relays.We study two variants of the generic relay selection problem, namely, the completely observable (CO) case where, when a relay arrives, both forwarders get to observe both rewards, and the partially observable (PO) case where each forwarder can only observe its own reward. Formulating the problem as a two person stochastic game, we characterize solution in terms of Nash Equilibrium Policy Pairs (NEPPs). For the CO case we provide a general structure of the NEPPs. For the PO case we prove that there exists an NEPP within the class of threshold policy pairs.We then consider the particular application of geographical forwarding of packets in a shared network of sleep-wake cycling wireless relays. For this problem, for a particular reward structure, using realistic parameter values corresponding to TelosB wireless mote, we numerically compare the performance (in terms of cost to both forwarders) of the various NEPPs and draw the following key insight: even for moderate separation between the two forwarders, the performance of the various NEPPs is close to the performance of a simple strategy where each forwarder behaves as if the other forwarder is not present. We also conduct simulation experiments to study the end-to-end performance of the simple forwarding policy.

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“…−η 1 r i in the min-expression above is the cost of stopping. Thus, denoting D (1) −η1 by α (1) , whenever the state is of the form (r i , t) an optimal policy is as follows:…”

Section: B Characterization Of Neppsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Competitive Selection of Ephemeral Relays in Wireless Networks

Naveen

Altman

Kumar

2017

IEEE J. Select. Areas Commun.

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“…Moreover, we let R s .q, hjg, 1 / and T w .q, hjg, 1 /, respectively, denote the FTP-based effect factors of R s and T w under the specific setting of q, h, g and 1 . They can be computed according to Equation (25).…”

Section: Hybrid Decision-makingmentioning

confidence: 99%

On prioritised opportunistic spectrum access in cognitive radio cellular networks

Yao

Popescu

2014

Trans Emerging Tel Tech

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Cognitive radio (CR) networks allow secondary users (SUs) to opportunistically access licensed spectrum, thus providing efficient use of radio resources. Different studies carried out on CR networks have focused on the procedure of spectrum handoff of SUs such as the data transmission in a communication that can be carried out in different channels. In this paper, we consider cellular networks enhanced with facilities for CR communication where a user with a call in progress moves across neighbouring cells, that is, the so‐called inter‐cell handoff. Our model assumes that the cell gives priority to inter‐cell handoff calls over the calls originating within it. A finite queue is used in every cell for SUs, and a fixed number of buffer slots are reserved for the inter‐handoff SU calls. With these considerations, we study the transmission performance of SUs by using Markov chains‐based modelling approach. The numerical analysis is validated by simulation experiments. We also suggest a fuzzy logic‐based hybrid decision‐making algorithm to select the best solution for inter‐handoff prioritisation. The goal is to optimise the transmission performance of SUs by leveraging their requirements on service completion throughput and waiting time in each cell. Copyright © 2014 John Wiley & Sons, Ltd.

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“…Every SOP is described in a fourdimensional space in terms of geographical point (referred We ignore at the moment other metrics like, e.g., interference level. Additionally, information about the expected temporal availability of these SOP s is also assumed, which can be obtained based on traffic measurements and analysis as well as prediction methods like the ones suggested in [1].…”

Section: System Modelmentioning

confidence: 99%

“…To achieve this, statistics collected over a long time period, different prediction models, e.g., Moving Average (MA), Auto Regressive (AR), Autoregressive moving average model (ARMA) and suitable decision making process based on solutions like in [1] are used.…”

Section: System Modelmentioning

confidence: 99%

On routing in Cognitive Radio Networks

Popescu

Fiedler

2012

2012 9th International Conference on Communications (COMM)

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Cognitive Radio Networks (CRNs) are expected to address and to resolve important technological and operational challenges of future networks, such as Dynamic Spectrum Access (DSA), routing in heterogeneous networks and provision of Quality of Experience (QoE) for different applications. Accordingly, a number of new terminal and network functionalities are required to solve the technical problems and to provide efficient management of CRNs. The paper advances a new solution for routing in CRNs, providing communication between Secondary Users (SUs) occupying different so-called Spectrum Opportunities (SOPs), i.e., portions of spectrum not occupied by Primary Users (PUs). This entails solving a complex process composed by two fundamental elements. These elements are multi-constraint routing and multi-dimensional adaptation for multiple cognitive radio dimensions like space, frequency, power and time. The goal of the paper is to develop optimization algorithms necessary to provide end-to-end (e2e) routing paths for communication between SUs with associated QoE demands.

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Competition-based channel selection for cognitive radio networks

Cited by 9 publications

References 9 publications

Competitive Selection of Ephemeral Relays in Wireless Networks

Competitive Selection of Ephemeral Relays in Wireless Networks

On prioritised opportunistic spectrum access in cognitive radio cellular networks

On routing in Cognitive Radio Networks

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