In this paper, we propose an adaptive and occupancy-based channel selection
for unreliable cognitive radio networks

Fdida, Serge

Khalife, Hicham

Rehmani, Mubashir Husain

Viana, Aline Carneiro

English

arXiv

National audienceNous présentons une stratégie dynamique pour le choix de canaux dans un réseau radio cognitif. Notre stratégie se base essentiellement sur l'estimation de l'occupation du canal radio provoquée par l'activité des noeuds primaires plus prioritaires sur les canaux en questions. Notre technique, et grâce à une écoute permanante sur les canaux, dote les noeuds cognitifs de la capacité d'inférer les canaux les plus adaptés à une communication cognitive. En effet, notre stratégie permet d'assurer une fiabilité accrue dans les communications en évitant les canaux surchargés. Par des simulations, nous validons notre contribution en montrant qu'elle assure un taux de paquets remis en succès, dans différents scénarios, largement supérieur au cas où le choix de canaux s'effectue aléatoirement. Par ailleurs, nous montrons également que notre stratégie permet un nombre supérieur de voisins sur chaque canal que le contexte aléatoire. Cela constitue un résultat prometteur en faveur de son utilisation dans un contexte multi-saut en présence d'un algorithme de routage

Carneiro Viana, Aline

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Adaptive and Occupancy-based Channel Selection forunreliable Cognitive Radio NetworksMubashir Husain Rehmani, Aline Carneiro Viana, Hicham Khalife, SergeFdidaTo cite this version:Mubashir Husain Rehmani, Aline Carneiro Viana, Hicham Khalife, Serge Fdida. Adaptiveand Occupancy-based Channel Selection for unreliable Cognitive Radio Networks. 11e`mesRencontres Francophones sur les Aspects Algorithmiques des Te´le´communications (AlgoTel2009), Jun 2009, Carry-Le-Rouet, France. 2009. <inria-00441154>HAL Id: inria-00441154https://hal.inria.fr/inria-00441154Submitted on 14 Dec 2009HAL is a multi-disciplinary open accessarchive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come fromteaching and research institutions in France orabroad, or from public or private research centers.L’archive ouverte pluridisciplinaire HAL, estdestine´e au de´poˆt et a` la diffusion de documentsscientifiques de niveau recherche, publie´s ou non,e´manant des e´tablissements d’enseignement et derecherche franc¸ais ou e´trangers, des laboratoirespublics ou prive´s.Adaptive and occupancy-based channelselection for unreliable cognitive radionetworksM. H. Rehmani,1,2 A. C. Viana,2 H. Khalife,1 and S. Fdida 11 LIP6/Universite´ Pierre et Marie Curie – Paris 6, France2 ASAP/INRIA Saclay - Ilde France sud, FranceNous pre´sentons une strate´gie dynamique pour le choix de canaux dans un re´seau radio cognitif. Notre strate´gie se baseessentiellement sur l’estimation de l’occupation du canal radio provoque´e par l’activite´ des nœuds primaires plus prio-ritaires sur les canaux en questions. Notre technique, et graˆce a` une e´coute permanante sur les canaux, dote les nœudscognitifs de la capacite´ d’infe´rer les canaux les plus adapte´s a` une communication cognitive. En effet, notre strate´gie per-met d’assurer une fiabilite´ accrue dans les communications en e´vitant les canaux surcharge´s. Par des simulations, nousvalidons notre contribution en montrant qu’elle assure un taux de paquets remis en succe`s, dans diffe´rents sce´narios,largement supe´rieur au cas ou` le choix de canaux s’effectue ale´atoirement. Par ailleurs, nous montrons e´galement quenotre strate´gie permet un nombre supe´rieur de voisins sur chaque canal que le contexte ale´atoire. Cela constitue unre´sultat prometteur en faveur de son utilisation dans un contexte multi-saut en pre´sence d’un algorithme de routage.1 IntroductionDue to limited available spectrum and fixed spectrum assignment policy in today’s wireless networks,radio spectrum is used inefficiently. To counter this issue, Cognitive Radio Networks (CRNs) are designedto allow cognitive radio (CR) nodes (i) utilizing free parts of unlicensed spectrum as well as (ii) opportu-nistically exploiting licensed frequency bands in silent periods of licensed users, called primary radio (PR)nodes [ALVM06, MM99].Note that the traffic pattern of primary users is of key importance here : if we know that a particularchannel is heavily used by a PR node and it tends to occupy it for a long period of time, that channel wouldbe less likely available for a CR node. Because of this PR’s high time occupancy, the usability of the chan-nels by CR nodes becomes uncertain. In addition, since PR nodes operating over different channels havedifferent activity patterns, depending on the technology they are using and the environment characteristics,a hardly predictable and time-variant occupancy can be also perceived. Thus, it is essential and, however,extremely challenging to correctly select channels allowing reliable communication among CR nodes aswell as channels that increase the number of CR receivers. This constitutes the goal of this paper.In this paper, we present a new strategy for adaptive and occupancy-based channel selection in CRNs.Our strategy empowers CR nodes with the ability to infer, based on information regarding PR occupancy,the less occupied channel to use. CR nodes then use the proposed strategy to select channels for transmissionand overhearing. Hence, by exploiting overhearing and PR occupancy properties, our strategy allows notonly increasing the network reliability – since less PR-occupied channels will be selected – but also thedelivery ratio – since a high number of CR nodes will overhear the selected channel.2 Adaptive and occupancy-based channel selectionWe are considering an ad-hoc infrastructure-less architecture of Cognitive Radio Network. In this archi-tecture, only CR-CR communications will occur. Cognitive Radio (CR) nodes are highly frequency agile.Due to PR activity over every channel, intermittent connectivity of links occurs, requiring CRNs to behighly opportunistic. CR nodes are able to communicate over multiple channels. Within the network, twonodes can communicate if they use at least one common channel and if they are within the transmissionrange of each other. The spectrum used by PR and CR nodes consists of N Channels C = {1,2,3, . . . ,N},where channels availability for CR nodes is highly time variant and dependent on the PR activity variabilityover every channel.M. H. Rehmani, A. C. Viana, H. Khalife, and S. FdidaAfter sensing the channels in the CRN, each CR node makes a list of detected channels in the network.Each CR node then classifies the sensed channels in a decreasing order of availability, and selects fortransmission and/or overhearing the best weighted channel. Channels’ weight Pchannel is calculated basedon PR and CR nodes’ occupancy :Pchannel = e−PROccupancy×CROccupancyCROccupancy = 1−PROccupancySince PR and CR occupancy are inversely proportional, selection of the less occupied channel by PR nodesalso implies the selection of the most used channel by CR nodes. Hence, the use of the best channel givenby the highest value of Pchannel allows improving network reliability as well as increasing the delivery ratio.3 Simulation Results and ConclusionTo assess the performance of the proposed approach, two performance metrics are evaluated : (i) theaverage delivery ratio, which is ratio of packet received by a particular CR node over total packets sent inthe network and (ii) the average number of receivers, which is the real quantity of receivers per node id. Inorder to simulate message losses, a probability of receiving a message is assigned to each channel. Resultsshown below are generated for an average of 500 simulations, along with 95% of confidence interval, for anetwork of 10 CR nodes.00.20.40.60.81.00 1 2 3 4 5 6 7 8 9Average Delivery RatioCR Nodes’ IDRD : nb. channels = 5, PR Nodes = 15RD : nb. channels = 8, PR Nodes = 15RD : nb. channels = 10, PR Nodes = 15RD : nb. channels = 15, PR Nodes = 15OS : nb. channels = 5, PR Nodes = 15OS : nb. channels = 8, PR Nodes = 15OS : nb. channels = 10, PR Nodes = 15OS : nb. channels = 15, PR Nodes = 15(a)0123456789100 1 2 3 4 5 6 7 8 9Average Number of ReceiversCR Nodes’ IDRD : nb. channels = 5, PR Nodes = 15RD : nb. channels = 8, PR Nodes = 15RD : nb. channels = 10, PR Nodes = 15RD : nb. channels = 15, PR Nodes = 15OS : nb. channels = 5, PR Nodes = 15OS : nb. channels = 8, PR Nodes = 15OS : nb. channels = 10, PR Nodes = 15OS : nb. channels = 15, PR Nodes = 15(b)FIG. 1: Average delivery ratio and number of receivers in a CRN, for random (RD) and our adaptive strategy (OS).Fig. 1 compare random (RD) and our strategy (OS) results for the delivery ratio and number of receiversof these two strategies, as a function of the CR nodes’ ID. The results show how the number of channelsimpacts the average delivery ratio and the average number of receivers for the two strategies. In particular,by selecting the channel with highest Pchannel, CR nodes are trying to access best channel in terms ofoccupancy, for transmitting and overhearing. Hence, as shown in Fig. 1, our strategy considerably increasesthe delivery ratio and the number of receivers. Our strategy guarantees the delivery of 80% to 85% ofmessages, contrarily to less than 45% to 40% for the random strategy (cf. Fig. 1(a)). Note that the increaseof the number of channels has a negative impact on the delivery ratio for the random strategy. This is due tothe fact that the probability of a CR node to randomly select for overhearing, the same channel that anotherCR node has randomly selected for transmitting, decreases with the increase of the number of channels.Moreover, our strategy guarantees from 38% to 40% more nodes reception than with the random strategy(cf. Fig. 1(b)). Our solution increases the delivery ratio and the number of receivers since it selects thechannel with low primary activity and have a high probability to encounter overhearing CR nodes.In summary, our experiments reveal that, by increasing the number of channels, our proposed strategyconsiderably increases the average delivery ratio and the average number of receivers, when compared tothe random strategy. In addition, contrarily to random strategy, our proposed strategy guarantees obtaininghigh delivery ratio proportional to the number of available channels. This shows how good our strategy isin allowing CR nodes taking profit of available channels.Re´fe´rences[ALVM06] Ian F. Akyildiz, Won-Yeol Lee, Mehmet C. Vuran, and Shantidev Mohanty. Next generation/dynamic spectrum ac-cess/cognitive radio wireless networks : a survey. Computer Networks : The International Journal of Computer andTelecommunications Networking, 50 , Issue 13 :2127 – 2159, 2006.[MM99] J. Mitola and G. Q. Maguire. Cognitive radio : Making software radios more personal. IEEE Personal Communications,6, no. 4 :13–18, 1999.

Adaptive and Occupancy-based Channel Selection for unreliable Cognitive Radio Networks

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   Adaptive and Occupancy­based Channel Selection for Unreliable Cognitive Radio Networks (CRNs)fMubashir Husain Rehmani, Aline Carneiro Viana, Hicham Khalife, and Serge Fdida※   Our Solution   Each CR node sense channels   Classify sensed channels in the decreasing order of               availability for transmission and/or overhearing   Based upon PR and CR Occupancy   Approaches are present [3] that provides PR Occupancy   Assign weights to channels based upon PR Occupancy    and CR Occupancy.   PR Occupancy   Ratio of the PR nodes utilizing the ⇒   channels over total number of PR nodes on that channel.   Based on PR nodes that are in activity and is based on PR nodes' state (i.e. if they are active – ON – or not – OFF)O    CR Occupancy   Number of active CR nodes competing ⇒   for the channel    CR Occupancy = 1 – PROccupancy     Channels' weight is calculated based on formula:Pchannel = e­PROccupancy x CROccupancy  ※   Simulation Results   Comparison:  Our Strategy (OS) and Random (RD),       Single­Hop Scenario, network of 10 CR and 15 PR nodes   OS guarantees the delivery of  80­85% messages,    contrarily to less than 45­40% for the RD.     OS also guarantees from 38­40% more nodes reception    than with the RD   Advantages   Increased  throughput      Reliable communication   High number of CR nodes overhears the channel      Nodes make local decision   Decrease disconnectivity of CR nodes   By using channels with less PR nodes   Empowers CR nodes with the ability to infer, based on    information regarding PR Occupancy, the less occupied    channels to use※   Future Work                      Multi­hop scenarios,  opportunistically forwarding       mechanisms, and comparison with related approaches※   Cognitive Radio Networks (CRNs)C※   Motivation   Limited available spectrum in today's wireless networks   Fixed spectrum assignment policy   Geographical and temporal utilization of spectrum varies              from 15%­85% (FCC) [1]   Results in the:   Inefficiency in spectrum usage   Creation of spectrum holes※   Cognitive Radio NodesIn CRNs, Cognitive Radio (CR) nodes:   Utilize free parts of unlicensed spectrum   Opportunistically exploit licensed band※   Operating Constraints   CR transmissions should not degrade the reception quality           of PR nodes   CR node should immediately interrupt its transmission                whenever a neighboring PR activity is detected [2]※   Challenges   Frequency agility   CR nodes rapidly changes the channels   Multiple channels   CR nodes can access to a range of channels   Intermittent connectivity   Due to PR activity, links are not consistent   Unreliability   Difficulty for CR nodes to select a particular channel※   Traffic Pattern and Activity of PR     Nodes   Traffic pattern of PR nodes are of key importance   Highly used channel by PR nodes in terms of agility and time   Less availability of that channel to CR node⇒   Occupancy is time­variant and hardly predictable※  Adaptive and occupancy­based Channel Selection※   Our Goal   Select channel that is less occupied by PR nodes as       well as increase the number of CR receivers   To understand the behavior of the mechanism before start       with multi­hop scenario※   How?       By exploiting PR Occupancy and OverhearingH. Khalife : Hicham.Khalife@lip6.fr (LIP6/UPMC)(S. Fdida: Serge.Fdida@lip6.fr (LIP6/UPMC)M. H. Rehmani : Mubashir.Rehmani@lip6.fr (ASAP/INRIA and LIP6/UPMC)A. C. Viana : Aline.Viana@inria.fr (ASAP/INRIA)                                                                                                                                                   Algotel 2009 Poster SessionAlgotel 2009 Poster Session                   ReferencesT. Yucek and H. Arslan, “A Survey of Spectrum Sensing Algorithms for  Cognitive Radio Applications”, IEEE Communications Surveys and Tutorials, Vol. 11, No. 1, First Quarter 2009[3]H. Khalife, S. Ahuja, N. Malouch, and M. Krunz, Probabilistic path selection in opportunistic cognitive radio networks”, in Proceeding of the IEEE GlobeCom Conference, 30 Nov­4 Dec 2008, pp. 1­5[2]I. F. Akyildiz, W. ­Y. Lee, M. C. Vuran, and S. Mohanty, “Next Generation/ dynamic spectrum access/ cognitive radio wireless networks: a survey”, Computer Networks: The International Journal of Computer and Telecommunications Networking, Vol. 50, Issue 13, pp. 2127­2159, 2006[1]

Adaptive and occupancy-based channel selection for unreliable cognitive radio networks

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