Multi-Strategy Dynamic Spectrum Access in Cognitive Radio Networks: Modeling, Analysis and Optimization
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摘要
Dynamic spectrum access(DSA) based on cognitive radios(CR) technique is an effective approach to address the "spectrum scarcity" issue. However, traditional CR-enabled DSA system employs only single DSA strategy, which might not be suited to the dynamic network environment. In this paper, we propose a multi-strategy DSA(MS-DSA) system, where the primary and the secondary system share spectrum resources with multiple DSA strategies simultaneously. To analyze the performance of the proposed MS-DSA system, we model it as a continuous-time Markov chain(CTMC) and derive the expressions to compute the corresponding performance metrics. Based on this, we define a utility function involving the concerns of effective throughput, interference quantity on primary users, and spectrum leasing cost. Two optimization schemes, named as spectrum allocation and false alarm probability selection, are proposed to maximize the utility function. Finally, numerical simulations are provided to validate our analysis and demonstrate that the performance can be significantly improved caused by virtues of the proposed MS-DSA system.
Dynamic spectrum access(DSA) based on cognitive radios(CR) technique is an effective approach to address the "spectrum scarcity" issue. However, traditional CR-enabled DSA system employs only single DSA strategy, which might not be suited to the dynamic network environment. In this paper, we propose a multi-strategy DSA(MS-DSA) system, where the primary and the secondary system share spectrum resources with multiple DSA strategies simultaneously. To analyze the performance of the proposed MS-DSA system, we model it as a continuous-time Markov chain(CTMC) and derive the expressions to compute the corresponding performance metrics. Based on this, we define a utility function involving the concerns of effective throughput, interference quantity on primary users, and spectrum leasing cost. Two optimization schemes, named as spectrum allocation and false alarm probability selection, are proposed to maximize the utility function. Finally, numerical simulations are provided to validate our analysis and demonstrate that the performance can be significantly improved caused by virtues of the proposed MS-DSA system.
Dynamic spectrum access(DSA) based on cognitive radios(CR) technique is an effective approach to address the "spectrum scarcity" issue. However, traditional CR-enabled DSA system employs only single DSA strategy, which might not be suited to the dynamic network environment. In this paper, we propose a multi-strategy DSA(MS-DSA) system, where the primary and the secondary system share spectrum resources with multiple DSA strategies simultaneously. To analyze the performance of the proposed MS-DSA system, we model it as a continuous-time Markov chain(CTMC) and derive the expressions to compute the corresponding performance metrics. Based on this, we define a utility function involving the concerns of effective throughput, interference quantity on primary users, and spectrum leasing cost. Two optimization schemes, named as spectrum allocation and false alarm probability selection, are proposed to maximize the utility function. Finally, numerical simulations are provided to validate our analysis and demonstrate that the performance can be significantly improved caused by virtues of the proposed MS-DSA system.
引文
[1]Q.Zhao and B.Sadler,“A survey of dynamic spectrum access.”Signal Processing Magazine,IEEE,vol.24,no.3,pp.79-89,may 2007.
[2]M.Buddhikot,“Understanding dynamic spectrum access:Models,taxonomy and challenges,”Dynamic Spectrum Access Networks,2nd IEEE International Symposium,2007,pp.649-663.
[3]Vishakha Ramani;Sanjay K.Sharma,“Cognitive Radios:A Survey On Spectrum Sensing,Security and Spectrum Handoff,”China Communications,vol.14,no.11,pp.185-208,2017.
[4]I.F.Akyildiz,W.Y.Lee,M.C.Vuran,and S.Mohanty,“Next generation/dynamic spectrum access/cognitive radio wireless networks:Asurvey,”Computer Networks,vol.50,no.13,pp.2127-2159,2006.
[5]N.Cheng,N.Zhang,N.Lu,X.Shen,J.Mark,and F.Liu,“Opportunistic spectrum access for crvanets:A game-theoretic approach,”Vehicular Technology,IEEE Transactions,vol.63,no.1,pp.237-251,Jan 2014.
[6]Y.S.Chen,C.H.Cho,I.You,and H.C.Chao,“Across-layer protocol of spectrum mobility and handover in cognitive lte networks,”Simulation Modelling Practice and Theory,vol.19,no.8,pp.1723-1744,2011.
[7]H.Kim,J.Choi,and K.G.Shin,“Hierarchical market competition in a duopoly super wi-fi spectrum market,”Selected Areas in Communications,IEEE Journal,vol.31,no.11,pp.2580-2591,2013.
[8]J.Chapin and W.Lehr,“Cognitive radios for dynamic spectrum access-the path to market success for dynamic spectrum access technology,”Communications Magazine,IEEE,vol.45,no.5,pp.96-103,2007.
[9]B.Wang,Z.Ji,and K.Liu,“Primary-prioritized markov approach for dynamic spectrum access,”Dynamic Spectrum Access Networks,2nd IEEEInternational Symposium,2007,pp.507-515.
[10]B.Wang,Z.Ji,K.Liu,and T.Clancy,“Primary-prioritized markov approach for dynamic spectrum allocation,”Wireless Communications,IEEETransactions,vol.8,no.4,pp.1854-1865,2009.
[11]P.K.Tang and Y.Chew,“On the modeling and performance of three opportunistic spectrum access schemes,”Vehicular Technology,IEEETransactions,vol.59,no.8,pp.4070-4078,2010.
[12]P.P.Chen,Q.Y.Zhang,Y.L.Zhang and Y.Wang,“Performance analysis of spectrum sharing mechanisms in cognitive radio networks,”EUR-ASIP Journal on Wireless Communications and Networking,vol.2011,no.1,pp.1-15,2011.
[13]V.Tumuluru,P.Wang,D.Niyato,and W.Song,“Performance analysis of cognitive radio spectrum access with prioritized traffic,”Vehicular Technology,IEEE Transactions,vol.61,no.4,pp.1895-1906,2012.
[14]M.M.Buddhikot,P.Kolodzy,S.Miller,K.Ryan,and J.Evans,“Dimsumnet:new directions in wireless networking using coordinated dynamic spectrum,”World of Wireless Mobile and Multimedia Networks,2005.Sixth IEEE International Symposium,pp.78-85.
[15]Y.Wang,Y.Zhang,Q.Zhang,and S.Wu,“Optimal selection of false alarm probability for dynamic spectrum access,”Communications Letters,IEEE,vol.17,no.5,pp.844-847,May2013.
[16]D.Niyato and E.Hossain,“Market-equilibrium,competitive,and cooperative pricing for spectrum sharing in cognitive radio networks:Analysis and comparison,”Wireless Communications,IEEE Transactions,vol.7,no.11,pp.4273-4283,November 2008.
[17]P.Humblet and M.Azizoglu,“On the bit error rate of lightwave systems with optical amplifi ers,”Lightwave Technology,vol.9,no.11,pp.1576-1582,nov 1991.
[18]C.Jiang,Y.Chen,K.Liu,and Y.Ren,“Renewal-theoretical dynamic spectrum access in cognitive radio network with unknown primary behavior,”Selected Areas in Communications,IEEE Journal,vol.31,no.3,pp.406-416,2013.
[19]H.C.Tijms,A fi rst course in stochastic models.Wiley.com,2003.
[20]D.P.Bertsekas,Constrained Optimization and Lagrange Multiplier Methods.Academic Press,1982.
1 In this paper,we use a spectrum unit to represent a basic physical transmission resource,e.g.,a resource block(RB)in a OFDMA-based system or a spread spectrum code-sequence in a CD-MA-based system.
2 In this study,we assume that the energy detection-based sensing[17]is adopted for the sensing operation due to its low complexity and the capability of fast detection.Moreover since the SUdevices have usually small size and limited power,the sensing functionality is implemented in the SAP.
[2]M.Buddhikot,“Understanding dynamic spectrum access:Models,taxonomy and challenges,”Dynamic Spectrum Access Networks,2nd IEEE International Symposium,2007,pp.649-663.
[3]Vishakha Ramani;Sanjay K.Sharma,“Cognitive Radios:A Survey On Spectrum Sensing,Security and Spectrum Handoff,”China Communications,vol.14,no.11,pp.185-208,2017.
[4]I.F.Akyildiz,W.Y.Lee,M.C.Vuran,and S.Mohanty,“Next generation/dynamic spectrum access/cognitive radio wireless networks:Asurvey,”Computer Networks,vol.50,no.13,pp.2127-2159,2006.
[5]N.Cheng,N.Zhang,N.Lu,X.Shen,J.Mark,and F.Liu,“Opportunistic spectrum access for crvanets:A game-theoretic approach,”Vehicular Technology,IEEE Transactions,vol.63,no.1,pp.237-251,Jan 2014.
[6]Y.S.Chen,C.H.Cho,I.You,and H.C.Chao,“Across-layer protocol of spectrum mobility and handover in cognitive lte networks,”Simulation Modelling Practice and Theory,vol.19,no.8,pp.1723-1744,2011.
[7]H.Kim,J.Choi,and K.G.Shin,“Hierarchical market competition in a duopoly super wi-fi spectrum market,”Selected Areas in Communications,IEEE Journal,vol.31,no.11,pp.2580-2591,2013.
[8]J.Chapin and W.Lehr,“Cognitive radios for dynamic spectrum access-the path to market success for dynamic spectrum access technology,”Communications Magazine,IEEE,vol.45,no.5,pp.96-103,2007.
[9]B.Wang,Z.Ji,and K.Liu,“Primary-prioritized markov approach for dynamic spectrum access,”Dynamic Spectrum Access Networks,2nd IEEEInternational Symposium,2007,pp.507-515.
[10]B.Wang,Z.Ji,K.Liu,and T.Clancy,“Primary-prioritized markov approach for dynamic spectrum allocation,”Wireless Communications,IEEETransactions,vol.8,no.4,pp.1854-1865,2009.
[11]P.K.Tang and Y.Chew,“On the modeling and performance of three opportunistic spectrum access schemes,”Vehicular Technology,IEEETransactions,vol.59,no.8,pp.4070-4078,2010.
[12]P.P.Chen,Q.Y.Zhang,Y.L.Zhang and Y.Wang,“Performance analysis of spectrum sharing mechanisms in cognitive radio networks,”EUR-ASIP Journal on Wireless Communications and Networking,vol.2011,no.1,pp.1-15,2011.
[13]V.Tumuluru,P.Wang,D.Niyato,and W.Song,“Performance analysis of cognitive radio spectrum access with prioritized traffic,”Vehicular Technology,IEEE Transactions,vol.61,no.4,pp.1895-1906,2012.
[14]M.M.Buddhikot,P.Kolodzy,S.Miller,K.Ryan,and J.Evans,“Dimsumnet:new directions in wireless networking using coordinated dynamic spectrum,”World of Wireless Mobile and Multimedia Networks,2005.Sixth IEEE International Symposium,pp.78-85.
[15]Y.Wang,Y.Zhang,Q.Zhang,and S.Wu,“Optimal selection of false alarm probability for dynamic spectrum access,”Communications Letters,IEEE,vol.17,no.5,pp.844-847,May2013.
[16]D.Niyato and E.Hossain,“Market-equilibrium,competitive,and cooperative pricing for spectrum sharing in cognitive radio networks:Analysis and comparison,”Wireless Communications,IEEE Transactions,vol.7,no.11,pp.4273-4283,November 2008.
[17]P.Humblet and M.Azizoglu,“On the bit error rate of lightwave systems with optical amplifi ers,”Lightwave Technology,vol.9,no.11,pp.1576-1582,nov 1991.
[18]C.Jiang,Y.Chen,K.Liu,and Y.Ren,“Renewal-theoretical dynamic spectrum access in cognitive radio network with unknown primary behavior,”Selected Areas in Communications,IEEE Journal,vol.31,no.3,pp.406-416,2013.
[19]H.C.Tijms,A fi rst course in stochastic models.Wiley.com,2003.
[20]D.P.Bertsekas,Constrained Optimization and Lagrange Multiplier Methods.Academic Press,1982.
1 In this paper,we use a spectrum unit to represent a basic physical transmission resource,e.g.,a resource block(RB)in a OFDMA-based system or a spread spectrum code-sequence in a CD-MA-based system.
2 In this study,we assume that the energy detection-based sensing[17]is adopted for the sensing operation due to its low complexity and the capability of fast detection.Moreover since the SUdevices have usually small size and limited power,the sensing functionality is implemented in the SAP.