Two-dimensional POMDP-based opportunistic spectrum access in time-varying environment with fading channels

In this research, we study the problem of opportunistic spectrum access (OSA) in a time-varying environment with fading channels, where the channel state is characterized by both channel quality and the occupancy of primary users (PUs). First, a finite-state Markov channel model is introduced to represent a fading channel. Second, by probing channel quality and exploring the activities of PUs jointly, a two-dimensional partially observable Markov decision process framework is proposed for OSA. In addition, a greedy strategy is designed, where a secondary user selects a channel that has the best-expected data transmission rate to maximize the instantaneous reward in the current slot. Compared with the optimal strategy that considers future reward, the greedy strategy brings low complexity and relatively ideal performance. Meanwhile, the spectrum sensing error that causes the collision between a PU and a secondary user (SU) is also discussed. Furthermore, we analyze the multiuser situation in which the proposed single-user strategy is adopted by every SU compared with the previous one. By observing the simulation results, the proposed strategy attains a larger throughput than the previous works under various parameter configurations.

[1]  Hamid Reza Karimi,et al.  Geolocation databases for white space devices in the UHF TV bands: Specification of maximum permitted emission levels , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[2]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[3]  Ananthram Swami,et al.  Joint Design and Separation Principle for Opportunistic Spectrum Access in the Presence of Sensing Errors , 2007, IEEE Transactions on Information Theory.

[4]  Ananthram Swami,et al.  Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework , 2007, IEEE Journal on Selected Areas in Communications.

[5]  Dong-Ho Cho,et al.  Comparison of channel information acquisition schemes in cognitive radio system , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[6]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[7]  Shaojie Tang,et al.  Optimal Frequency-Temporal Opportunity Exploitation for Multichannel Ad Hoc Networks , 2012, IEEE Transactions on Parallel and Distributed Systems.

[8]  Ananthram Swami,et al.  Bursty Traffic in Energy-Constrained Opportunistic Spectrum Access , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[9]  Santosh Pandey,et al.  IEEE 802.11af: a standard for TV white space spectrum sharing , 2013, IEEE Communications Magazine.

[10]  Paramvir Bahl,et al.  SenseLess: A database-driven white spaces network , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[11]  Yonghong Zeng,et al.  Opportunistic spectrum access for energy-constrained cognitive radios , 2008, IEEE Transactions on Wireless Communications.

[12]  Brian M. Sadler,et al.  Dynamic Spectrum Access: Signal Processing, Networking, and Regulatory Policy , 2006, ArXiv.

[13]  Alagan Anpalagan,et al.  Decision-Theoretic Distributed Channel Selection for Opportunistic Spectrum Access: Strategies, Challenges and Solutions , 2013, IEEE Communications Surveys & Tutorials.

[14]  Mingyan Liu,et al.  Optimality of Myopic Sensing in Multi-Channel Opportunistic Access , 2008, 2008 IEEE International Conference on Communications.

[15]  Bhaskar Krishnamachari,et al.  On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance , 2007, IEEE Transactions on Wireless Communications.

[16]  Maria-Gabriella Di Benedetto,et al.  A Survey on MAC Strategies for Cognitive Radio Networks , 2012, IEEE Communications Surveys & Tutorials.

[17]  Saleem A. Kassam,et al.  Finite-state Markov model for Rayleigh fading channels , 1999, IEEE Trans. Commun..

[18]  Ananthram Swami,et al.  A Decision-Theoretic Framework for Opportunistic Spectrum Access , 2007, IEEE Wireless Communications.

[19]  Vijay K. Bhargava,et al.  Opportunistic Spectrum Access in Cognitive Radio Networks: A Queueing Analytic Model and Admission Controller Design , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[20]  Ian F. Akyildiz,et al.  NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey , 2006, Comput. Networks.

[21]  Anant Sahai,et al.  Some Fundamental Limits on Cognitive Radio , 2004 .

[22]  Brian M. Sadler,et al.  A Survey of Dynamic Spectrum Access , 2007, IEEE Signal Processing Magazine.

[23]  Ian F. Akyildiz,et al.  A survey on spectrum management in cognitive radio networks , 2008, IEEE Communications Magazine.

[24]  Kang G. Shin,et al.  Cognitive radios for dynamic spectrum access: from concept to reality , 2010, IEEE Wireless Communications.

[25]  Alagan Anpalagan,et al.  Opportunistic Spectrum Access in Cognitive Radio Networks: Global Optimization Using Local Interaction Games , 2012, IEEE Journal of Selected Topics in Signal Processing.

[26]  Yonghong Zeng,et al.  Opportunistic spectrum access for energy-constrained cognitive radios , 2009 .

[27]  Alagan Anpalagan,et al.  Opportunistic Spectrum Access in Unknown Dynamic Environment: A Game-Theoretic Stochastic Learning Solution , 2012, IEEE Transactions on Wireless Communications.

[28]  Kang G. Shin,et al.  Secure Cooperative Sensing in IEEE 802.22 WRANs Using Shadow Fading Correlation , 2011, IEEE Transactions on Mobile Computing.

[29]  Zhongding Lei,et al.  IEEE 802.22: The first cognitive radio wireless regional area network standard , 2009, IEEE Communications Magazine.

[30]  Qihui Wu,et al.  Spatial-Temporal Opportunity Detection for Spectrum-Heterogeneous Cognitive Radio Networks: Two-Dimensional Sensing , 2013, IEEE Transactions on Wireless Communications.

[31]  Ingrid Moerman,et al.  Geolocation database beyond TV white spaces? Matching applications with database requirements , 2012, 2012 IEEE International Symposium on Dynamic Spectrum Access Networks.