Distributed Spectrum Sensing and Access in Cognitive Radio Networks With Energy Constraint

We design distributed spectrum sensing and access strategies for opportunistic spectrum access (OSA) under an energy constraint on secondary users. Both the continuous and the bursty traffic models are considered for different applications of the secondary network. In each slot, a secondary user sequentially decides whether to sense, where in the spectrum to sense, and whether to access. By casting this sequential decision-making problem in the framework of partially observable Markov decision processes, we obtain stationary optimal spectrum sensing and access policies that maximize the throughput of the secondary user during its battery lifetime. We also establish threshold structures of the optimal policies and study the fundamental tradeoffs involved in the energy-constrained OSA design. Numerical results are provided to investigate the impact of the secondary user's residual energy on the optimal spectrum sensing and access decisions.

[1]  Panagiotis Papadimitratos,et al.  A bandwidth sharing approach to improve licensed spectrum utilization , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[2]  Anthony R. Cassandra,et al.  Optimal Policies for Partially Observable Markov Decision Processes , 1994 .

[3]  William S. Lovejoy,et al.  Some Monotonicity Results for Partially Observed Markov Decision Processes , 1987, Oper. Res..

[4]  M. Littman The Witness Algorithm: Solving Partially Observable Markov Decision Processes , 1994 .

[5]  Brian M. Sadler,et al.  Dynamic spectrum access in WLAN channels: empirical model and its stochastic analysis , 2006, TAPAS '06.

[6]  Joseph Mitola Cognitive Radio for Flexible Mobile Multimedia Communications , 2001, Mob. Networks Appl..

[7]  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.

[8]  N. Zhang,et al.  Algorithms for partially observable markov decision processes , 2001 .

[9]  Ananthram Swami,et al.  Joint Design and Separation Principle for Opportunistic Spectrum Access , 2006, ASILOMAR 2006.

[10]  Edward J. Sondik,et al.  The optimal control of par-tially observable Markov processes , 1971 .

[11]  Ananthram Swami,et al.  A Survey of Dynamic Spectrum Access: Signal Processing and Networking Perspectives , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[12]  Friedrich Jondral,et al.  Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency , 2004, IEEE Communications Magazine.

[13]  Qing Zhao,et al.  Distributed Sensing and Access in Cognitive Radio Networks , 2008, 2008 IEEE 10th International Symposium on Spread Spectrum Techniques and Applications.

[14]  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.

[15]  Alexander M. Wyglinski,et al.  A Spectrum Surveying Framework for Dynamic Spectrum Access Networks , 2009, IEEE Transactions on Vehicular Technology.

[16]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[17]  Qing Zhao,et al.  Detecting, tracking, and exploiting spectrum opportunities in unslotted primary systems , 2008, 2008 IEEE Radio and Wireless Symposium.

[18]  I-Jeng Wang,et al.  Characterization of Spectrum Activities in the U.S. Public Safety Band for Opportunistic Spectrum Access , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[19]  Q. Zhao,et al.  Decentralized cognitive mac for dynamic spectrum access , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[20]  Michael L. Littman,et al.  Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes , 1997, UAI.

[21]  Brian M. Sadler,et al.  Optimal Dynamic Spectrum Access via Periodic Channel Sensing , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[22]  Edward J. Sondik,et al.  The Optimal Control of Partially Observable Markov Processes over a Finite Horizon , 1973, Oper. Res..

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