Opportunistic Channel-Aware Spectrum Access for Cognitive Radio Networks with Interleaved Transmission and Sensing

Opportunistic spectrum access in a cognitive radio network has been a challenge due to the dynamic nature of spectrum availability and possible collisions between the primary user (PU) and the secondary user (SU). To maximize the spectrum utilization, we propose a spectrum access strategy where SU's packets are interleaved with periodic sensing to detect PU's return. Similar to earlier works on distributed opportunistic scheduling (DOS), we formulate the sensing/probing/access process as a maximum rate-of-return problem in the optimal stopping theory framework and show that the optimal channel access strategy is a pure threshold policy. We consider a realistic channel and system model by taking into account channel fading and sensing errors. We jointly optimize the rate threshold and the packet transmission time to maximize the average throughput of SU, while limiting interference to PU. Our numerical results show that significant throughput gains can be achieved with the proposed scheme compared to other well-known schemes. Our work sheds light on designing DOS protocols for cognitive radio with optimal transmission time that takes into account the dynamic nature of PUs.

[1]  James R. Zeidler,et al.  Opportunistic Spectrum Access for Cognitive Radio Networks withMultiple Secondary Users , 2013, IEEE Transactions on Wireless Communications.

[2]  Özgür B. Akan,et al.  Energy-Efficient Packet Size Optimization for Cognitive Radio Sensor Networks , 2012, IEEE Transactions on Wireless Communications.

[3]  Shaojie Tang,et al.  Almost optimal accessing of nonstochastic channels in cognitive radio networks , 2012, 2012 Proceedings IEEE INFOCOM.

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

[5]  Ananthram Swami,et al.  Distributed Spectrum Sensing and Access in Cognitive Radio Networks With Energy Constraint , 2009, IEEE Transactions on Signal Processing.

[6]  Marwan Krunz,et al.  Throughput-efficient sequential channel sensing and probing in cognitive radio networks under sensing errors , 2009, MobiCom '09.

[7]  Junshan Zhang,et al.  Distributed Opportunistic Scheduling for Ad Hoc Networks With Random Access: An Optimal Stopping Approach , 2009, IEEE Transactions on Information Theory.

[8]  Junshan Zhang,et al.  Distributed opportunistic scheduling for ad-hoc communications: an optimal stopping approach , 2007, MobiHoc '07.

[9]  Brian M. Sadler,et al.  Opportunistic Spectrum Access via Periodic Channel Sensing , 2008, IEEE Transactions on Signal Processing.

[10]  Xi Fang,et al.  Taming Wheel of Fortune in the Air: An Algorithmic Framework for Channel Selection Strategy in Cognitive Radio Networks , 2013, IEEE Transactions on Vehicular Technology.

[11]  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.

[12]  Panganamala Ramana Kumar,et al.  Channel Aware Distributed Scheduling for Exploiting Multi-Receiver Diversity and Multiuser Diversity in Ad-Hoc Networks: A Unified PHY/MAC Approach , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

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

[14]  Lei Yang,et al.  Pricing-Based Decentralized Spectrum Access Control in Cognitive Radio Networks , 2013, IEEE/ACM Transactions on Networking.

[15]  Yonghong Zeng,et al.  Sensing-Throughput Tradeoff for Cognitive Radio Networks , 2008, IEEE Trans. Wirel. Commun..

[16]  Yiyang Pei,et al.  Energy-Efficient Design of Sequential Channel Sensing in Cognitive Radio Networks: Optimal Sensing Strategy, Power Allocation, and Sensing Order , 2011, IEEE Journal on Selected Areas in Communications.

[17]  Yiyang Pei,et al.  Sensing-Throughput Tradeoff in Cognitive Radio Networks: How Frequently Should Spectrum Sensing be Carried Out? , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[18]  Erik G. Larsson,et al.  Spectrum Sensing for Cognitive Radio : State-of-the-Art and Recent Advances , 2012, IEEE Signal Processing Magazine.

[19]  Sai Shankar Nandagopalan,et al.  IEEE 802.22: An Introduction to the First Wireless Standard based on Cognitive Radios , 2006, J. Commun..

[20]  G. Simons Great Expectations: Theory of Optimal Stopping , 1973 .

[21]  Mingyan Liu,et al.  Optimal Channel Probing and Transmission Scheduling for Opportunistic Spectrum Access , 2007, IEEE/ACM Transactions on Networking.

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

[23]  Zhi Ding,et al.  Short Paper: On Optimal Sensing and Transmission Strategies for Dynamic Spectrum Access , 2008, 2008 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[24]  Geoffrey Ye Li,et al.  Optimal sequential detection in cognitive radio networks , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[25]  David Siegmund,et al.  Great expectations: The theory of optimal stopping , 1971 .

[26]  Dan Xu,et al.  Opportunistic spectrum access in cognitive radio networks: when to turn off the spectrum sensors , 2008, WICON 2008.

[27]  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.

[28]  Mingyan Liu,et al.  Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study , 2009, IEEE Transactions on Mobile Computing.

[29]  Kang G. Shin,et al.  Attack Prevention for Collaborative Spectrum Sensing in Cognitive Radio Networks , 2011, IEEE Journal on Selected Areas in Communications.