Primary User Detection in Distributed Cognitive Radio Networks under Timing Inaccuracy

In this paper we study energy detection for primary user signals in the case of distributed Cognitive Radio (CR) networks. We concentrate on the effects of interference caused by other CR users due to timing misalignments and propose a novel mathematical model for calculating the effects of interfering nodes on energy detection and derive closed-form solutions for the probabilities of detection and false alarm. We verify our model by simulations and show that the impact of interference is severe in the presence of timing errors in distributed CR networks. To the best of authors' knowledge, the problem of inaccurate timing has not been investigated before. However, as we show in this paper, without interference cancellation or precise synchronization, timing errors will degrade sensing performance heavily in decentralized secondary networks and the throughput of CR networks will be significantly lower as well. The results obtained in this work can be used to guide the design and performance analysis of energy-based detection in distributed CR networks when accurate time synchronization is not available.

[1]  R.W. Brodersen,et al.  Implementation issues in spectrum sensing for cognitive radios , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[2]  Tom Burr,et al.  Introduction to Matrix Analytic Methods in Stochastic Modeling , 2001, Technometrics.

[3]  Kay Römer,et al.  Wireless sensor networks: a new regime for time synchronization , 2003, CCRV.

[4]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[5]  Larry J. Greenstein,et al.  An empirically based path loss model for wireless channels in suburban environments , 1999, IEEE J. Sel. Areas Commun..

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

[7]  Saurabh Ganeriwal,et al.  Timing-sync protocol for sensor networks , 2003, SenSys '03.

[8]  Hassan M. El-Sallabi,et al.  An Additive Model as a Physical Basis for Shadow Fading , 2007, IEEE Transactions on Vehicular Technology.

[9]  J. I. Mararm,et al.  Energy Detection of Unknown Deterministic Signals , 2022 .

[10]  C. Cordeiro,et al.  C-MAC: A Cognitive MAC Protocol for Multi-Channel Wireless Networks , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

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

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

[13]  Edgar Nett,et al.  Clock synchronization for wireless local area networks , 2000, Proceedings 12th Euromicro Conference on Real-Time Systems. Euromicro RTS 2000.

[14]  Vladimir I. Kostylev,et al.  Energy detection of a signal with random amplitude , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[15]  Milton Abramowitz,et al.  Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables , 1964 .

[16]  Petri Mähönen,et al.  Evaluation of Spectrum Occupancy in Indoor and Outdoor Scenario in the Context of Cognitive Radio , 2007, 2007 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[17]  D. Owen Handbook of Mathematical Functions with Formulas , 1965 .

[18]  Mohamed-Slim Alouini,et al.  On the Energy Detection of Unknown Signals Over Fading Channels , 2007, IEEE Transactions on Communications.