Qiang Peng, Youchen Dong^*, Weimin Wu, Haiyang Rao, Gan Liu

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Wuhan University of Technology, Wuhan, Hubei, China.
Wuhan National Laboratory for Optoelectronics, Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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Abstract: Dynamic spectrum access (DSA) scheme in Cognitive Radio (CR) can solve the current problem of scarce spectrum resource effectively, in which the unlicensed users (i.e. Second Users, SUs) can access the licensed spectrum in opportunistic ways without interference to the licensed users (i.e. Primary Users, PUs). However, SUs have to vacate the spectrum because of PUs coming, in this case the spectrum switch occurs, and it leads to the increasing of SUs’ delay. In this paper, we proposed a Variable Service Rate (VSR) scheme with the switch buffer as to real-time traffic (such as VoIP, Video), in order to decrease the average switch delay of SUs and improve the other performance. Different from previous studies, the main characteristics of our studying of VSR in this paper as follows: 1) Our study is on the condition of real-time traffic and we establish three-dimension Markov model; 2) Using the internal optimization strategy, including switching buffer, optimizing buffer and variable service rate; 3) As to the real-time traffic, on the condition of meeting the Quality of Service(QoS) on dropping probability, the average switch delay is decreased as well as improving the other performance. By extensive simulation and numerical analysis, the performance of real-time traffic is improved greatly on the condition of ensuring its dropping probability. The result fully demonstrates the feasibility and effectiveness of the variable service rate scheme.

Keywords: Cognitive Radio; Dynamic Spectrum Access; Variable Service Rate; Optimal Buffer; Markov Decision

Cite this paper: Peng, Q. , Dong, Y. , Wu, W. , Rao, H. and Liu, G. (2013) Dynamic Spectrum Access Scheme of Variable Service Rate and Optimal Buffer-Based in Cognitive Radio. Communications and Network, 5, 232-237. doi: 10.4236/cn.2013.53B2043.

References

[1]   W. Lehr and L. W. McKnight, “Wireless Internet access: 3Gvs.WiFi?,” Telecommun. policy, Competition Wirel., Spectr., Service Technol. Wars, Vol. 27, No. 5/6, 2003, pp. 351-370.

[2]   M. A. McHenry, “NSF Spectrum Occupancy Measurements Project Summary,” Shared Spectrum Company Report, Aug. 2005.

[3]   X. Zhu, L. Shen and T. P. Yum, “Analysis of Cognitive Radio Spectrum Access with Optimal Channel Reservation,” IEEE Communications Letters, Vol. 11, No. 4, pp. 304-306, Apr. 2007. doi:10.1109/LCOM.2007.348282

[4]   G. Liu, X. Zhu and L. Hanzo, “Dynamic Spectrum Sharing Models for Cognitive Radio Aided Ad Hoc Networks and Their Performance Analysis,” Proceeding of IEEE GLOBE-COM 2011.

[5]   E. W. M. Wong and C. H. Foh, “Analysis of Cognitive Radio Spectrum Access with Finite User Polulation,” IEEE Communications Letters, Vol. 13, No. 5, 2009, pp. 294-296. doi:10.1109/LCOMM.2009.082113

[6]   G. Liu, X. Zhu and L. Hanzo, “Impact of Variance of Heterogeneous Spectrum on Performance of Cognitive Radio Ad Hoc Network,” IEEE ICC, Vol. 1, No. 1, Jun 2012.

[7]   Tumuluru, V.K.;Ping Wang; Niyato, D.and Wei Song, “Performance Analysis of Cognitive Radio Spectrum Access With Prioritized Traffic,” IEEE Transactions on Vehicular Technology, Vol. 61, No. 4, 2012, pp. 1895-1906. doi:10.1109/TVT.2012.2186471

[8]   P. Zhou, Y. S. Chang and John A. Copeland, “Capacity and Delay Scaling in Cognitive Radio AdHoc Networks: Impact of Primary User Activity,” IEEE Globecom, 2010.

[9]   W. T. Huang and X. B. Wang, “Throughput and Delay Scaling of General Cognitive Networks,” IEEE Infocom, 2011.

[10]   N. Mokari, H. Saeedi and KeivanNavaie, “Channel Coding Increases the Achievable Rate of the Cognitive Networks,” IEEE Communications Letters, Vol. 17, No. 3, March 2013, pp. 495-498.