The Impact of Spectrum Sensing Frequency and Packet-Loading Scheme on Multimedia Transmission Over Cognitive Radio Networks

Recently, multimedia transmission over cognitive radio networks (CRNs) becomes an important topic due to the CR's capability of using unoccupied spectrum for data transmission. Conventional work has focused on typical quality-of-service (QoS) factors such as radio link reliability, maximum tolerable communication delay, and spectral efficiency. However, there is no work considering the impact of CR spectrum sensing frequency and packet-loading scheme on multimedia QoS. Here the spectrum sensing frequency means how frequently a CR user detects the free spectrum. Continuous, frequent spectrum sensing could increase the medium access control (MAC) layer processing overhead and delay, and cause some multimedia packets to miss the receiving deadline, and thus decrease the multimedia quality at the receiver side. In this research, we will derive the math model between the spectrum sensing frequency and the number of remaining packets that need to be sent, as well as the relationship between spectrum sensing frequency and the new channel availability time during which the CRN user is allowed to use a new channel (after the current channel is re-occupied by primary users) to continue packet transmission. A smaller number of remaining packets and a larger value of new channel availability time will help to transmit multimedia packets within a delay deadline. Based on the above relationship model, we select appropriate spectrum sensing frequency under single-channel case, and study the trade-offs among the number of selected channels, optimal spectrum sensing frequency, and packet-loading scheme under multi-channel case. The optimal spectrum sensing frequency and packet-loading solutions for multi-channel case are obtained by using the combination of Hughes-Hartogs and discrete particle swarm optimization (DPSO) algorithms. Our experiments of JPEG2000 packet-stream and H.264 video packet-stream transmission over CRN demonstrate the validity of our spectrum sensing frequency selection and packet-loading scheme.

[1]  Yan Liu,et al.  Skeleton-Network Reconfiguration Based on Topological Characteristics of Scale-Free Networks and Discrete Particle Swarm Optimization , 2007, IEEE Transactions on Power Systems.

[2]  Ian F. Akyildiz,et al.  STOD-RP: A Spectrum-Tree Based On-Demand Routing Protocol for Multi-Hop Cognitive Radio Networks , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[3]  Marwan Krunz,et al.  Probabilistic Path Selection in Opportunistic Cognitive Radio Networks , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[4]  Jiang Hao.  An efficient bit loading algorithm for OFDM system , 2010 .

[5]  Ian F. Akyildiz,et al.  Optimal spectrum sensing framework for cognitive radio networks , 2008, IEEE Transactions on Wireless Communications.

[6]  Hang Su,et al.  Opportunistic MAC Protocols for Cognitive Radio Based Wireless Networks , 2007, 2007 41st Annual Conference on Information Sciences and Systems.

[7]  Jean-Lien C. Wu,et al.  Performance analysis of rate control with scaling QoS parameters for multimedia transmissions , 2003 .

[8]  Rozeha A. Rashid,et al.  Performance Evaluation of Video Transmission Over Ultrawideband WPAN , 2009, 2009 Third Asia International Conference on Modelling & Simulation.

[9]  Zhao Zhijin,et al.  Cognitive Radio Decision Engine Based on Binary Chaotic Particle Swarm Optimization , 2013 .

[10]  Danijela Cabric,et al.  White paper: Corvus: A cognitive radio approach for usage of virtual unlicensed spectrum , 2004 .

[11]  James Kennedy,et al.  Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[12]  John G. Apostolopoulos,et al.  On multiple description streaming with content delivery networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

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

[14]  Mihaela van der Schaar,et al.  Queuing-Based Dynamic Channel Selection for Heterogeneous Multimedia Applications Over Cognitive Radio Networks , 2008, IEEE Transactions on Multimedia.

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

[16]  Miao Pan,et al.  Cost design for opportunistic multi-hop routing in Cognitive Radio networks , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.

[17]  Hüseyin Arslan,et al.  A survey of spectrum sensing algorithms for cognitive radio applications , 2009, IEEE Communications Surveys & Tutorials.

[18]  Hamid Sharif,et al.  On Energy Efficient Encryption for Video Streaming in Wireless Sensor Networks , 2010, IEEE Transactions on Multimedia.

[19]  Rajarathnam Chandramouli,et al.  Reliable Multimedia Transmission Over Cognitive Radio Networks Using Fountain Codes , 2008, Proceedings of the IEEE.

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

[21]  迪克·胡斯·哈托格斯.  Ensemble modem structure for imperfect transmission media , 1986 .

[22]  R. Chandramouli,et al.  Secondary Spectrum Access with LT Codes for Delay-Constrained Applications , 2007, 2007 4th IEEE Consumer Communications and Networking Conference.

[23]  Andrew Michael James.  A link-quality-aware graph model for cognitive radio network routing topology management , 2007 .