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HYBRID SHARING AND POWER ALLOCATION USING WATERFILLING ALGORITHM FOR MIMO-OFDM BASED COGNITIVE RADIO NETWORK


Affiliations
1 I.K. Gujral Punjab Technical University, India
2 Guru Nanak Dev Engineering College, India
 

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In order to optimize power allocation, Orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) network allows flexible spectrum and adaptive capability. Decreased capacity due to subcarrier cancelation and out of band reduction can be compensated while employing multiple inputs and multiple outputs (MIMO) along with OFDM based CR. MIMO allows better beam forming and directivity due to multiple transmit and receive antenna. Here we have implemented water filling mechanism with channel state information (CSI) for optimal power allocation under hybrid spectrum sharing scenario such as overlay, underlay and interweave. Main objective is to maximize overall capacity of cognitive radio network in downlink while considering interference constraint imposed by primary user and maximum transmit power constraint at secondary user. Simulation results demonstrate waterfilling approach for hybrid scenario in MIMO-OFDM based CRN.
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  • Federal Communications Commission, “Spectrum Policy Task Force”, Available at: https://www.fcc.gov/document/spectrum-policy-task-force, Accessed at 2002.

  • J. Mitola and G.Q. Maguire, “Cognitive Radio: Making Software Radios More Personal”, IEEE Communications Magazine, Vol 6, No.4, pp. 13-18, 1999.

  • S. Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications”, IEEE Journal on Selected Areas in Communications, Vol. 23, No. 2, pp. 201-220, 2005.

  • F. Akyildiz, W.Y. Lee, M. C. Vuran and S. Mohanty, “Next Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey”, Computer Networks, Vol. 50, No. 13, pp. 2127-2159, 2006.

  • R. V. Nee and R. Prasad, “OFDM for Wireless Multimedia Communication”, Artech House, 2000.

  • B. FarhangvBoroujeny and R. Kempter, “Multicarrier Communication Techniques for Spectrum Sensing and Communication in Cognitive Radios”, IEEE Communications Magazine, Vol. 46, No. 4, pp. 80-85, 2008.

  • U. Berthold, F. Jondral, S. Brandes and M. Schnell, “OFDM-Based Overlay Systems: A Promising Approach for Enhancing Spectral Efficiency”, IEEE Communications Magazine, Vol. 45, No. 12, pp. 52-58, 2007.

  • D. Bepari and D. Mitra, “Improved Power Loading Scheme for Orthogonal Frequency Division Multiplexing based Cognitive Radio”, IET Communications, Vol. 9, No. 16, pp. 2033-2040. 2015.

  • H. Yamaguchi, “Active Interference Cancellation Technique for MB-OFDM Cognitive Radio”, Proceedings of European Conference on Microwave, pp. 1105-1108, 2004.

  • S. Brandes, I. Cosovic and M. Schnell, “Reduction of Outof-Band Radiation in OFDM Systems by Insertion of Cancellation Carriers,” IEEE Communication Letters, Vol 10, No.6, pp. 420-422, 2006.

  • A. J. Paulraj, “An Overview of MIMO communications-A Key to Gigabit Wireless”, Proceedings of the IEEE, Vol. 92, No. 2, pp. 198-218, 2004.

  • D. Gesbert, M. Shafi, D. Shiu, P.J. Smith and A. Naguib, “From Theory to Practice: An Overview of MIMO SpaceTime Coded Wireless Systems,” IEEE Journal on Selected Areas in Communications, Vol. 21, No. 3, pp. 281-302, 2003. [13] H. Bolcskei and E. Zurich, “MIMO-OFDM Wireless Systems: Basics, Perspectives, and Challenges”, IEEE Wireless Communications, Vol. 13, No. 4, pp. 31-37, 2006.

  • W. Zhang, X.G. Xia and K.B. Letaief, “Space Time/Frequency Coding for MIMO-OFDM in Next Generation Broadband Wireless System”, IEEE Wireless Communication, Vol. 14, No. 3, pp. 32-43, 2007.

  • D. Zhang, Z. Tian and G. Wei, “Spatial Capacity of Narrowband vs. Ultra-Wideband Cognitive Radio Systems”, IEEE Transactions on Wireless Communications, Vol. 7, No. 11, pp. 4670-4680, 2008.

  • M. G. Khoshkholgh, K. Navaie and H. Yanikomeroglu, “On the Impact of the Primary Network Activity on the Achievable Capacity of Spectrum Sharing over Fading Channels”, IEEE Transactions on Wireless Communications, Vol. 8, No. 4, pp. 2100-2111, 2009.

  • Kuldeep Kumar and Manwinder Singh, “Proposed Water Filling Model in a MIMO System”, International Journal of Emerging Technology and Advanced Engineering, Vol. 1, No. 2, pp. 1-12, 2011.

  • S. Wang, W. Shi and C. Wang, “Energy-Efficient Resource Management in OFDM Based Cognitive Radio Networks under Channel Uncertainty”, IEEE Transactions on Communications, Vol. 63, No. 9, pp. 3092-3102, 2015.

  • A. Goldsmith, S.A. Jafar, I. Maric and S. Srinivasa, “Breaking Spectrum Gridlock with Cognitive Radios: An Information Theoretic Perspective”, Proceedings of the IEEE, Vol. 97, No. 5, pp. 894-914, 2009.

  • Z. Wu and B. Natarajan, “Interference Tolerant Agile Cognitive Radio: Maximize Channel Capacity of Cognitive Radio”, Proceedings of International Conference on Consumer Communications and Networking, pp. 1027- 1031, 2007.

  • Y.J. Jang and K.B. Letaief, “An Efficient Resource Allocation Scheme for Spatial Multiuser Access in MIMOOFDM/OFDM Systems”, IEEE Transactions on Information Theory, Vol. 53, No. 1, pp. 107-116, 2005.

  • T. Weiss, J. Hillenbrand, A. Krohn and F.K. Jondral, “Mutual Interference in OFDM Based Spectrum Pooling Systems”, Proceedings of International Conference on IEEE Vehicular Technology, pp. 1873-1877, 2004.

  • G. Bansal, M.J. Hossain and V.K. Bhargava, “Optimal and Suboptimal Power Allocation Schemes for OFDM-Based Cognitive Radio Systems”, IEEE Transactions on Wireless Communications, Vol. 7, No. 11, pp. 4710-4718, 2008.

  • G. Bansal, M.J. Hossain, V.K. Bhargava and T. Le-Ngoc, “Subcarrier and Power Allocation for OFDMA-Based Cognitive Radio Systems with Hybrid Overlay and Underlay Spectrum Access Mechanism”, IEEE Transactions on Vehicular Technology, Vol. 62, No. 3, pp. 1111-1122, 2013.

  • M.R. Bharti and D. Ghosh, “Hybrid Spectral Shaping and Power Loading for OFDM based Cognitive Radio”, Proceedings of International Conference on Advanced Networks and Telecommunications Systems, pp. 1-6, 2016.

  • Qilin Qi, Andrew Minturn and Yaoqing Yang, “An Efficient Water-Filling Algorithm for Power Allocation in OFDMBased Cognitive Radio System”, Proceedings of International Conference on Systems and Informatics, pp. 2069-2073, 2012.

  • E. Bedeer, O.A. Dobre, M.H. Ahmed and K.E. Baddour, “A Novel Algorithm for Rate/Power Allocation in OFDM Based Cognitive Radio Systems with Statistical Interference Constraints”, Proceedings of International Conference on Global Communications, pp. 3504-3509, 2013.

  • S Shahraki, K. Mohamed-Pour and L. Vangelista, “Sum Capacity Maximization for MIMO-OFDMA based Cognitive Radio Networks”, Physical Communication, Vol. 10, pp. 106-115, 2014.

  • S. Boyd and L. Vandenberghe, “Convex Optimization”, Cambridge University Press, 2004.


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  • HYBRID SHARING AND POWER ALLOCATION USING WATERFILLING ALGORITHM FOR MIMO-OFDM BASED COGNITIVE RADIO NETWORK

Abstract Views: 213  |  PDF Views: 119

Authors

Sandeep Kumar Jain
I.K. Gujral Punjab Technical University, India
Baljeet Kaur
Guru Nanak Dev Engineering College, India

Abstract


In order to optimize power allocation, Orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) network allows flexible spectrum and adaptive capability. Decreased capacity due to subcarrier cancelation and out of band reduction can be compensated while employing multiple inputs and multiple outputs (MIMO) along with OFDM based CR. MIMO allows better beam forming and directivity due to multiple transmit and receive antenna. Here we have implemented water filling mechanism with channel state information (CSI) for optimal power allocation under hybrid spectrum sharing scenario such as overlay, underlay and interweave. Main objective is to maximize overall capacity of cognitive radio network in downlink while considering interference constraint imposed by primary user and maximum transmit power constraint at secondary user. Simulation results demonstrate waterfilling approach for hybrid scenario in MIMO-OFDM based CRN.

References