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Spectrum Allocation of Cognitive Radio Based on Autonomy Evolutionary Algorithm

References 1. Mitola, J. I., G. Q. Maguire. Cognitive Radio: Making Software Radios More Personal. - IEEE Personal Communications, Vol. 6, 1999, No 4, pp. 13-18. 2. Qadir, J. Artificial Intelligence Based Cognitive Routing for Cognitive Radio Networks. - Artificial Intelligence Review, Vol. 45, 2016, No 1, pp. 25-96. 3. Abbas, N., Y. Nasser, K. E. Ahmad. Recent Advances on Artificial Intelligence and Learning Techniques in Cognitive Radio Networks. - Eurasip Journal on Wireless Communications & Networking, Vol

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Optimizing the Capacity of Cognitive Radio Networks with Power Control and Variable Spectrum Allocation

References 1. Ashrafinia, S., Pareek, U., Naeem, M. and Lee, D. (2011) Biogeography-based optimization for joint relay assignment and power allocation in cognitive radio systems. IEEE Symposium on Swarm Intelligence, pp. 1-8. 2. Benaya, A.M., Rosas, A.A. and Shokair, M. (2016) Maximization of minimal throughput using genetic algorithm in MIMO underlay cognitive radio networks. 33rd National Radio Science Conference (NRSC), pp. 141-148. 3. Bhardwaj, P., Panwar, A., Ozdemir, O., Masazade, E., Kasperovich, I

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Next Generation Mobile Communication System with Cognitive Radio, OFDM and Beamforming Tecnique

, Elvino S. Sousa, Collaborative spectrum sensing for opportunistic access in fading environments. New Frontiers in Dynamic Spectrum Access Networks, DySPAN 2005, First IEEE International Symposium on. IEEE, 2005. [5] Ghasemi, Amir, Elvino S. Sousa, Optimization of spectrum sensing for opportunistic spectrum access in cognitive radio networks, 4th IEEE Consumer Transmissions and Networking Conference, 2007. [6] Arun K, Manisha G, Design, comparative study and analysis of CDMA for different modulation techniques, EGYPTIAN INFORMATIC JOURNAL 2015; 16(3): 351

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Multi-Band Spectrum Allocation Algorithm Based on First-Price Sealed Auction

References 1. Broderson, R. W., A. Wolisz, D. Cabric et al. CORVUS: A Cognitive Radio Approach for Usage of Virtual Unlicensed Spectrum. 2. Mitola, J. Cognitive Radio: Making Software Radios More Personal. - IEEE Pers Commun, Vol. 6, 1999, No 4, pp. 13-18. 3. Feng, W. J., R. Jiang, P. Han, W. Liao, H. He. Performance Analysis of Cognitive Radio Spectrum Access with Different Primary User Access Schemes. - Wireless Personal Communications, Vol. 75

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Review on The Performance of Softened Two-Bit Hard Combination Scheme for Cooperative Spectrum Sensing

Used sources [1] H. Sun, “Collaborative Spectrum Sensing in Cognitive Radio Networks,” Ph.D. Dissertation, University of Edinburgh, 2011. [2] S. Pudi, T. Sundara, and N. Padmaja, “Performance analysis of cognitive radio based on cooperative spectrum sensing,” International Journal of Engineering Trends and Technology, Vol.4, Issue 4, 2013. [3] G. Padmavathi and S. Shanmugavel, “Performance Analysis of Centralized Cooperative Spectrum Sensing Technique for Cognitive Radio Networks,” Asian Journal of Scientific Research, Vol.7, No.4, PP. 536

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TCP Performance in Multi-Polling Game Theory-Based IEEE 802.11 Networks


Easy usage and integration with various applications made IEEE 802.11 one of the most used technologies these days, both at home and business premises. Over the years, there have been many additional improvements to the 802.11 standards. Nevertheless, the algorithms and Media Access Control (MAC) layer methods are almost the same as in previous Wi-Fi versions. In this paper, a set of methods to improve the total system capacity is proposed – such as efficient transmit power management based on Game Theory with a custom wireless medium protocol. The transmit power management and wireless medium protocol is verified by both simulation and real application scenarios. The results conclude that the capacity of the proposed wireless medium protocol is overall 20 percent higher than the standard 802.11 wireless medium access protocols. Additional TCP Acknowledgment filtering, which was tested together with the proposed wireless medium access protocol, can provide up to 10-percent-higher TCP throughput in high-density scenarios, especially for asymmetrical traffic cases. The conducted research suggests that efficient power management could result in lighter transmit power allocation rules that are currently set by the local regulators for current Wi-Fi devices. Thus, better propagation characteristics and wireless medium management would lead to an overall higher wireless system capacity.

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Peak to Average Power Ratio Reduction in NC–OFDM Systems

References [1] MITOLA, J. III : Cognitive Radio: An Integrated Agent Archi- tecture for Software Defined Radio, Royal Institute of Technol- ogy (KTH), Stockholm, Sweden, May 2000. [2] RAJBANSHI, R.-WYGLINSKI, A. M.-MINDEN, G. J. : An Efficient Implementation of NC-OFDM Transceivers for Cogni- tive Radios, In Proceedings of the First International Conference on Cognitive Radio Oriented Wireless Networks and Communi- cations, Mykonos Island, Greece, June 2006. [3] O’NEILL, R.-LOPES, L. B. : Envelope Variations and

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Low Power Consumption Digital Clock Recovery Circuit Based on Threshold Crossing

-Complexity Non-Data-Aided Timing Recovery for PAM-based M-ary CPM Receivers, Radioengineering 21 No. 3 (Sep 2012). [9] LOTZE, J.—FAHMY, S. A.—NOGUERA, J.—DOYLE, L. E. : A Model-Based Approach to Cognitive Radio Design, IEEE J. Sel. Areas Commun. 29 No. 2 (Feb 2011). [10] XIONG, F. : Digital Modulation Techniques, Second Edition, Artech House, 2006. [11] CORDESSES, L. : A Direct Digital Synthesis: A Tool for Periodic Wave Generation (Part I)a, IEEE Signal Processing Magazine 21 No. 4 (July 2004), 50–54. [12] CESSNA, R. J.—DONALD, L. M. : Phase

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"Implicature-Laden" Elicitations in Talk Radio Shows

References Allison, D. 1991. "Textual explicitness and paragmatic inferencing: The case of ‘Hypothetical - Real’ contrasts in written instructional scientific discourse in English." Journal of Pragmatics 15: 373-393. Carston, R. 2002. "Linguistic Meaning, Communicated Meaning and Cognitive Pragmatics." Mind and Language 17 (1&2): 127-148. Carston, R. 2004. "Explicature and Semantics." In Semantics: A Reader , S. Davis & B. Gillon (eds), 817-845. Oxford: Oxford University Press

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Electromagnetic Compatibility Studies: LTE BS vs. Aeronautical Radionavigation Services in 694-790 MHz Frequency Band

using cognitive base-stations for UMTS Lte,” IEEE Communications Magazine, Volume 49, Issue 8, IEEE, 2011, pp. 152-159. [5] X. Hognian, S. Hakola “The investigation of power control schemes for a device-to-device communication integrated into Ofdma cellular system,” in 2010 IEEE 21st International Symposium on Personal Indoor and Mobile Radio Communications, 2010, pp. 1775-1780. [6] C.U. Castellanos et al. “Performance of Uplink Fractional Power Control in UTRAN LTE,” in 2008 Vehicular Technology Conference, 2008, pp. 2517-2521. [7] R. Love et al. “Downlink

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