Abstract
The wireless communication has undergone a revolution due to advancements in technology. For each new user or application to be a part of communication network the preliminary requirement is the allocation of frequency spectrum band. This frequency band is a limited resource and it is impossible to expand its boundaries. So the need is to employ intelligent, adaptive and reconfigurable communication systems which can investigate the requiremenmts of the end user and assign the requisite resources in contrast to the traditional communication systems which allocate a fixed amount of resource to the user under adaptive, autonomic and opportunistic cognitive radio environment. Cognitive radio technology has emerged from software defined radios wherein the key parameters of interest are frequency, power and modulation technique adopted. The role of cognitive radio is to alter these parameters under ubiquitous situations. The spectrum sensing is an important task to determine the availability of the vacant channels to be utilised by the secondary users without posing any harmful interference to the primary users. In multi carrier communication using digital signal processing techniques, filter bank multi carrier has an edge over other technologies in terms of bandwidth and spectral efficiency. The present paper deals with the multi rate FIR decimation and interpolation filter approach for physical layer of cognitive radio under binary symmetric fading channel environment.
Similar content being viewed by others
References
Mitola, J., & Maguire, G. Q. (1999). Cognitive radios: Making software radios more personal. IEEE Personal Communication, 6(4), 13–18.
Haykin, S. (2005). Cognitive Radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 23, 201–220.
Akyildiz, I. F., Lee, W. Y., et al. (2006). Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Networks, 50(13), 2127–2159.
Krenik, W. et al. (2009). Cognitive radio techniques for wide areanetworks. Conference proceedings, Texas Instruments, Dallas, USA, pp. 409–412.
Zhang, H. et al. (2009). Spectral efficiency analysis in OFDM and OFDM /OQAM based cognitive radio networks. In: IEEE 69th vehicular technology conference. VTC Spring, Dublin, pp. 1–5.
Laddomada, M., et al. (2011). Advanced technique on multirate signal processing for digital information processing. IET Signal Processing, 5(3), 313–315.
Mohammed, H et al. (2010). On spectrum sharing and dynamic spectrum allocation: MAC layer spectrum sensing in cognitive radio networks. In Procof international conference on communication and mobile computing, IEEE, pp. 183–187.
Farhang-Boroujeny, B., et al. (2008). Multicarrier communication techniques for spectrum sensing and communication in cognitive radios. IEEE Communication Magazine, 46(4), 80–85.
Moret, N., & Tonello, M. (2009). Design of orthogonal filtered multitone modulation systems and comparison among efficient realizations. EURASIP Journal on Advances in Signal Processing, 2009, 1–18.
Ziyang, J., et al. (2010). Optimized paraunitary filter banks for time-frequency channel diagonalization. EURASIP Journal on Advances in Signal Processing, 2010, 1–12.
Ma, J., Li, G., et al. (2009). Signal processing in cognitive radio. Proceedings of the IEEE, 97(5), 805–823.
Zhang, H., et al. (2010) Spectral efficiency comparsion of OFDM/FBMC for uplink cognitive radio networks. EURASIP Journal on Advances in Signal Processing, 2010, 1–14.
Amini, P., & Farhang-Boroujeny, B. (2010). Packet format design and decision directed tracking methods for filter bank multicarrier systems. EURASIP Journal on Advances in Signal Processing, 2010, 1–13.
Stitz, T. H., et al. (2010). Pilot-based synchronization and equalization in filter bank multicarrier communication. EURASIP Journal on Advances in Signal Processing, 2010, 1–18.
TeroIhalainen, T. H. (2007). Stitz et al. “Channel equalization in filter bank based multicarrirer modulation for wireless communacations”. EURASIP Journal on Advances in Signal Processing, 2007, 1–18.
Rosenbaum, L., et al. (2007). An approach for synthesis of modulated M-channel FIR filter banks utilizing the frequency-response masking technique. EURASIP Journal on Advances in Signal Processing, 2007, 1–13.
Feldbauer, C., Kepesi, M., et al. (2005). Multirate signal processing. Graz University of Technology, 1.3.3, 1–10.
Abo-Zahhad, M. (2003). Current state and future direction of multirate filter banks and their applications. Digital Signal Processing, 13(3), 495–518.
Kang, A. S., & Vig, R. (2014). Analysis of effect of variable number of subchannels on the performance of filter bank multicarrier prototype filter. Journal of Electrical and Electronic Systems, 3:1, 1–7.
Kang, A. S., & Vig, R. (2014). BER performance analysis of filter bank multicarrier using sub band processing for physical layer cognitive radio. Journal of Electrical and Electronic Systems, 3:3, 1–8.
Kang, A. S., & Vig, R. (2014). Computational complexity analysis of FBMC-OQAM under different strategic conditions. In Proceedings 2014 RAECS UIET Panjab University Chandigarh, 06–08 March 2014. 978-1-4799-2291-8/14/\(\$ 31.00\)Copyright 2014IEEE, pp. 1–9.
Kang, A. S., & Vig, R. (2014) Study of filter bank multicarrier cognitive radio under wireless fading channel. In Proceeding of IEEE- IACC international conference 2014, 978-1-4799-2572-8/14/\( \$ 31.00\)Copyright2014IEEE, pp. 209–214.
Kang, A. S., et al. (2014). Trade-off between AND and OR detection method for cooperative sensing in cognitive radio. In Proceedings IEEE- IACC international conference, 978-1-4799-2572-8/14/\( \$ 31.00\)Copyright2014IEEE, pp. 209–214, pp. 395–399.
Kang, A. S., Singh, J. P., et al. (2013). Cognitive radio: State of research domain in next generation wireless networks—A critical analysis. International Journal of Computer Applications (0975–8887), 74(10), 1–9.
Kang, A. S., Singh, R., et al. (2013). Cognitive radio new dimension in wireless communication—State of art. International Journal of Computer Appilcation, 74(10), 10–19.
Singh, J. S. P., & Kang, A. S. et al. (2014). Cooperative sensing for cognitive radio: A powerful access method for shadowing environment, SPRINGER-Journal of Wireless Personal Communications. Journal:11277WIRE Article No. 2088, p. 15.
Kang, A. S. & Renu, V. (2014). Performance analysis of FBMC prototype filter under the effect of variable parameters for physical layer cognitive radio. International Journal of Modern Computer Science, 2(5), (CSIR, Govt of India Recognised Journal), pp. 64–70.
Kang, A. S., & Vig, R. (2014). Simulation analysis of modified filter bank multicarrier for physical layer cognitive radio under radio environment. Invertis Journal of Science and Technology, 7(4), 214–223.
Kang, A. S., & Vig, R. (2014). Comparatative performance analysis of FBMC prototype filter under strategic conditions. European Journal of Scientific Research, 125(3), 362–369.
Kang, A. S., & Singh, J. P., et al. (2013). Cooperative fusion sensing technique for cognitive radio for efficient detection method for shadowing environment. In Proceedings of Wilkes international conference for computing sciences, pp. 70–79, Elseveir, ISBN:978-935107-172-3.
Acknowledgments
The first author is thankful to the Joint Research Action Group (JRAG) on intelligent information and signal processing in communication, Deptt of Electronics Technology, Guru Nanak Dev University Amritsar for valuable suggestions and discussion on Multirate–CR system. The help rendered by Dr. Jasvir Singh, Professor Communication Signal Processing Lab, GNDU Asr and Er. Hardeep Singh, Research Scholar is also acknowledged The first author is also thankful to Dr. Harjitpal Singh, Research Scholar at Dr BR Ambedkar National Institute of Technology, Jalandhar in the area of Multirate signal Processing Applications in Communication. Finally,the author wishes to acknowledge the constant inspiration and help rendered by Dr. Davinder Pal Sharma, University of the West Indies St. Augustine, Trinidad & Tobago for providing useful suggestions and comments in the field of DSP applications in Communication. Last but not the least, the motivation received from Prof. Dr. B. P. Patil, from Army Institute of Technology, AIT, Pune to carry out this research work with great zeal of enthusiasm and interest is worth to be mentioned.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kang, A.S., Vig, R. Computer Aided BER Performance Analysis of FBMC Cognitive Radio for Physical Layer Under the Effect of Binary Symmetric Radio Fading Channel. Wireless Pers Commun 82, 1263–1278 (2015). https://doi.org/10.1007/s11277-015-2281-x
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-015-2281-x