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Dependability-Based Analysis for Ultra-reliable Communication in Heterogeneous Traffic Cognitive Radio Networks with Spectrum Reservation

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Abstract

Spectrum availability and network reliability both are the crucial aspects in Cognitive Radio Networks (CRNs) to ensure ultra-reliable communication (URC). Therefore, the current research work aims to perform an in-depth dependability theory-based analysis for cognitive system availability and reliability. In our analysis, the impact of random channel failures and their recovery on the CRN system is investigated. Also, the system facilitates the arrival of heterogeneous secondary users and encompasses a multi-level channel reservation feature. The whole system is modeled using Continuous Time Markov Chain (CTMC) and mathematical expressions are derived for several transient dependability metrics utilizing the uniformization tool. Performance of the system is evaluated under various network conditions. Results demonstrate that the channel reservation might not necessarily provide improved performance as suggested in the sate-of-the-art, contrarily, its success highly depends on the network load and the time elapsed. Moreover, the availability and reliability provided to end users are also significantly impacted by the channel failure rate and recovery rate at higher time points.

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References

  1. Sharma, N., & Kumar, K. (2021). Resource allocation trends for ultra dense networks in 5G and beyond networks: A classification and comprehensive survey. Physical Communication, 48, 1–27 (Article ID 101415).

    Article  Google Scholar 

  2. Mendis, H. V., Balapuwaduge, I. A., & Li, F. Y. (2019). Dependability-based reliability analysis in URC networks: Availability in the space domain. IEEE/ACM Transactions on Networking, 27(5), 1915–1930.

    Article  Google Scholar 

  3. Khan, A. U., Tanveer, M., & Khan, W. U. (2021). On reliability in the performance analysis of cognitive radio networks. Journal of King Saud University: Computer and Information Sciences. https://doi.org/10.1016/j.jksuci.2021.10.010.

    Article  Google Scholar 

  4. Ni, S., Zhuang, Y., Cao, Z., & Kong, X. (2014). Modeling dependability features for real-time embedded systems. IEEE Transactions on Dependable and Secure Computing, 12(2), 190–203.

    Article  Google Scholar 

  5. Ahmad, W., Hasan, O., Pervez, U., & Qadir, J. (2017). Reliability modeling and analysis of communication networks. Journal of Network and Computer Applications, 78, 191–215.

    Article  Google Scholar 

  6. Rubino, G., & Sericola, B. (2014). Markov chains and dependability theory. Cambridge University Press.

    Book  MATH  Google Scholar 

  7. Gouda, A. E., Rabia, S. I., Zakariya, A. Y., & Omar, M. (2018). Reactive spectrum handoff combined with random target channel selection in cognitive radio networks with prioritized secondary users. Alexandria Engineering Journal, 57(4), 3219–3225.

    Article  Google Scholar 

  8. Debnath, S., Arif, W., Roy, S., Baishya, S., & Sen, D. (2021). A comprehensive survey of emergency communication network and management. Wireless Personal Communications, 124, 1–47.

    Google Scholar 

  9. Shruti, & Kulshrestha, R. (2020). Channel allocation and ultra-reliable communication in CRNs with heterogeneous traffic and retrials: A dependability theory-based analysis. Computer Communications, 158, 51–63.

    Article  Google Scholar 

  10. Parthasarathy, P., & Dharmaraja, S. (2001). Transient solution of a link with finite capacity supporting multiple streams. Performance Evaluation, 43(1), 1–14.

    Article  MATH  Google Scholar 

  11. Yang, D. Y., & Wu, Y. Y. (2017). Analysis of a finite-capacity system with working breakdowns and retention of impatient customers. Journal of Manufacturing Systems, 44, 207–216.

    Article  Google Scholar 

  12. Legros, B. (2019). Transient analysis of a Markovian queue with deterministic rejection. Operations Research Letters, 47, 391–397.

    Article  MathSciNet  MATH  Google Scholar 

  13. Falcao, M., Silva, G. A., Dias, K., & Balieiro, A. (2016). Three-layered prioritized cognitive radio networks with channel aggregation and fragmentation techniques. In 2016 8th IEEE Latin-American conference on communications (LATINCOM) (pp. 1–5). IEEE.

  14. Kumar, A., & Gupta, M. (2018). A review on activities of fifth generation mobile communication system. Alexandria Engineering Journal, 57(2), 1125–1135.

    Article  Google Scholar 

  15. Raja, S., & Louis, A. (2021). A review of call admission control schemes in wireless cellular networks. Wireless Personal Communications, 120(4), 3369–3388.

    Article  Google Scholar 

  16. El Azaly, N. M., Badran, E. F., Rizk, M., & Mokhtar, M. A. (2017). Performance enhancement of steady-state Markov analysis for cognitive radio networks via channel reservation. Alexandria Engineering Journal, 56(4), 469–475.

    Article  Google Scholar 

  17. Chu, T. M. C., Zepernick, H. J., & Phan, H. (2015). Channel reservation for dynamic spectrum access of cognitive radio networks with prioritized traffic. In 2015 IEEE International conference on communication workshop (ICCW) (pp. 883–888). IEEE.

  18. Politis, C., Maleki, S., Tsinos, C. G., Liolis, K. P., Chatzinotas, S., & Ottersten, B. (2017). Simultaneous sensing and transmission for cognitive radios with imperfect signal cancellation. IEEE Transactions on Wireless Communications, 16(9), 5599–5615.

    Article  Google Scholar 

  19. Thakur, P., Kumar, A., Pandit, S., Singh, G., & Satashia, S. (2018). Analysis of high-traffic cognitive radio network with imperfect spectrum monitoring technique. Computer Networks, 147, 27–37.

    Article  Google Scholar 

  20. Mohammad, F. R., Ciuonzo, D., & Mohammed, Z. A. K. (2018). Mean-based blind hard decision fusion rules. IEEE Signal Processing Letters, 25(5), 630–634.

    Article  Google Scholar 

  21. Cao, Y., Zhao, N., Yu, F. R., Jin, M., Chen, Y., Tang, J., & Leung, V. C. (2018). Optimization or alignment: Secure primary transmission assisted by secondary networks. IEEE Journal on Selected Areas in Communications, 36(4), 905–917.

    Article  Google Scholar 

  22. Lu, W., Hu, S., Liu, X., He, C., & Gong, Y. (2019). Incentive mechanism based cooperative spectrum sharing for OFDM cognitive IoT network. IEEE Transactions on Network Science and Engineering, 7(2), 662–672.

    Article  MathSciNet  Google Scholar 

  23. Sun, L., Wang, W., & Lu, Z. (2015). On topology and resilience of large-scale cognitive radio networks under generic failures. IEEE Transactions on Wireless Communications, 14(6), 3390–3401.

    Article  Google Scholar 

  24. Zaghouani, M. H., Sztrik, J., & Melikov, A. Z. (2019). Reliability analysis of cognitive radio networks. In 2019 International conference on information and digital technologies (IDT) (pp. 557–562). IEEE.

  25. Hamza, D., & Aïssa, S. (2013). Enhanced primary and secondary performance through cognitive relaying and leveraging primary feedback. IEEE Transactions on Vehicular Technology, 63(5), 2236–2247.

    Article  Google Scholar 

  26. Dudin, A. N., Lee, M. H., Dudina, O., & Lee, S. K. (2016). Analysis of priority retrial queue with many types of customers and servers reservation as a model of cognitive radio system. IEEE Transactions on Communications, 65(1), 186–199.

    Google Scholar 

  27. Balapuwaduge, I. A., Li, F. Y., & Pla, V. (2016). Significance of channel failures on network performance in CRNs with reserved spectrum. In 2016 IEEE International conference on communications (ICC) (pp 1–6). IEEE.

  28. Balapuwaduge, I. A., Li, F. Y., & Pla, V. (2017). Dynamic spectrum reservation for CR networks in the presence of channel failures: Channel allocation and reliability analysis. IEEE Transactions on Wireless Communications, 17(2), 882–898.

    Article  Google Scholar 

  29. Falcão, M. R., Balieiro, A. M., & Dias, K. L. (2018). A flexible-bandwidth model with channel reservation and channel aggregation for three-layered cognitive radio networks. Computer Networks, 135, 213–225.

    Article  Google Scholar 

  30. Khan, A. U., Abbas, G., Abbas, Z. H., Baker, T., & Waqas, M. (2020). Spectrum efficiency in CRNs using hybrid dynamic channel reservation and enhanced dynamic spectrum access. Ad Hoc Networks, 107, 1–16 (Article ID 102246).

    Article  Google Scholar 

  31. El Azaly, N. M., Badran, E. F., Kheirallah, H. N., & Farag, H. H. (2021). Performance analysis of centralized dynamic spectrum access via channel reservation mechanism in cognitive radio networks. Alexandria Engineering Journal, 60(1), 1677–1688.

    Article  Google Scholar 

  32. Rodríguez-Estrello, C. B., Hernández-Valdez, G., & Cruz-Pérez, F. A. (2008). System-level analysis of mobile cellular networks considering link unreliability. IEEE Transactions on Vehicular Technology, 58(2), 926–940.

    Article  Google Scholar 

  33. Chakraborty, T., & Misra, I. S. (2015). Design and analysis of channel reservation scheme in cognitive radio networks. Computers and Electrical Engineering, 42, 148–167.

    Article  Google Scholar 

  34. Ding, G., & Zhao, Q. (2016). Analysis on the performance of special channel reservation mechanism in cognitive radio. In 2016 First IEEE International conference on computer communication and the Internet (ICCCI) (pp. 37–40). IEEE.

  35. Balapuwaduge, I. A., Li, F. Y., & Pla, V. (2016). System times and channel availability for secondary transmissions in CRNs: A dependability-theory-based analysis. IEEE Transactions on Vehicular Technology, 66(3), 2771–2788.

    Article  Google Scholar 

  36. ITU. (2007). Quality of service and dependability vocabulary. Recommendation ITU-T E.800. Telecommunication Standardization Sector of ITU. http://www.itu.int/rec/T-REC-E.800-198811-S/en.

  37. Balapuwaduge, I. A., & Li, F. Y. (2018). A joint time–space domain analysis for ultra-reliable communication in 5G networks. In 2018 IEEE International conference on communications (ICC) (pp. 1–6). IEEE.

  38. Karlin, S., & Taylor, H. (1975). A first course in stochastic processes (2nd ed.). Academic Press.

    MATH  Google Scholar 

  39. Van Dijk, N. M., Van Brummelen, S. P., & Boucherie, R. J. (2018). Uniformization: Basics, extensions and applications. Performance Evaluation, 118, 8–32.

    Article  Google Scholar 

  40. Amich, A., Imran, M. A., Tafazolli, R., & Cheraghi, P. (2014). Accurate and efficient algorithms for cognitive radio modeling applications under the i.n.i.d. paradigm. IEEE Transactions on Vehicular Technology, 64(5), 1750–1765.

    Article  Google Scholar 

  41. Jiao, L., Balapuwaduge, I. A., Li, F. Y., & Pla, V. (2014). On the performance of channel assembling and fragmentation in cognitive radio networks. IEEE Transactions on Wireless Communications, 13(10), 5661–5675.

    Article  Google Scholar 

  42. Lee, L. (1971). The unserviceable probability of a class of telecommunications networks. IEEE Transactions on Reliability, 20(3), 132–135.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Mathematics, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, 201309, India

    Shruti Goel

  2. Department of Mathematics, Birla Institute of Technology and Science, Pilani, Pilani, India

    Rakhee Kulshrestha

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  1. Shruti Goel
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  2. Rakhee Kulshrestha
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Correspondence to Shruti Goel.

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Goel, S., Kulshrestha, R. Dependability-Based Analysis for Ultra-reliable Communication in Heterogeneous Traffic Cognitive Radio Networks with Spectrum Reservation. Wireless Pers Commun 127, 3015–3039 (2022). https://doi.org/10.1007/s11277-022-09908-3

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