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5G mobile terminals with advanced QoS-based user-centric aggregation (AQUA) for heterogeneous wireless and mobile networks

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Abstract

In this paper we present an advanced QoS provisioning module with vertical multi-homing framework for future fifth generation (5G) mobile terminals with radio network aggregation capability and traffic load sharing in heterogeneous mobile and wireless environments. The proposed 5G mobile terminal framework is leading to high performance utility networks with high QoS provisioning for any given multimedia service, higher bandwidth utilization and multi-RAT capabilities. It is using vertical multi-homing and virtual QoS routing algorithms within the mobile terminal, that is able to handle simultaneously multiple radio network connections via multiple wireless and mobile network interfaces. Our 5G proposal is user-centric, targeted to always-on connectivity, maximal network utilization, maximal throughput, seamless handovers and performances improvement by using vertical multi-homing, as well as session continuity. The performance of our proposed mobile terminal framework for 5G is evaluated using simulations and analysis with multimedia traffic in heterogeneous mobile and wireless scenarios with coexistence of multiple radio access technologies, such as 3G, 4G as well as future 5G radio access networks.

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References

  1. Boccardi, F., et al. (2014). Five disruptive technology directions for 5G. IEEE Communications Magazine, 52(2), 74–80.

    Article  Google Scholar 

  2. Bhushan, N., et al. (2014). Network densification: The dominant theme for wireless evolution into 5G. IEEE Communications Magazine, 52(2), 82–89.

    Article  Google Scholar 

  3. Bangerter, B., Talwar, S., Arefi, R., & Stewart, K. (2014). Networks and devices for the 5G era. IEEE Communications Magazine, 52(2), 90–96.

    Article  Google Scholar 

  4. Wang, C. X., et al. (2014). Cellular architecture and key technologies for 5g wireless communication networks. IEEE Communications Magazine, 52(2), 122–130.

    Article  Google Scholar 

  5. Janevski, T. (2009). 5G mobile phone concept. In IEEE consumer communications and networking conference (CCNC) 2009, Las Vegas, USA.

  6. Lu, W. W. (2008). An open baseband processing architecture for future mobile terminals design. IEEE Wireless Communications, 15, 110–119.

    Article  Google Scholar 

  7. Tudzarov, A., & Janevski, T. (2011). Design for 5G mobile network architecture. International Journal of Communication Networks and Information Security (IJCNIS), 3(2), 112–123.

    Google Scholar 

  8. Noll, J., & Chowdhury, M. M. R. (2010). 5G—Service continuity in heterogeneous environments. Wireless Personal Communications. doi:10.1007/s11277-010-0077-6.

    Google Scholar 

  9. Rahman, M., & Mir F. (2005). Fourth generation (4G) mobile networks—Features, technologies and issues, In 6th IEE international conference on 3G mobile communication technologies (3G 2005), (pp. 1–5). London, UK, November 2005.

  10. Pereira, J. M. (2000). Fourth generation: Now, it is personal. In 11th IEEE international symposium on personal, indoor and mobile radio communications (PIMRC) (Vol. 2, pp. 1009–1016). UK.

  11. Recommendation ITU-T Y.2052 (02/2008): Framework of multi-homing in IPv6-based NGN.

  12. Recommendation ITU-T Y.2056 (08/2011): Framework of vertical multihoming in IPv6-based Next Generation Networks.

  13. Janevski, T. (2014). NGN architectures, protocols, and services. London: Wiley.

    Book  Google Scholar 

  14. Tudzarov, A., & Janevski, T. (2011). Protocols and algorithms for the next generation 5G mobile systems, network protocols and algorithms (Vol. 3, No. 1, pp. 94–114). ISSN 1943-3581.

  15. Janevski, T. (2003). Traffic analysis and design of wireless IP networks. Norwood: Artech House.

    Google Scholar 

  16. Shuminoski, T., & Janevski, T. (2011). Novel adaptive QoS provisioning in heterogeneous wireless environment, International Journal of Communication Networks and Information Security (IJCNIS), 3(1): 1–7, ISSN: 2076-0930.

  17. Shuminoski, T., & Janevski, T. (2013). Novel adaptive QoS framework for integrated UMTS/WLAN environment. Telfor Journal, 5(1), 14–19.

    Google Scholar 

  18. Nkansah-Gyekye, Y., & Agbinya, J. I. Vertical handoff decision algorithm based on fuzzy logic and genetic algorithm. SATNAC September 7–10, 2008.

  19. Radhika, K., & Venugopal Reddy, A. (2011). Network selection in heterogeneous wireless networks based on fuzzy multiple criteria decision making. International Journal of Computer Applications (0975–8887), 22(1), 136–139.

    Google Scholar 

  20. Kaloxylos A., et al. (2009). Network selection algorithm for heterogeneous wireless networks: From design to implementation. Network Protocol and Algorithms, 1(2):27–47 ISSN 1943-3581.

  21. Alkhawlani, M., & Ayesh, A. (2008). Access network selection based on fuzzy logic and genetic algorithms. Advances in Artificial Intelligence, 8(1), 1.

    Article  Google Scholar 

  22. Giupponi, L., Agustı, R., Perez Romero, J. & Sallent, O. (2005). A novel joint radio resource management approach with reinforcement learning mechanisms. In Proceedings of the 24th IEEE international performance, computing, and communications conference (IPCCC’05) (pp. 621–626). Arizona, USA: Phoenix.

  23. Vasilakos, A. V., & Papadimitriou, G. I. (1995). A new approach to the design of reinforcement schemes for learning automata: Stochastic estimator learning algorithm. Neurocomputing, 7(3), 275–297.

    Article  MATH  Google Scholar 

  24. Vasilakos, A. et al. (1998). Evolutionary-fuzzy prediction for strategic QoS routing in broadband networks. In The 1998 IEEE international conference on fuzzy systems proceedings (Vol. 2, pp. 1488–1493).

  25. Kassotakis, I. E., Markaki, M. E., & Vasilakos, A. V. (2000). A hybrid genetic approach for channel reuse in multiple access telecommunication networks. IEEE Journal on Selected Areas in Communications, 18(2), 234–243.

    Article  Google Scholar 

  26. Marwaha, S., Srinivasan, D., Tham, C. K. & Vasilakos, A. (2004). Evolutionary fuzzy multi-objective routing for wireless mobile ad hoc networks. Evolutionary computation, CEC2004. Congress on 2 (pp. 1964–1971).

  27. Duarte, P. B. F., et al. (2012). On the partially overlapped channel assignment on wireless mesh network backbone: A game theoretic approach. IEEE Journal on Selected Areas in Communications, 30(1), 119–127.

    Article  Google Scholar 

  28. Yen, Y. S., et al. (2011). Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs. Mathematical and Computer Modelling, 53(11–12), 2238–2250.

    Article  Google Scholar 

  29. Zhang, X. M., et al. (2015). Interference-based topology control algorithm for delay-constrained mobile Ad hoc networks. IEEE Transactions on Mobile Computing, 14(4), 742–754.

    Article  Google Scholar 

  30. López-Pérez, D., et al. (2013). On distributed and coordinated resource allocation for interference mitigation in self-organizing LTE networks. IEEE/ACM Transaction Networking, 21(4), 1145–1158.

    Article  Google Scholar 

  31. López-Pérez, D., et al. (2014). Power minimization based resource allocation for interference mitigation in OFDMA femtocell networks. IEEE Journal on Selected Areas in Communications, 32(2), 333–344.

    Article  Google Scholar 

  32. Wang, C. Y. et al. (2014). A voting-based femtocell downlink cell-breathing control mechanism. IEEE/ACM Transactions on Networking, PP(99), 1. doi:10.1109/TNET.2014.2357498.

    Google Scholar 

  33. Khan, M., et al. (2012). Game dynamics and cost of learning in heterogeneous 4G networks. IEEE Journal on Selected Areas in Communications, 30(1), 198–213.

    Article  Google Scholar 

  34. Zhou, L., et al. (2010). Context-aware middleware for multimedia services in heterogeneous networks. IEEE Intelligent Systems, 25(2), 40–47.

    Article  Google Scholar 

  35. Demestichas, P., et al. (2004). Service configuration and traffic distribution in composite radio environments. IEEE Transactions on Systems, Man, and Cybernetics, Part C, 34(1), 69–81.

    Article  Google Scholar 

  36. Meng, T., et al. (2015). Spatial reusability-aware routing in multi-hop wireless networks. IEEE TMC. doi:10.1109/TC.2015.2417543.

    Google Scholar 

  37. Dvir, A., et al. (2011). Backpressure-based routing protocol for DTNs. ACM SIGCOMM Computer Communication Review, 41(4), 405–406.

    MathSciNet  Google Scholar 

  38. Attar, A., et al. (2012). A survey of security challenges in cognitive radio networks: Solutions and future research directions. Proceedings of the IEEE, 100(12), 3172–3186.

    Article  Google Scholar 

  39. Fu, S., & Atiquzzaman, M. (2004). SCTP: state of the art in research, products, and technical challenges. Communications Magazine, IEEE, 42(4), 64–76.

    Article  Google Scholar 

  40. Kohler, E., Handley, M., & Floyd, S. (2006). RFC: 4340. Datagram congestion control protocol (DCCP). http://tools.ietf.org/html/rfc4340. Accessed April 3, 2014.

  41. Shuminoski, T., & Janevski, T. (2014). Radio network aggregation for 5G mobile terminals in heterogeneous wireless and mobile networks. Wireless Personal Communications, 78(2), 1211–1229. (Springer).

    Article  Google Scholar 

  42. Broyler, D., Jabbar, A. & Sterbenz, J. P. G. (2010). Design and analysis of a 3-D gauss-markov mobility model for highly dynamic airborne networks, In International telemetering conference (ITC 2010).

  43. Recommendation ITU-T E.804 (02/2014): QoS aspects for popular services in mobile networks.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University, Karpos 2 bb, 1000, Skopje, Republic of Macedonia

    Tomislav Shuminoski & Toni Janevski

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  1. Tomislav Shuminoski
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  2. Toni Janevski
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Correspondence to Tomislav Shuminoski.

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Shuminoski, T., Janevski, T. 5G mobile terminals with advanced QoS-based user-centric aggregation (AQUA) for heterogeneous wireless and mobile networks. Wireless Netw 22, 1553–1570 (2016). https://doi.org/10.1007/s11276-015-1047-4

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