Research ArticlesNo Access

Experimental Study on Elliott Wave Theory for Handoff Prediction

K. S. Vishvaksenan

Department of ECE, SSN College of Engineering, Kalavakkam, Chennai, India

Search for more papers by this author

K. Mithra

Department of ECE, SSN College of Engineering, Kalavakkam, Chennai, India

Search for more papers by this author

R. Kalidoss

Department of ECE, SSN College of Engineering, Kalavakkam, Chennai, India

E-mail Address: kalidossr@ssn.edu.in

Corresponding author.

Search for more papers by this author

, and

R. Karthipan

Department of ECE, SSN College of Engineering, Kalavakkam, Chennai, India

Search for more papers by this author

https://doi.org/10.1142/S0219477516500255Cited by:11 (Source: Crossref)

Abstract

The main objective for the next generation wireless network is the offer of a high data rate when the user is on the move. The key element that offers continuous connectivity is the handoff. In this paper, we propose a handoff prediction model, which can predict handoff behavior of the user well in advance and reduce the latency in the handoff operation. The prediction model is validated with real life scenario both for the pedestrian user and the vehicle user, traveling at a speed of 80km/h. The experimental result verifies the capability of the proposed algorithm to predict the future sample with accuracy and minimum latency. Simulation results demonstrate the proposed system outperforming the existing system compared to the probability of the handoff detection and minimizing the false alarm probability. There is also the fact of the proposed algorithm not requiring any additional hardware for predicting the mobility of the user.

Communicated by Boris M. Grafov

Keywords:

References

1. A. M. Miyim, M. Ismail, R. Nordin and M. Taha Ismail, Technique for cross-layer vertical handover prediction in 4G wireless networks, 4th Int. Conf. Electrical Engineering and Informatics (ICEEI), (2013), pp. 114–121. Google Scholar
2. T.-S. Shih, J.-S. Su and H.-M. Lee, Fuzzy seasonal demand and fuzzy total demand production quantities based on interval valued fuzzy sets, Int. J. Innov. Comput. Inform. Control 7(5B) (2011) 2637–2650. Web of Science, Google Scholar
3. Y.-F. Huang, Y.-F. Chen, T.-H. Tan and H.-L. Hung, Applications of fuzzy logic for adaptive interference canceller in CDMA wireless communication systems, Int. J. Innov. Comput. Inform. Control 6(4) (2010) 1749–1761. Web of Science, Google Scholar
4. K. Rajakani and M. A. Bhagyaveni, Adaptive duplex technique for reduction of turnaround time in IEEE 802.22, Commun. Comput. Inform. Sci. 269 (2012) 503–511. Google Scholar
5. R. Kalidoss, M. A. Bhagyaveni and K. S. Vishvaksenan, A Location Based Duplex Scheme for Cost Effective Rural Broadband Connectivity Using IEEE 802.22 Cognitive Radio Based Wireless Regional Area Networks, Fluct. Noise Lett. 13(4) (2014) 1–20. Link, Web of Science, Google Scholar
6. B. Partibane, V. Nagarajan, K. S. Vishvaksenan and R. Kalidoss, Performance of Multi-User Transmitter Pre-Processing Assisted Multi-Cell IDMA System for Downlink Transmission, Fluct. Noise Lett. 14(3) (2015) 1–16. Link, Web of Science, Google Scholar
7. R. Karthipan, K. S. Vishvaksenan, R. Kalidoss and R. S. Babu, Uplink Capacity Enhancement in IEEE 802.22 Using Modified Duplex Approach, Wirel. Pers. Commun. 86(2) (2016) 635–656. Web of Science, Google Scholar
8. R. Karthipan, K. S. Vishvaksenan, R. Kalidoss and A. Krishan, Performance of turbo coded triply-Polarized MIMO–CDMA system for downlink communication, Comput. Electr. Eng. (2016) 1–11, doi: 10.1016/j.compeleceng.2016.01.004. Web of Science, Google Scholar
9. V. Vijayarangan, R. Kalidoss and R. Sukanesh, Low crest mapping for PAPR reduction in OFDM system, IET International Conference on Wireless, Mobile and Multimedia Networks (hangzhou, China, 2006), pp. 1–4. Google Scholar
10. M. A. Bhagyaveni, R. Kalidoss and K. S. Vishvaksenan, Introduction to analog and digital communication, River Publishers (Netherlands, 2016). Google Scholar
11. M. Al-Sanabani, S. Subramaniam, M. Othman and Z. Zukarnaim, Mobility prediction based resource reservation for handoff in multimedia wireless cellular networks, Int. Arab J. Inform. Technol. 5(2) (2008) 162–169. Web of Science, Google Scholar
12. T. Liu, P. Bahl and I. Chalmtac, Mobility modeling location tracking and trajectory prediction in wireless ATM networks, IEEE J. Sel. areas Commun. 16(6) (1998) 922–936. Web of Science, Google Scholar
13. A. Sleem and A. Kumar, Handoff management in wireless data networks using topography-aware mobility prediction, J. Parallel Distrib. Comput. 65 (2005) 963–982. Web of Science, Google Scholar