Volume 3, Number 1 (2018)
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Home > Journals > SCIREA Journal of Agriculture > Archive > Paper Information

Adaptive Handoff Prediction and Appreciate Decision Using ANFIS between Terrestrial Communication and HAP

Volume 3, Issue 1, February 2018    |    PP. 19-33    |PDF (1561 K)|    Pub. Date: January 7, 2018
105 Downloads     1493 Views  

S.H. Alsamhi, Electronics Engineering, AMU and IBB University, Aligarh, India
M. Ansari, Electronics Engineering, AMU, Aligarh, India
M. Hebah, Electronics Engineering, AMU,Aligarh, India
A. Ahmed, Electronics Engineering, AMU,Aligarh, India
A. Hatem, Electronics Engineering, AMU,Aligarh, India
M. Alasali, Electrical Engineering,AMU,Aligarh, India

Adaptive handoff provides a cost-effective way to enhance the Quality of Service (QOS) of homogeneous and heterogeneous communication systems. Recent researches focused on handoff between Heterogonous communications systems. Therefore, handoff between terrestrial communication systems and High altitude platform using Neuro Fuzzy Interference system (ANFIS) is our proposed technique for enhancing the QoS. The proposed techniques used for accurate prediction and appreciated decision-based on Received Signal Strength (RSS), Velocity of the user, and the distance between the user from the cell center and the available channel in both terrestrial and HAP. HAP has been considered as a complementary BS to the terrestrial mobile system, giving coverage in shadow zones. HAPs can provide back-up services to areas which are uncovered by terrestrial systems, thus with the goodness of HAP, QoS improved. The results show that ANFIS is a viable option for an appreciated hand-off decision and more sensitive for hand-off prediction.

ANFIS, QOS, HAP, Heterogeneous communication, Hand-off, prediction

Cite this paper
S.H. Alsamhi, M. Ansari, M. Hebah, A. Ahmed, A. Hatem, M. Alasali, Adaptive Handoff Prediction and Appreciate Decision Using ANFIS between Terrestrial Communication and HAP, SCIREA Journal of Agriculture. Vol. 3 , No. 1 , 2018 , pp. 19 - 33 .


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