User velocity based hand-off prediction in micro-femtocell clustered network. (November 2018)

• Record Type: Journal Article
• Authors: Mukherjee, Anwesha; De, Debashis
• Is Part Of: Computers & electrical engineering. Volume 72(2018)
• Page Start: 732
• Page End: 751
• Publication Date: 2018-11
• Subjects: Hand-off -- Velocity -- Movement -- Satisfaction probability -- Power -- SINR; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.11.023
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: This article presents a strategy for predicting the mean number of hand-offs in a micro-femtocell network. This approach considers the velocity of the mobile terminal across three-dimensions and determines the frequency of hand-off occurrences. Simulation results illustrate that the proposed method increases the satisfaction probability by approximately 55%–90% than the existing borrowing channel assignment approach. Based on the velocity and movement pattern, a new user is handed over to a femtocell within the newly entered microcell where the cooperative frequency allocation is performed. Simulation results demonstrate that the proposed micro-femtocell network reduces the power transmission in the area covered by the base stations by approximately 40% and 25% than the macro-femtocell network, and the macro-femtocell and micro-femtocell clustered network respectively. Simulation results illustrate that the proposed network increases the Signal-to-Interference-plus-Noise Ratio (SINR) by approximately 55–65% and 27–32% than the macro-femtocell network, and the macro-femtocell and micro-femtocell clustered network respectively.