Open AccessApplication of Adaptive Neuro‐Fuzzy Inference System for Interference Management in Heterogeneous Network
Author(s) -
Palanisamy Padmaloshani,
Sivaraj Nirmala
Publication year - 2018
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.2017-0195
Subject(s) - macrocell , femtocell , computer science , computer network , overhead (engineering) , base station , throughput , interference (communication) , wireless network , heterogeneous network , transmission (telecommunications) , telecommunications link , power control , wireless , distributed computing , power (physics) , channel (broadcasting) , telecommunications , physics , quantum mechanics , operating system
Femtocell ( FC ) technology envisaged as a cost‐effective approach to attain better indoor coverage of mobile voice and data service. Deployment of FC s over macrocell forms a heterogeneous network. In urban areas, the key factor limits the successful deployment of FC s is inter‐cell interference ( ICI ), which severely affects the performance of victim users. Autonomous FC transmission power setting is one straightforward way for coordinating ICI in the downlink. Application of intelligent control using soft computing techniques has not yet explored well for wireless networks. In this work, autonomous FC transmission power setting strategy using Adaptive Neuro Fuzzy Inference System is proposed. The main advantage of the proposed method is zero signaling overhead, reduced computational complexity and bare minimum delay in performing power setting of FC base station because only the periodic channel measurement reports fed back by the user equipment are needed. System level simulation results validate the effectiveness of the proposed method by providing much better throughput, even under high interference activation scenario and cell edge users can be prevented from going outage.