دانلود مقاله ISI انگلیسی شماره 46406
ترجمه فارسی عنوان مقاله

تعادل بار و بهینه سازی مشترک جابجایی در شبکه های LTE با استفاده از منطق فازی و یادگیری تقویتی

عنوان انگلیسی
Load balancing and handover joint optimization in LTE networks using Fuzzy Logic and Reinforcement Learning
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
46406 2015 14 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Computer Networks, Volume 76, 15 January 2015, Pages 112–125

ترجمه کلمات کلیدی
تعادل بار - جابجایی - شبکه های خودسازمانده - تکامل بلند مدت - منطق فازی - یادگیری تقویتی
کلمات کلیدی انگلیسی
Load balancing; Handover; Self-organizing networks; Long-term evolution; Fuzzy logic; Reinforcement learning
پیش نمایش مقاله
پیش نمایش مقاله  تعادل بار و بهینه سازی مشترک جابجایی در شبکه های LTE با استفاده از منطق فازی و یادگیری تقویتی

چکیده انگلیسی

With the growing deployment of cellular networks, operators have to devote significant manual effort to network management. As a result, Self-Organizing Networks (SONs) have become increasingly important in order to raise the level of automated operation in cellular technologies. In this context, Load Balancing (LB) and Handover Optimization (HOO) have been identified by industry as key self-organizing mechanisms for the Radio Access Networks (RANs). However, most efforts have been focused on developing a stand-alone entity for each self-organizing mechanism, which will run in parallel with other entities, as well as designing coordination mechanisms in charge of stabilizing the network as a whole. Due to the importance of LB and HOO, in this paper, a unified self-management mechanism based on Fuzzy Logic and Reinforcement Learning is proposed. In particular, the proposed algorithm modifies handover parameters to optimize the main Key Performance Indicators related to LB and HOO. Results show that the proposed scheme effectively provides better performance than independent entities running simultaneously in the network.