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Publication

Design a Cross-Layer Cognitive Engine using Cross-Layer Optimization with Case-Based Reasoning and Reinforcement Learning

Authors:
Dr.-Ing. Ali Haider Mahdi
Prof. Dr.-Ing. habil. Andreas Mitschele-Thiel
Typ:
Workshop
Status:
accepted
Date of publication
10/11/2013
Abstract:
Cognitive Radio (CR) is one of the promising technologies which investigated to solve autonomously the spectrum congestion problem because of wide users’ applications. In order to use CR for solving the aforementioned problem, we need to have a smart entity which can autonomously perform the desired behavior. Our contribution is a proposal of a Cross-Layer Cognitive Engine (CLCE) which applies three AI-based methodologies: Cross-Layer Optimization (CLO), Case-Based Reasoning (CBR), and Reinforcement Learning (RL). Our Contribution shows an improvement of 60% in signaling overhead and 50% in throughput comparing to literature.
Bibtex