Walter Scott, Jr. College of Engineering

Graduate Exam Abstract

Fateh Elsherif
Ph.D. Preliminary
Apr 22, 2019, 4:00 pm - 6:00 pm
Civil/ Environmental Engineering conference room
Green Communication and Security in Wireless Networks based on Markov Decision Process and Semivariance Optimization
Abstract: In this thesis, we introduce new frameworks, problems, and solutions for green communication and RF anti-jamming in wireless networks. First, we study the problem of base station (BS) dynamic switching for energy efficient design of fifth generation (5G) cellular networks and beyond. We formulate this problem as a Markov decision process (MDP) and use an approximation method known as policy rollout to solve it. This method employs Monte Carlo sampling to approximate the Q-value. In this work, we introduce a novel approach to design an energy efficient BS control algorithm. We design an MDP-based algorithm to control the ON/OFF switching of BSs in real-time; we exploit user mobility and location information in the selection of the optimal control actions. We start our formulation with the simple case of one-user one-ON. We then gradually and systematically extend this formulation to the multi-user multi-ON scenario. Simulation results show the potential of our novel approach of exploiting user mobility information within the MDP framework to achieve significant energy savings while providing quality-of-service guarantees. Second, in our ongoing work, we study the problem of jamming-aware-multi-path routing in wireless networks. To address this problem, we propose a new framework based on semivariance optimization. We map the problem of jamming-aware-multi-path routing to that of the portfolio selection within the semivariance risk framework. Then we use this framework to design a new RF anti-jamming algorithm. Last, in our future work, we will study the problem of RF anti-jamming in a multiple radio access technology network environment. We propose a unified approach combining cellular, WLAN, and carrier aggregation. We will investigate the possibility to map this problem to portfolio-selection-semivariance optimization. The assets in this case will be the communication resources (frequency bands and/or energy) from the available communication channels.
Adviser: Edwin Chong
Co-Adviser: N/A
Non-ECE Member: Rebecca Atadero
Member 3: Anura P. Jayasumana
Addional Members: J. Rockey Luo
Real-Time Base Station Control for 5G Cellular Networks Based on Markov Decision Process
Program of Study:
ECE 520 (Optimization Methods-Control and Communication)
ECE 581 (Global Navigation Satellite System Receivers)
ECE 516 (Information Theory)
ECE 514 (Applications of Random Processes)
ECE 652 (Estimation and Filtering Theory)
ECE 656 (Machine Learning and Adaptive Systems)
ECE 569 (Micro-Electro-Mechanical Devices)
ENGR 501 (Foundations of Systems Engineering)