Document Type

Thesis

Degree

Master of Science (MS)

Department

Electrical Engineering

First Advisor's Name

Dr. Ismail Guvenc

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Dr. Hai Deng

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Dr. Nazih Pala

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Dr. Walid Saad

Fourth Advisor's Committee Title

Committee Member

Keywords

Beacon, licensed-Assisted Access (LAA), Q-Learning, TDD-LTE, WiFi 802.11n

Date of Defense

3-26-2015

Abstract

Today, smart-phones have revolutionized wireless communication industry towards an era of mobile data. To cater for the ever increasing data traffic demand, it is of utmost importance to have more spectrum resources whereby sharing under-utilized spectrum bands is an effective solution. In particular, the 4G broadband Long Term Evolution (LTE) technology and its foreseen 5G successor will benefit immensely if their operation can be extended to the under-utilized unlicensed spectrum. In this thesis, first we analyze WiFi 802.11n and LTE coexistence performance in the unlicensed spectrum considering multi-layer cell layouts through system level simulations. We consider a time division duplexing (TDD)-LTE system with an FTP traffic model for performance evaluation. Simulation results show that WiFi performance is more vulnerable to LTE interference, while LTE performance is degraded only slightly. Based on the initial findings, we propose a Q-Learning based dynamic duty cycle selection technique for configuring LTE transmission gaps, so that a satisfactory throughput is maintained both for LTE and WiFi systems. Simulation results show that the proposed approach can enhance the overall capacity performance by 19% and WiFi capacity performance by 77%, hence enabling effective coexistence of LTE and WiFi systems in the unlicensed band.

Identifier

FI15032155

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