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Publication Date

Fall 2021

Degree Type

Thesis - Campus Access Only

Degree Name

Master of Science (MS)

Department

Computer Engineering

Advisor

Mahima A. Suresh

Subject Areas

Computer engineering

Abstract

The expansion of wireless network deployments in the industry along with growingpenetration of wireless network consumers (smartphone and tablets) led to an exponential growth of wireless traffic demand. Internet of Things (IoT) connected an unprecedented number of devices using a significant proportion of wireless spectrum. This led to the use of unlicensed spectrum for LTE. As a result, two main communication technologies, WiFi and LTE, operate and coexist in the unlicensed spectrum. We aim to apply deep learning for classification of coexisting signals in the surrounding area of a device. Following their classification, we wish to develop a machine learning based model which will assist the device to choose the technology with the highest throughput at that instance in time.

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