Project Details
Description
Utilizing Deep Neural Networks (DNN) in engineering and sciences applications has grown significantly
in recent years. Recently, a paradigm shift from model-based to end-to-end design and optimization of
communication systems has been introduced using deep learning tools. In wireless communication
system, the demand and exchange of information has significantly increased. New factors, such as low-
latency requirements, mobility, changing channel conditions, or unknown channel models will benefit
from deep learning applications. In addition, communicating over unlicensed spectrum, such as ISM
band, became wide popular for wireless applications, such as WiFi and Bluetooth, which in turn
increases the interference at the receiver. The plethora of both interference sources and mitigation
algorithms along with the exponential growth of wireless systems necessitate designing an adaptive
system that accounts for multiple interference sources without compromising the bandwidth of the
signal-of-interest or increasing the computational complexity of the system. This issue requires an agile
system with the ability to detect the interference and mitigate it without human intervention. The recent
success in implementing supervised learning to classify modulation types by classification of different
types of modulation using Convolutional Neural Networks (CNN), suggests that other problems akin to
modulation classification would eventually benefit from that implementation. One of these problems
is classifying the interference type added to a signal-of-interest, also known as interference classification.
This project will design and evaluate key applications of DNN in communications systems physical layer,
such as modulation and interference classifiers, MIMO Detection, power allocation, channel estimation,
and encoding/ decoding. In addition, some classical communication blocks, such as Viterbi decoders, can
benefit a lot from DNN assistance. Furthermore, deep reinforcement learning could be used to solve
complex optimization problems in communication systems. Therefore, we will investigate the
implications of such application on the design and performance of communication system
Status | Finished |
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Effective start/end date | 1/07/21 → 31/12/22 |
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