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Deep Reinforcement Learning based Wireless Resource Management

Description:

Next generation cellular networks are expected to support a massive data traffic volume and satisfy a vast number of users that have latency-critical quality-of-service expectations. Towards serving this demand, it is envisaged that the interference management problem will be the main bottleneck due to the likeliness of a heavily interfering...

Keyword:

power control, deep Q-learning, reinforcement learning, actor critic learning, radio resource management, and Jakes fading model

Subject:

Electrical engineering, Computer science, and Engineering

Creator:

Nasir, Yasar Sinan

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/02/2022

Date Created:

2021-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:15788 and etdadmin_upload_849279