Work

Deep Reinforcement Learning for BBU Placement and Routing in C-RAN

Year: 2019

Type: conference-paper

Abstract: The paper proposes a deep reinforcement learning (DRL) based policy for BBU placement and routing in C-RAN. The simulation results show DRL-based policy reaches the near-optimal performance with a significantly reduced computing time.

Source: Optical Fiber Communication Conference

DOI: 10.1364/ofc.2019.w2a.22

Authors: Zhengguang Gao, Jiawei Zhang, Shuangyi Yan, Yuming Xiao, Dimitra Simeonidou, Yuefeng Ji

Institutions: Beijing University of Posts and Telecommunications, State Key Laboratory of Information Photonics and Optical Communications, University of Bristol

Language: English

Topic: Advanced MIMO Systems Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W2918136175

FWCI: 7.921

Cites: 4

Cited by: 30

Related to: 10