Primal Dual PPO Learning Resource Allocation in Indoor IRS-Aided Networks

Haijun Zhang, Xiangnan Liu, Keping Long, H. Vincent Poor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Terahertz communications is regarded as a promising technology due to its higher bandwidth and narrower beamwidths, which can improve capacity and coverage for indoor wireless users. In this paper, the intelligent reflecting surface (IRS) technique and non-orthogonal multiple access (NOMA) are utilized to compensate drawbacks of indoor transmission mismatch in the terahertz band. Then wireless resource allocation optimization in indoor terahertz IRS-aided systems is transformed into a universal optimization problem with ergodic constraints. With the aid of parametrization features of deep neural networks (DNNs), proximal policy optimization (PPO) is adopted to train the policy and corresponding actions to allocate power and bandwidths. The actor part generates continuous power allocation, and the critic part takes charge of discrete bandwidths allocation. In the design of a deep reinforcement learning (DRL) framework, primal dual ascent is proposed to realize model-free training. Simulation results demonstrate the effectiveness of the primal dual PPO learning algorithm in different settings.

Original languageEnglish (US)
Title of host publication2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728181042
DOIs
StatePublished - 2021
Event2021 IEEE Global Communications Conference, GLOBECOM 2021 - Madrid, Spain
Duration: Dec 7 2021Dec 11 2021

Publication series

Name2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings

Conference

Conference2021 IEEE Global Communications Conference, GLOBECOM 2021
Country/TerritorySpain
CityMadrid
Period12/7/2112/11/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Health Informatics

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