Low complexity closed‐loop strategy for mmWave communication in industrial intelligent systems. Issue 12 (11th July 2022)
- Record Type:
- Journal Article
- Title:
- Low complexity closed‐loop strategy for mmWave communication in industrial intelligent systems. Issue 12 (11th July 2022)
- Main Title:
- Low complexity closed‐loop strategy for mmWave communication in industrial intelligent systems
- Authors:
- Chen, Ning
Lin, Hongyue
Zhao, Yifeng
Huang, Lianfen
Du, Xiaojiang
Guizani, Mohsen - Abstract:
- Abstract: Modern communication and computing technology is the basic support of the industrial intelligent systems (IIS). As a key component of IIS, the smart port is essential to be offered low‐complexity and high‐reliability communication service, especially for driverless engineering vehicles. However, it is combined and nonconvex to find the optimal association between vehicles and the road side units (RSUs). Besides, due to the mobility of vehicles and the severe path loss of mmWave links, beam switching and reassociation between vehicles and RSUs are required frequently, which brings a great challenge to the communication for the IIS. A low complexity closed‐loop strategy based on distributed cooperation for mmWave communication in IIS is proposed in this study, in which user association and beam tracking with the assistance of beam pools is proposed. Many‐to‐many user association is established based on distributed multiagent reinforcement learning, where the vehicle can independently select the set of serving RSUs based on the local observation without information exchange with others, reducing the signaling overhead and computational complexity while improving system throughput. Furthermore, multipoint‐cooperation soft switching of beams based on beam tracking improves the reliability of mmWave communication with the smaller training cost. Extensive analysis and simulation results demonstrate that the proposed solution significantly reduces the complexity of theAbstract: Modern communication and computing technology is the basic support of the industrial intelligent systems (IIS). As a key component of IIS, the smart port is essential to be offered low‐complexity and high‐reliability communication service, especially for driverless engineering vehicles. However, it is combined and nonconvex to find the optimal association between vehicles and the road side units (RSUs). Besides, due to the mobility of vehicles and the severe path loss of mmWave links, beam switching and reassociation between vehicles and RSUs are required frequently, which brings a great challenge to the communication for the IIS. A low complexity closed‐loop strategy based on distributed cooperation for mmWave communication in IIS is proposed in this study, in which user association and beam tracking with the assistance of beam pools is proposed. Many‐to‐many user association is established based on distributed multiagent reinforcement learning, where the vehicle can independently select the set of serving RSUs based on the local observation without information exchange with others, reducing the signaling overhead and computational complexity while improving system throughput. Furthermore, multipoint‐cooperation soft switching of beams based on beam tracking improves the reliability of mmWave communication with the smaller training cost. Extensive analysis and simulation results demonstrate that the proposed solution significantly reduces the complexity of the mmWave communication while improving the throughput and stability in IIS. … (more)
- Is Part Of:
- International journal of intelligent systems. Volume 37:Issue 12(2022)
- Journal:
- International journal of intelligent systems
- Issue:
- Volume 37:Issue 12(2022)
- Issue Display:
- Volume 37, Issue 12 (2022)
- Year:
- 2022
- Volume:
- 37
- Issue:
- 12
- Issue Sort Value:
- 2022-0037-0012-0000
- Page Start:
- 10813
- Page End:
- 10844
- Publication Date:
- 2022-07-11
- Subjects:
- beam tracking -- industrial intelligent systems -- mmWave communication -- system complexity -- user association
Artificial intelligence -- Periodicals
Expert systems (Computer science) -- Periodicals
Intelligence artificielle -- Périodiques
Systèmes experts (Informatique) -- Périodiques
006.3 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1098-111X ↗
https://www.hindawi.com/journals/ijis ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/int.22953 ↗
- Languages:
- English
- ISSNs:
- 0884-8173
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.310500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25605.xml