Optimisation of the duplex D2D network: a deep learning approach. Issue 3 (1st May 2020)

• Record Type: Journal Article
• Authors: Liu, Xian
• Is Part Of: IET networks. Volume 9:Issue 3(2020)
• Page Start: 139
• Page End: 144
• Publication Date: 2020-05-01
• Subjects: learning (artificial intelligence) -- neural nets -- optimisation -- nonlinear programming -- linear programming -- cellular radio; duplex D2D network -- deep learning approach -- wireless networks -- quality‐of‐service‐promotion strategy -- transmission power -- deep learning methodology -- device‐to‐device network -- nonlinear programming problem -- training data -- standard optimisation tool -- artificial neural network -- deep leaning; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/iet-net.2019.0074
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract : For wireless networks, it is highly desirable to design a quality‐of‐service‐promotion strategy to allocate the transmission power. In this study, the authors apply the deep learning methodology to solve such a problem in a duplex device‐to‐device network. The model is formulated as a constrained non‐linear programming problem. The training data are generated by a standard optimisation tool. Then, an artificial neural network is designed to learn the system from the training data. Simulation results show the effectiveness of deep leaning.