Deep Reinforcement Learning for Intelligent Reflecting Surface-assisted D2D Communications

Khoi Khac Nguyen, Antonino Masaracchia, Cheng Yin — Tue, 03 Jan 2023 00:00:00 +0000

In this paper, we propose a deep reinforcement learning (DRL) approach for solving the optimisation problem of the network’s sum-rate in device-to-device (D2D) communications supported by an intelligent reflecting surface (IRS). The IRS is deployed to mitigate the interference and enhance the signal between the D2D transmitter and the associated D2D receiver. Our objective is to jointly optimise the transmit power at the D2D transmitter and the phase shift matrix at the IRS to maximise the network sum-rate. We formulate a Markov decision process and then propose the proximal policy optimisation for solving the maximisation game. Simulation results show impressive performance in terms of the achievable rate and processing time.

AgFAB - A Farmer-centered Agricultural Bower

Muhammad Azhar Iqbal, Brianna B. Posadas, Fudi Qin, Bohan Liu, Ali Siddique — Wed, 08 Feb 2023 00:00:00 +0000

Digital Agriculture aims to raise agricultural productivity while empowering the farming stakeholders (especially the farmers) with the availability of ICT-based applications on smart devices. However, despite putting in much effort, smallholder farmers’ willingness for adopting digital technologies is low in developing countries. In this study, following the principles of the human-design process, we investigated the smallholder farmers’ core demands from mobile/computing application(s). Considering these core demands of the farming community, the developed prototypical interfaces were evaluated by farmers using the System Usability Scale (SUS) to check the acceptability of a proposed farmer-centered solution named AgFAB. The AgFAB prototypical interface design received an average SUS score of 72.37, which is an indication of an acceptable design. Moreover, the results of Paired T-test seem promising for the strong adoptability of AgFAB by farmers with reference to their aspect of usability in the agricultural context.

EAI Endorsed Transactions on Industrial Networks and Intelligent Systems

Deep Reinforcement Learning for Intelligent Reflecting Surface-assisted D2D Communications

AgFAB - A Farmer-centered Agricultural Bower