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Joint Lifetime-Outage Optimization in Relay-Enabled IoT Networks—A Deep Reinforcement Learning Approach | IEEE Journals & Magazine | IEEE Xplore

Joint Lifetime-Outage Optimization in Relay-Enabled IoT Networks—A Deep Reinforcement Learning Approach


Abstract:

Network lifetime maximization in Internet of things (IoT) is of paramount importance to ensure uninterrupted data transmission and reduce the frequency of battery replace...Show More

Abstract:

Network lifetime maximization in Internet of things (IoT) is of paramount importance to ensure uninterrupted data transmission and reduce the frequency of battery replacement. This letter deals with the joint lifetime-outage optimization in relay-enabled IoT networks employing a multiple relay selection (MRS) scheme. The considered MRS problem is essentially a general nonlinear 0-1 programming which is NP-hard. In this work, we use the application of the double deep Q network (DDQN) algorithm to solve the MRS problem. Our results reveal that the proposed DDQN-MRS scheme can achieve superior performance than the benchmark MRS schemes.
Published in: IEEE Communications Letters ( Volume: 27, Issue: 1, January 2023)
Page(s): 190 - 194
Date of Publication: 12 October 2022

ISSN Information:


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