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.
Original language | English (US) |
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Pages (from-to) | 190-194 |
Number of pages | 5 |
Journal | IEEE Communications Letters |
Volume | 27 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2023 |
Keywords
- Internet of Things
- cooperative communication
- deep reinforcement learning
- lifetime
- multiple relay selection
ASJC Scopus subject areas
- Modeling and Simulation
- Computer Science Applications
- Electrical and Electronic Engineering