Joint lifetime-outage optimization in relay-enabled IoT networks—A deep reinforcement learning approach

Name: Joint lifetime-outage optimization in relay-enabled IoT networks—A deep reinforcement learning approach
Author: Heidarpour, A. R., Heidarpour, M. R., Ardakani, M., Tellambura, C., Uysal, Murat

İsim	Joint lifetime-outage optimization in relay-enabled IoT networks—A deep reinforcement learning approach
Yazar	Heidarpour, A. R., Heidarpour, M. R., Ardakani, M., Tellambura, C., Uysal, Murat
Basım Tarihi:	2023-01
Basım Yeri	- IEEE
Konu	Cooperative communication, Deep reinforcement learning, Internet of Things, Lifetime, Multiple relay selection
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	1089-7798
Kayıt Numarası	9c4ca822-63ff-4cfc-94a5-3916e1779676
Lokasyon	Electrical & Electronics Engineering
Tarih	2023-01
Örnek Metin	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.
DOI	10.1109/LCOMM.2022.3214146
Cilt	27

Kaynağa git Özyeğin Üniversitesi

Aramaya Dön

Özyeğin Üniversitesi

Kaynağa git

Joint lifetime-outage optimization in relay-enabled IoT networks—A deep reinforcement learning approach

Yazar Heidarpour, A. R., Heidarpour, M. R., Ardakani, M., Tellambura, C., Uysal, Murat

Basım Tarihi 2023-01

Basım Yeri - IEEE

Konu Cooperative communication, Deep reinforcement learning, Internet of Things, Lifetime, Multiple relay selection

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 1089-7798

Kayıt Numarası 9c4ca822-63ff-4cfc-94a5-3916e1779676

Lokasyon Electrical & Electronics Engineering

Tarih 2023-01

Örnek Metin 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.

DOI 10.1109/LCOMM.2022.3214146

Cilt 27