Просмотреть запись

A Machine Learning Based Energy-Efficient Non-Orthogonal Multiple Access Scheme

Электронный архив ТПУ

Информация об архиве | Просмотр оригинала
 
 
Поле Значение
 
Заглавие A Machine Learning Based Energy-Efficient Non-Orthogonal Multiple Access Scheme
 
Автор Khan, Rabia
Dzhayakodi (Jayakody) Arachshiladzh, Dushanta Nalin Kumara
Vishal Sharma
Vinay Kumar
Kuljeet Kaur
Zheng Chang
 
Тематика BEEM-NOMA
cooperative communication
EE
GLMA
ITS
ITS
ML
NOMA
point-to-point communication
RFEH
множественный доступ
машинное обучение
искусственный интеллект
беспроводная связь
передача данных
надежность
энергоэффективность
энергоэффективные системы
 
Описание Applicability of Artificial Intelligent (AI) and NonOrthogonal Multiple Access (NOMA) have drawn remarkable attraction towards the implementation of 5th Generation (5G) wireless communication systems. 5G demands significant improvements in terms of data rate, throughput, reliability, Quality of Service (QoS), fairness, Symbol Error Rate (SER), Outage, reliability and latency as compared to the current standards. The aforementioned parameters have a critical impact when applied to the Internet of Thing (IoT). Considering the demand of high power and energy, we have optimized Energy-Efficiency (EE) and Radio Frequency Energy Harvesting (RFEH) using Machine Learning based Genetic Algorithm (MLGA). For the system integration, we proposed to Built-in Energy Efficient Modulation based NOMA (BEEM-NOMA). BEEM NOMA is an energy efficient system that has the capability to prevent the waste of energy. Combination of BEEM-NOMA with MLGA further enhances the performance of the system, as proved with the simulation results in this paper.
 
Дата 2020-01-23T09:13:06Z
2020-01-23T09:13:06Z
2019
 
Тип Conference Paper
Published version (info:eu-repo/semantics/publishedVersion)
Conference paper (info:eu-repo/semantics/conferencePaper)
 
Идентификатор A Machine Learning Based Energy-Efficient Non-Orthogonal Multiple Access Scheme / R. Khan [et al.] // 14th International Forum on Strategic Technology (IFOST-2019), October 14-17, 2019, Tomsk, Russia : [proceedings]. — Tomsk : TPU Publishing House, 2019. — [С. 330-335].
http://earchive.tpu.ru/handle/11683/57475
 
Язык en
 
Связанные ресурсы 14th International Forum on Strategic Technology (IFOST-2019), October 14-17, 2019, Tomsk, Russia : [proceedings]. — Tomsk, 2019.
 
Права Open access (info:eu-repo/semantics/openAccess)