Deep Learning for Selection Between RF and VLC Bands in Device-to-Device Communication

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00343556" target="_blank" >RIV/68407700:21230/20:00343556 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/LWC.2020.3003786" target="_blank" >https://doi.org/10.1109/LWC.2020.3003786</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/LWC.2020.3003786" target="_blank" >10.1109/LWC.2020.3003786</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Deep Learning for Selection Between RF and VLC Bands in Device-to-Device Communication

Popis výsledku v původním jazyce

This letter focuses on the selection between radio frequency (RF) and visible light communications (VLC) bands for users exchanging data directly with each other via device-to-device (D2D) communication. We target to maximize the energy efficiency of D2D communication while the outage is minimized. Since the VLC channel can vary quickly due to the possible changes in irradiance and incidence angles, we aim to reach a quick band selection decision in a multi-user scenario based only on the knowledge of the received power and sum interference from all D2D transmitters at the individual D2D receivers. The proposed solution is based on a deep neural network making an initial band selection decision. Then, based on the DNN's output, a fast heuristic algorithm is proposed to further improve the band selection decision. The results show that the proposal reaches a close-to-optimal performance and outperforms the existing solutions in complexity, outage ratio, and energy efficiency.

Název v anglickém jazyce

Deep Learning for Selection Between RF and VLC Bands in Device-to-Device Communication

Popis výsledku anglicky

This letter focuses on the selection between radio frequency (RF) and visible light communications (VLC) bands for users exchanging data directly with each other via device-to-device (D2D) communication. We target to maximize the energy efficiency of D2D communication while the outage is minimized. Since the VLC channel can vary quickly due to the possible changes in irradiance and incidence angles, we aim to reach a quick band selection decision in a multi-user scenario based only on the knowledge of the received power and sum interference from all D2D transmitters at the individual D2D receivers. The proposed solution is based on a deep neural network making an initial band selection decision. Then, based on the DNN's output, a fast heuristic algorithm is proposed to further improve the band selection decision. The results show that the proposal reaches a close-to-optimal performance and outperforms the existing solutions in complexity, outage ratio, and energy efficiency.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20203 - Telecommunications

Projekt

<a href="/cs/project/GA17-17538S" target="_blank" >GA17-17538S: Kombinace radiofrekvenčního pásma a viditelného spektra pro přímou komunikaci mezi zařízeními</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Wireless Communications Letters

ISSN

2162-2337

e-ISSN

2162-2345

Svazek periodika

9

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

5

Strana od-do

1763-1767

Kód UT WoS článku

000577969000036

EID výsledku v databázi Scopus

2-s2.0-85092771813