TY - JOUR
T1 - An Energy Consumption Model for WiFi Direct Based D2D Communications
AU - Usman, Muhammad
AU - Asghar, Muhammad Rizwan
AU - Ansari, Imran Shafique
AU - Qaraqe, Marwa
AU - Granelli, Fabrizio
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018
Y1 - 2018
N2 - WiFi direct is a variant of Infrastructure mode WiFi, which is designed to enable direct Device-to-Device (D2D) communications between proximity devices. This new technology enables various proximity-based services such as social networking, multimedia content distribution, cellular traffic offloading, Internet of Things (IoT), and mission critical communications. However, energy consumption of battery-constrained devices remains a major concern in all the aforementioned applications. In this paper, we model energy consumption of the WiFi direct protocol, starting from device discovery to actual data transmissions for intra group D2D communications. We simulate a content distribution scenario in Matlab and analyze our model for the energy consumption of the devices. We argue that the energy spent in device discovery becomes significant in the case of small data sizes. In particular, we find that smaller data sizes, such as 100KB, cause the equal amount of energy to spend in both device discovery and data transmission phases, even when the device discovery time is very small.
AB - WiFi direct is a variant of Infrastructure mode WiFi, which is designed to enable direct Device-to-Device (D2D) communications between proximity devices. This new technology enables various proximity-based services such as social networking, multimedia content distribution, cellular traffic offloading, Internet of Things (IoT), and mission critical communications. However, energy consumption of battery-constrained devices remains a major concern in all the aforementioned applications. In this paper, we model energy consumption of the WiFi direct protocol, starting from device discovery to actual data transmissions for intra group D2D communications. We simulate a content distribution scenario in Matlab and analyze our model for the energy consumption of the devices. We argue that the energy spent in device discovery becomes significant in the case of small data sizes. In particular, we find that smaller data sizes, such as 100KB, cause the equal amount of energy to spend in both device discovery and data transmission phases, even when the device discovery time is very small.
KW - 5G networks
KW - D2D communications
KW - Device discovery
KW - Energy efficiency
KW - Energy model
KW - Proximitybased services
KW - WiFi direct
UR - http://www.scopus.com/inward/record.url?scp=85063485319&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2018.8647905
DO - 10.1109/GLOCOM.2018.8647905
M3 - Conference article
AN - SCOPUS:85063485319
SN - 2334-0983
JO - Proceedings - IEEE Global Communications Conference, GLOBECOM
JF - Proceedings - IEEE Global Communications Conference, GLOBECOM
M1 - 8647905
T2 - 2018 IEEE Global Communications Conference, GLOBECOM 2018
Y2 - 9 December 2018 through 13 December 2018
ER -