Abstract
The introduction of device-to-device (D2D) into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of user equipments (UEs). In this paper, we propose a distributed interference-aware energy-efficient resource allocation algorithm to maximize each UE's energy efficiency (EE) subject to its specific quality of service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. The formulated EE maximization problem is a non-convex problem and is transformed into a convex optimization problem by exploiting the properties of the nonlinear fractional programming. An iterative optimization algorithm is proposed and verified through computer simulations.
| Original language | English |
|---|---|
| Title of host publication | 2014 IEEE Global Communications Conference, GLOBECOM 2014 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 4454-4459 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781479935116 |
| DOIs | |
| Publication status | Published - 2014 Feb 9 |
| Event | 2014 IEEE Global Communications Conference, GLOBECOM 2014 - Austin, United States Duration: 2014 Dec 8 → 2014 Dec 12 |
Other
| Other | 2014 IEEE Global Communications Conference, GLOBECOM 2014 |
|---|---|
| Country | United States |
| City | Austin |
| Period | 14/12/8 → 14/12/12 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Computer Networks and Communications
- Communication
Cite this
Distributed interference-aware energy-efficient resource allocation for device-to-device communications underlaying cellular networks. / Zhou, Zhenyu; Dong, Mianxiong; Ota, Kaoru; Wu, Jun; Sato, Takuro.
2014 IEEE Global Communications Conference, GLOBECOM 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 4454-4459 7037509.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Distributed interference-aware energy-efficient resource allocation for device-to-device communications underlaying cellular networks
AU - Zhou, Zhenyu
AU - Dong, Mianxiong
AU - Ota, Kaoru
AU - Wu, Jun
AU - Sato, Takuro
PY - 2014/2/9
Y1 - 2014/2/9
N2 - The introduction of device-to-device (D2D) into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of user equipments (UEs). In this paper, we propose a distributed interference-aware energy-efficient resource allocation algorithm to maximize each UE's energy efficiency (EE) subject to its specific quality of service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. The formulated EE maximization problem is a non-convex problem and is transformed into a convex optimization problem by exploiting the properties of the nonlinear fractional programming. An iterative optimization algorithm is proposed and verified through computer simulations.
AB - The introduction of device-to-device (D2D) into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of user equipments (UEs). In this paper, we propose a distributed interference-aware energy-efficient resource allocation algorithm to maximize each UE's energy efficiency (EE) subject to its specific quality of service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. The formulated EE maximization problem is a non-convex problem and is transformed into a convex optimization problem by exploiting the properties of the nonlinear fractional programming. An iterative optimization algorithm is proposed and verified through computer simulations.
UR - http://www.scopus.com/inward/record.url?scp=84988290607&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84988290607&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2014.7037509
DO - 10.1109/GLOCOM.2014.7037509
M3 - Conference contribution
AN - SCOPUS:84988290607
SP - 4454
EP - 4459
BT - 2014 IEEE Global Communications Conference, GLOBECOM 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -