TY - GEN
T1 - Distributed optimization for downlink broadband small cell networks
AU - Guo, Shaozhen
AU - Xing, Chengwen
AU - Fei, Zesong
AU - Wang, Hualei
AU - Pan, Zhengang
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/9
Y1 - 2015/9/9
N2 - Small cell networks have been recognized as a promising technology to realize high spectrum and energy efficiency communications in future wireless networks. However, the capacity of small cell networks is limited by the interference among the links communicating simultaneously. Efficient resource allocation and effective interference management is definitely imperative for small cells. In this paper, we propose an algorithm to optimize the power and subcarrier allocation jointly in order to maximize the weighted sum rate for dense small cell networks. Facing with a large amount of small cells, the optimization problem is in nature a large scale optimization problem. Using advanced decomposition theory, the proposed algorithm can effectively decompose the considered optimization problem into a series of much simpler subproblems which can be efficiently solved in parallel. Finally, simulation results demonstrate that the proposed algorithm enjoys greater performance gain and faster convergence as compared to the existing schemes.
AB - Small cell networks have been recognized as a promising technology to realize high spectrum and energy efficiency communications in future wireless networks. However, the capacity of small cell networks is limited by the interference among the links communicating simultaneously. Efficient resource allocation and effective interference management is definitely imperative for small cells. In this paper, we propose an algorithm to optimize the power and subcarrier allocation jointly in order to maximize the weighted sum rate for dense small cell networks. Facing with a large amount of small cells, the optimization problem is in nature a large scale optimization problem. Using advanced decomposition theory, the proposed algorithm can effectively decompose the considered optimization problem into a series of much simpler subproblems which can be efficiently solved in parallel. Finally, simulation results demonstrate that the proposed algorithm enjoys greater performance gain and faster convergence as compared to the existing schemes.
KW - Distributed optimization
KW - broadband communications
KW - small cells
UR - http://www.scopus.com/inward/record.url?scp=84953740107&partnerID=8YFLogxK
U2 - 10.1109/ICC.2015.7248862
DO - 10.1109/ICC.2015.7248862
M3 - Conference contribution
AN - SCOPUS:84953740107
T3 - IEEE International Conference on Communications
SP - 3472
EP - 3476
BT - 2015 IEEE International Conference on Communications, ICC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Conference on Communications, ICC 2015
Y2 - 8 June 2015 through 12 June 2015
ER -