TY - GEN
T1 - Joint access and backhaul resource management for ultra-dense networks
AU - Zhuang, Hongcheng
AU - Chen, Jun
AU - Wu, Dapeng Oliver
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2017/7/28
Y1 - 2017/7/28
N2 - Wireless backhauling is a promising technology for Ultra-Dense Networks (UDN). Resource management for access and backhaul is a key issue. Different from conventional resource allocation approaches, we partition radio resources for access and backhaul, taking into account the impacts of cooperative transmission modes. This problem is formulated to maximize the area throughput of UDN to obtain the optimal resource partition and power allocation. It includes two coupling problems and thus is difficult to solve. Firstly we prove the power allocation problem i.e. beamforming problem can be equally decoupled from original problem. And then, the resource partition problem can be converted to a convex optimization problem. Finally, we can get the Pareto optimal solution to the original problem. Simulation results show the gains of the proposed approach.
AB - Wireless backhauling is a promising technology for Ultra-Dense Networks (UDN). Resource management for access and backhaul is a key issue. Different from conventional resource allocation approaches, we partition radio resources for access and backhaul, taking into account the impacts of cooperative transmission modes. This problem is formulated to maximize the area throughput of UDN to obtain the optimal resource partition and power allocation. It includes two coupling problems and thus is difficult to solve. Firstly we prove the power allocation problem i.e. beamforming problem can be equally decoupled from original problem. And then, the resource partition problem can be converted to a convex optimization problem. Finally, we can get the Pareto optimal solution to the original problem. Simulation results show the gains of the proposed approach.
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U2 - 10.1109/ICC.2017.7996390
DO - 10.1109/ICC.2017.7996390
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781467389990
T3 - IEEE International Conference on Communications
BT - 2017 IEEE International Conference on Communications, ICC 2017
PB - IEEE
T2 - 2017 IEEE International Conference on Communications, ICC 2017
Y2 - 21 May 2017 through 25 May 2017
ER -