5 research outputs found
Distributed Energy and Resource Management for Full-Duplex Dense Small Cells for 5G
We consider a multi-carrier and densely deployed small cell network, where
small cells are powered by renewable energy source and operate in a full-duplex
mode. We formulate an energy and traffic aware resource allocation optimization
problem, where a joint design of the beamformers, power and sub-carrier
allocation, and users scheduling is proposed. The problem minimizes the sum
data buffer lengths of each user in the network by using the harvested energy.
A practical uplink user rate-dependent decoding energy consumption is included
in the total energy consumption at the small cell base stations. Hence,
harvested energy is shared with both downlink and uplink users. Owing to the
non-convexity of the problem, a faster convergence sub-optimal algorithm based
on successive parametric convex approximation framework is proposed. The
algorithm is implemented in a distributed fashion, by using the alternating
direction method of multipliers, which offers not only the limited information
exchange between the base stations, but also fast convergence. Numerical
results advocate the redesigning of the resource allocation strategy when the
energy at the base station is shared among the downlink and uplink
transmissions.Comment: In Proc. of IEEE IWCMC-2017, Valencia, Spain, Jun. 201