Networked MIMO with fractional joint transmission in energy harvesting systems

LANGUAGE English SOURCE

IEEE Trans. Commun., 2016, 64(8):3323-3336.

Published Date:2016

ABSTRACT This paper considers two base stations (BSs)
powered by renewable energy serving two users cooperatively.
With different BS energy arrival rates, a fractional joint transmission
(JT) strategy is proposed, which divides each transmission
frame into two subframes. In the first subframe, one BS
keeps silent to store energy, while the other transmits data, and
then, they perform zero-forcing JT (ZF-JT) in the second subframe.
We consider the average sum-rate maximization problem
by optimizing the energy allocation and the time fraction of
ZF-JT separately. First, the sum-rate maximization for given
energy budgets in each frame is analyzed. We prove that the
optimal transmit power can be derived in closed form, and the
optimal time fraction can be found via bi-section search. Second,
an approximate dynamic programming algorithm is introduced
to determine the energy allocation among frames. We adopt a
linear approximation with the features associated with system
states and determine the weights of features by simulation. We
also operate the approximation several times with random initial
policy, named policy exploration, to broaden the policy search
range. Numerical results show that the proposed fractional JT
greatly improves the performance. In addition, appropriate policy
exploration is shown to perform close to the optimal.