  With the rapid growth of mobile traffic demand, a promising approach to
relieve cellular network congestion is to offload users' traffic to small-cell
networks. In this paper, we investigate how the mobile users (MUs) can
effectively offload traffic by taking advantage of the capability of
dual-connectivity, which enables an MU to simultaneously communicate with a
macro base station (BS) and a small-cell access point (AP) via two
radio-interfaces. Offloading traffic to the AP usually reduces the MUs' mobile
data cost, but often at the expense of suffering increased interferences from
other MUs at the same AP. We thus formulate an optimization problem that
jointly determines each MU's traffic schedule (between the BS and AP) and power
control (between two radio-interfaces). The system objective is to minimize all
MUs' total cost, while satisfying each MU's transmit-power constraints through
proper interference control. In spite of the non-convexity of the problem, we
design both a centralized algorithm and a distributed algorithm to solve the
joint optimization problem. Numerical results show that the proposed algorithms
can achieve the close-to-optimum results comparing with the ones achieved by
the LINGO (a commercial optimization software), but with significantly less
computational complexity. The results also show that the proposed adaptive
offloading can significantly reduce the MUs' cost, i.e., save more than 75% of
the cost without offloading traffic and 65% of the cost with a fixed
offloading.
