  Growing attentions have been paid to renewable energy or hybrid energy
powered heterogeneous networks (HetNets). In this paper, focusing on
backhaul-aware joint user association and resource allocation for this type of
HetNets, we formulate an online optimization problem to maximize the network
utility reflecting proportional fairness. Since user association and resource
allocation are tightly coupled not only on resource consumption of the base
stations (BSs), but also in the constraints of their available energy and
backhaul, the closed-form solution is quite difficult to obtain. Thus, we solve
the problem distributively via employing some decomposition methods.
Specifically, at first, by adopting primal decomposition method, we decompose
the original problem into a lower-level resource allocation problem for each
BS, and a higher-level user association problem. For the optimal resource
allocation, we prove that a BS either assigns equal normalized resources or
provides equal long-term service rate to its served users. Then, the user
association problem is solved by Lagrange dual decomposition method, and a
completely distributed algorithm is developed. Moreover, applying results of
the subgradient method, we demonstrate the convergence of the proposed
distributed algorithm. Furthermore, in order to efficiently and reliably apply
the proposed algorithm to the future wireless networks with an extremely dense
BS deployment, we design a virtual user association and resource allocation
scheme based on the software-defined networking architecture. Lastly, numerical
results validate the convergence of the proposed algorithm and the significant
improvement on network utility, load balancing and user fairness.
