Backhaul-Aware User Association and Resource Allocation for Energy-Constrained HetNets
Qiaoni Han, Bo Yang, Guowang Miao, Cailian Chen, Xiaocheng Wang, and, Xinping Guan

TL;DR
This paper proposes a distributed, backhaul-aware user association and resource allocation algorithm for energy-constrained HetNets, improving network utility, load balancing, and fairness through decomposition methods and SDN-based virtual schemes.
Contribution
It introduces a novel distributed algorithm for joint user association and resource allocation in energy-constrained HetNets, incorporating backhaul awareness and SDN-based virtual schemes.
Findings
Algorithm converges reliably as shown by subgradient method.
Significant improvements in network utility, load balancing, and fairness.
Effective handling of energy constraints and backhaul limitations.
Abstract
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…
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