The integration of millimeter-wave (mmWave) communication with conventional microwave transmission in the heterogeneous networks (HetNets) has recently emerged as an attractive solution to meet the exponentially increasing demand on mobile data traffic. Moreover, this integration combined with dual-connectivity (DC) technology is expected to further guarantee reliable transmission of as many users as possible. In this letter, from the point of user association, a downlink DC approach in the integrated HetNets is proposed. The objective is to improve the access-fairness among users, while guaranteeing the maximization of total throughput utility. First, the DC-enabled user association problem in mmWave-aided HetNets is formulated as a nonlinear integer programming problem. Then, a two-level iterative algorithm is proposed to achieve the sub-optimal user association. Finally, the numerical results show the effectiveness of our proposed algorithm.

The generalized maximum correntropy criterion (GMCC) algorithm is computationally simple and robust against impulsive noise but it suffers from slow convergence speed as it is derived and based on stochastic gradient, which only use the current data sample. In order to deal with this issue, a smoothed GMCC algorithm (SGMCC) is proposed. In the SGMCC algorithm, instead of taking the exponential weighted average of gradient vector to approximate the expectation of the gradient vector, we take the exponential weighted average of the variable step-size so that the SGMCC algorithm can be viewed as a sign GMCC algorithm with smoothed variable step-size. Moreover, convergence performance analyses are derived in terms of variable step-size, mean-square stability and steady-state behavior to demonstrate the robustness of the proposed algorithm. At last, simulation comparisons show that the proposed algorithm is robust against impulsive noise and converges fast with lower computational complexity. Also, for the steady-state behavior, simulation results verify that the simulated value matches well with the theoretical one.

By introducing the concept of dual connectivity (DC), joint user association and resource allocation for heterogeneous networks (HetNets) with backhaul constraint have been investigated. However, co-channel scenario is rarely considered in DC-enabled HetNets due to inter-tier interference. To solve this issue, enhanced intercell interference coordination (eICIC) via almost blank subframe (ABS) is introduced into DC-enabled HetNets with backhaul constraint. The objective is to improve overall system throughout while providing quality-of-service (QoS) guarantees on user’s rate. First, the joint DC-enabled user association and resource allocation problem is formulated as an mixed integer nonlinear programming (MINLP) problem. Then, by linearizing the products of the variables, the original problem is reformulated into a linear problem. Last, a low-complexity heuristic method to achieve the near-optimal solution is proposed. Also, the numerical results show the superiority of our algorithm.

Due to the Quality-of-Experience (QoE) degradation caused by the mismatch of supply and demand rate in heterogeneous wireless network (HWN), we introduce the idea of intent driven network (IDN) to associate the user intent (UI) with the network QoE strategy under a software-defined framework. We specifically construct a UI-aware QoE model to quantify the effect of dynamic request rate on actual QoE. Based on this model, we formulate a QoE maximization problem to adaptively match supply-demand rates. As a multivariable combinatorial optimization problem, we firstly present a robust algorithm based on simulated-annealing (SA) to obtain the approximate optimal solution as much as possible. Moreover, we present a genetic algorithm (GA) on the basis of the initial SA algorithm to improve the search accuracy of each step for more practical application. Compared with three schemes without UI interference, our approaches raise average QoE by at least 42.1%.