User Association In HetNets Research Articles

Multi-Objective Optimization of User Association in HetNets With Hybrid Power Supply

In this paper, we focus on proposing an appropriate user association method to improve the performance of HetNets supplied with hybrid energy sources (on-grid power and renewable energy). We first describe traffic and energy models, and then formulate the user association problem as a multi-objective optimization problem to minimize the average waiting delay of users and on-grid power consumption. Then we reformulate the multi-objective and integer optimization problem to single-objective convex optimization problem by using weight sum and variable substitution method. After that, an iterative algorithm is proposed for the user association problem and can be proved to converge to the global optimal solution. Simulation results show that the proposed algorithm in this paper can achieve different traffic load distributions by using different weight coefficients. In addition, the proposed algorithm has better performance in the average waiting delay of users and on-grid power consumption compared with traditional maxSINR user association algorithm. Finally, simulation results show the performance of the network can be adjusted by the renewable energy output power of BSs in the network.

User Association in HetNets: Impact of Traffic Differentiation and Backhaul Limitations

Operators, struggling to continuously add capacity and upgrade their architecture to keep up with data traffic increase, are turning their attention to denser deployments that improve spectral efficiency. Denser deployments make the problem of user association challenging, and much work has been devoted to finding algorithms that strike a tradeoff between user quality of service, and network-wide performance (load-balancing). Nevertheless, the majority of these algorithms typically consider simple setups with a single type of traffic, usually elastic non-guaranteed bit rate (GBR). They also focus on the radio access part, ignoring the backhaul topology and potential capacity limitations. Backhaul constraints are emerging as a key performance bottleneck in future networks, partly due to the continuous improvement of the radio interface, and partly due to the need for inexpensive backhaul links to reduce capital and operational expenditures. To this end, we propose an analytical framework for user association that jointly considers radio access and backhaul network performance. Specifically, we derive an algorithm that takes into account spectral efficiency, base station load, backhaul link capacities and topology, and two traffic classes (GBR and non-GBR) in both the uplink and downlink directions. We prove analytically an optimal user association rule that ends up maximizing either an arithmetic or a weighted harmonic mean of the achieved performance along different dimensions (e.g., uplink and downlink performances or GBR and non-GBR performances). We then use extensive simulations to study the impact of: 1) traffic differentiation; and 2) backhaul capacity limitations and topology on key performance metrics.

An Improved User Association Algorithm for MAP–FAPs Heterogeneous Networks

Heterogeneous networks (HetNets) give users the opportunity to access different access points(APs), which will simultaneously affect user performance and system performance, so user association in HetNets plays a critical role in enhancing the load balancing and the system sum-throughput of networks. Meanwhile, the incremental sum-throughput currently fails to meet the escalating data demands. Besides, ensuring fairness amongst users constitutes another urgent issue in the radio resource management (RRM) of HetNets. What is more, few works consider the maximum service user number constraint in femtocell access points (FAPs). To solve the aforementioned problem, this paper associates users to APs by considering system sum-throughput and fairness at the same time in HetNets under a maximum service user number constraint of FAPs; accordingly, the user association problem is formulated. By releasing constraint, the optimal user association algorithm is obtained by Lagrangian function, and based on this optimal solution, a low complexity suboptimal user association algorithm is proposed. At last, this paper investigates the relationship between system sum-throughput and maximum service user number of FAPs. Numerical simulation results show that the proposed algorithm can improve sum-throughput and fairness at the same time at a specific maximum service user number of FAPs.

User Association With Unequal User Priorities in Heterogeneous Cellular Networks

In heterogeneous networks (HetNets), the load between macrocell base stations (MBSs) and small-cell base stations (SBSs) is imbalanced due to their different transmission powers and locations. This load imbalance significantly impacts system performance and affects the experience of mobile users (MUs) with different priorities. In this paper, we aim to distributively optimize the user association in HetNets with various user priorities to solve the load balancing problem. Since the user association is a binary matching problem, which is NP-hard, we propose a distributed belief propagation (BP) algorithm to approach the optimal solution. We first develop a factor graph model, using the network topology, to represent this user association problem. With this factor graph, we propose a novel distributed BP algorithm by adopting the proportional fairness as the objective. Next, we theoretically prove the existence of the fixed point in our BP algorithm. To be more practical, we develop an approximation method to significantly reduce the computational and communication complexity of the BP algorithm. Furthermore, we analyze some properties of the factor graph relevant to the performance of the BP algorithm using the stochastic geometry. Simulation results show that 1) the proposed BP algorithm well approaches the optimal system performance and achieves a much better performance compared with other association schemes and that 2) the analytical results on the average degree distribution and sparsity of the factor graph match with those obtained from the Monte Carlo simulations.

User Association in 5G Networks: A Survey and an Outlook

The fifth generation (5G) mobile networks are envisioned to support the deluge of data traffic with reduced energy consumption and improved quality of service (QoS) provision. To this end, the key enabling technologies, such as heterogeneous networks (HetNets), massive multiple-input multiple-output (MIMO) and millimeter wave (mmWave) techniques, are identified to bring 5G to fruition. Regardless of the technology adopted, a user association mechanism is needed to determine whether a user is associated with a particular base station (BS) before the data transmission commences. User association plays a pivotal role in enhancing the load balancing, the spectrum efficiency and the energy efficiency of networks. The emerging 5G networks introduce numerous challenges and opportunities for the design of sophisticated user association mechanisms. Hence, substantial research efforts are dedicated to the issues of user association in HetNets, massive MIMO networks, mmWave networks and energy harvesting networks. We introduce a taxonomy as a framework for systematically studying the existing user association algorithms. Based on the proposed taxonomy, we then proceed to present an extensive overview of the state-of-the-art in user association conceived for HetNets, massive MIMO, mmWave and energy harvesting networks. Finally, we summarize the challenges as well as opportunities of user association in 5G and provide design guidelines and potential solutions for sophisticated user association mechanisms.

5G technology requirements and related test environments for evaluation

A novel user association model for heterogeneous network (HetNet) with dual connectivity (DC) and constrained backhaul is proposed in this paper, where not only the best combination of serving macro cell and small cell for each user to associate is selected but also the optimal traffic split between the macro cell and small cell is determined to enhance both radio resource efficiency and backhaul capacity utilization. To solve this optimization problem, an intuitive algorithm based on iteratively solving two sub-problems is proposed. One sub-problem is a binary integer programming problem and a corresponding greedy algorithm is proposed, while the other sub-problem is a simple linear programming problem and can be easily solved. Numerical results show that the proposed model and algorithm can achieve better radio resource efficiency and backhaul capacity utilization compared with user association in HetNet without DC, which validate the capacity enhancement potentials of radio resource coordination in HetNet with DC.