Unified and Distributed QoS-Driven Cell Association Algorithms in Heterogeneous Networks

This paper addresses the cell association problem in the downlink of a multi-tier heterogeneous network (HetNet), where base stations (BSs) have finite number of resource blocks (RBs) available to distribute among their associated users. Two problems are defined and treated in this paper: sum utility of long term rate maximization with long term rate quality of service (QoS) constraints, and global outage probability minimization with outage QoS constraints. The first problem is well-suited for low mobility environments, while the second problem provides a framework to deal with environments with fast fading. The defined optimization problems in this paper are solved in two phases: cell association phase followed by the optional RB distribution phase. We show that the cell association phase of both problems have the same structure. Based on this similarity, we propose a unified distributed algorithm with low levels of message passing to for the cell association phase. This distributed algorithm is derived by relaxing the association constraints and using Lagrange dual decomposition method. In the RB distribution phase, the remaining RBs after the cell association phase are distributed among the users. Simulation results show the superiority of our distributed cell association scheme compared to schemes that are based on maximum signal to interference plus noise ratio (SINR)

Adaptive Biasing Cell Association in FFR Aided Multi-tier Heterogeneous Networks under Dynamic Load Variation

Heterogeneous networks (HetNets) adopting fractional frequency reuse (FFR) improves cell coverage, network capacity, efficiency, assures higher data rates, and better quality of service (QoS) for next generation wireless networks. However they fail to handle dynamic load variation. So we attempt biasing cell association (BCA) to offload user from macrocell to small cell base stations (SCBs) to overcome capacity reduction and throughput degradation. It is based on range expansion of SCBSs by adding a positive bias to the reference signal received power (RSRP). In this paper we propose a FFR aided twin layer HetNet with an adaptive biasing scheme for load balancing. For users offloading a cell is selected by self-organizing network (SON) with adaptive bias value using Q-learning algorithm. Simulation result show that our system model can handle dynamic load variation with proper utilization of available bandwidth and mitigate interference better than the conventional HetNet design

User Association in Cell-less 5G Networks Exploiting Particle Swarm Optimisation

In heterogeneous networks (HetNets), users can by default associate with the macro base stations (BSs) while the small cell BSs are underloaded. Biasing user association is a simple and realistic approach to balance the load in HetNets, as well as creating a cell-less architecture where a user does not connect to the closest base station. Most of the existing research focuses on the static biasing scheme which is not the optimal strategy to improve the system performance. In this paper, the biasing factors are generated dynamically by the algorithm of particle swarm optimisation (PSO) with the objective of balancing the load and maximising the cell spectral efficiency (CSE). This work studies two different interference cases: the first case is when each tier uses different radio resources (typical when multiple radio access technologies are used) and a user receives interference only from same-tier base stations, whereas the second interference case is when all tiers use the same radio resources and a user receives interference from the same-tier and other tier BSs. The simulation results show that the dynamic biasing using PSO outperforms the static biasing in terms of balancing the load and maximising the CSE

Energy and throughput efficient strategies for heterogeneous future communication networks

As a result of the proliferation of wireless-enabled user equipment and data-hungry applications, mobile data traffic has exponentially increased in recent years.This in-crease has not only forced mobile networks to compete on the scarce wireless spectrum but also to intensify their power consumption to serve an ever-increasing number of user devices. The Heterogeneous Network (HetNet) concept, where mixed types of low-power base stations coexist with large macro base stations, has emerged as a potential solution to address power consumption and spectrum scarcity challenges. However, as a consequence of their inflexible, constrained, and hardware-based configurations, HetNets have major limitations in adapting to fluctuating traffic patterns. Moreover, for large mobile networks, the number of low-power base stations (BSs) may increase dramatically leading to sever power consumption. This can easily overwhelm the benefits of the HetNet concept. This thesis exploits the adaptive nature of Software-defined Radio (SDR) technology to design novel and optimal communication strategies. These strategies have been designed to leverage the spectrum-based cell zooming technique, the long-term evolution licensed assisted access (LTE-LAA) concept, and green energy, in order to introduce a novel communication framework that endeavors to minimize overall network on-grid power consumption and to maximize aggregated throughput, which brings significant benefits for both network operators and their customers. The proposed strategies take into consideration user data demands, BS loads, BS power consumption, and available spectrum to model the research questions as optimization problems. In addition, this thesis leverages the opportunistic nature of the cognitive radio (CR) technique and the adaptive nature of the SDR to introduce a CR-based communication strategy. This proposed CR-based strategy alleviates the power consumption of the CR technique and enhances its security measures according to the confidentiality level of the data being sent. Furthermore, the introduced strategy takes into account user-related factors, such as user battery levels and user data types, and network-related factors, such as the number of unutilized bands and vulnerability level, and then models the research question as a constrained optimization problem. Considering the time complexity of the optimum solutions for the above-mentioned strategies, heuristic solutions were proposed and examined against existing solutions. The obtained results show that the proposed strategies can save energy consumption up to 18%, increase user throughput up to 23%, and achieve better spectrum utilization. Therefore, the proposed strategies offer substantial benefits for both network operators and users

Inter-cell interference mitigation in LTE-advanced heterogeneous mobile networks

Heterogeneous Networks are one of the most effective solutions for enhancing the network performance of mobile systems, by deploying small cells within the coverage of the ordinary Macro cells. The goals of deploying such networks are to offload data from the possibly congested Macro cells towards the small cells and to achieve enhancements for outdoor/ indoor coverage in a cost-effective way. Moreover, heterogeneous networks aim to maximise the system capacity and to provide lower interference by reducing the distance between the transmitter and the receiver. However, inter-cell interference is a major technical challenge in heterogeneous networks, which mainly affects system performance and may cause a significant degradation in network throughput (especially for the edge users) in co-channel deployment. So, to overcome the aforementioned problem, both researchers and telecommunication operators are required to develop effective approaches that adapt different mobile system scenarios. The research study presented in this thesis provides a novel interference mitigation scheme, based on power control and time-domain inter-cell interference coordination to improve cell and users’ throughputs. In addition, powerful scheduling algorithms have been developed and optimised to adapt the proposed scheme for both macro and small cells. It is responsible for the optimum resource allocation to minimise the inter-cell interference to the minimum ranges. The focus of this work is for downlink inter-cell interference in Long Term Evolution (LTE- Advanced) mobile networks, as an example of OFDMA (orthogonal frequency division multiple access)-based networks. More attention is paid to the Pico cell as an important cell type in heterogeneous deployment, due to the direct backhauling with the macro cell to coordinate the resource allocation among cells tightly and efficiently. The intensive simulations and results analyses show that the proposed scheme demonstrates better performance with less complexity in terms of user and cell throughputs, and spectral efficiency, as compared with the previously employed schem

A comprehensive survey on radio resource management in 5G HetNets: current solutions, future trends and open issues

The 5G network technologies are intended to accommodate innovative services with a large influx of data traffic with lower energy consumption and increased quality of service and user quality of experience levels. In order to meet 5G expectations, heterogeneous networks (HetNets) have been introduced. They involve deployment of additional low power nodes within the coverage area of conventional high power nodes and their placement closer to user underlay HetNets. Due to the increased density of small-cell networks and radio access technologies, radio resource management (RRM) for potential 5G HetNets has emerged as a critical avenue. It plays a pivotal role in enhancing spectrum utilization, load balancing, and network energy efficiency. In this paper, we summarize the key challenges i.e., cross-tier interference, co-tier interference, and user association-resource-power allocation (UA-RA-PA) emerging in 5G HetNets and highlight their significance. In addition, we present a comprehensive survey of RRM schemes based on interference management (IM), UA-RA-PA and combined approaches (UA-RA-PA + IM). We introduce a taxonomy for individual (IM, UA-RA-PA) and combined approaches as a framework for systematically studying the existing schemes. These schemes are also qualitatively analyzed and compared to each other. Finally, challenges and opportunities for RRM in 5G are outlined, and design guidelines along with possible solutions for advanced mechanisms are presented