Stochastic Geometry Analysis and Additional Small Cell Deployment for HetNets Affected by Hot Spots

Hot spots (HSs) of mobile users that were not expected in the original network planning may occur after a heterogeneous network (HetNet) has been deployed and affect the network performance. In this case, deploying additional small cells on top of the existing HetNet without changing the existing network infrastructure is considered as a solution. In this paper, we first provide a stochastic geometry analysis for a HetNet affected by a large HS and for the additional small cells that need to be deployed based on the spatial bivariate Poisson point process. The optimal numbers of additional small cells required in the HS and non-HS areas are obtained by minimizing the difference between the numbers of macrocell users after and before the HS occurs based on the analytical results. We then propose an algorithm to maximize the average user throughput by jointly optimizing the locations of additional small cells and user associations of all cells. Simulation results show that the proposed algorithm can maintain the average user throughput above a threshold with excellent fairness among all users even for a very high density of HS users

Data Traffic Analysis and Small Cell Deployment in Cellular Networks

In this thesis, the study of small cell deployment in heterogeneous networks is presented. The research work can be divided into three aspects. The first part is user data traffic analysis for an existing 3G network in London. The second part is the deployment of additional small cells on top of existing heterogeneous networks. The third part is small cell deployment based on stochastic geometry analysis of heterogeneous networks. In the first part, an analysis of 3G network user downlink data traffic is presented. With the increasing demands for high data rate and energy-efficient cellular service, it is important to understand how cellular user data traffic changes over time and in space. A statistical model of time-varying throughput per cell and the distribution of instantaneous throughput per cell over different cells based on throughput measurements from a real-world large-scale urban cellular network are provided. The model can generate network traffic data that are very close to the measured traffic and can be used in simulations of large-scale urban-area mobile networks. In the second part of the work, three different small-cell deployment strategies are proposed. As the mobile data demand keeps growing, an existing heterogeneous network composed of macrocells and small cells may still face the problem of not being able to provide sufficient capacity for unexpected but reoccurring hot spots. The proposed strategies avoid replanning the overall network while fulfilling the hot spot demand by optimizing the deployment of additional mobile small cells on top of the existing HetNet. By simplified the optimization problem, we first proposed a fixed number deployment algorithm and then extend it into deployment over existing network algorithm to solve the joint optimization problem. The simulation results show that these two proposed algorithms require less small cells to be deployed while providing higher minimum user throughput. Moreover, a reduced-complexity iterative algorithm is proposed. The simulation results show that it significantly outperforms the random deployment of new small cells and achieves performance very close to numerically solving the joint optimization in terms of minimum user throughput and required number of new small cells, especially for a large number of unexpected hot-spot users. In the third part, a stochastic geometry analysis is provided for a heterogeneous network affected by a large hot spot. Based on the analysis, the optimal numbers of additional small cells required in the HS and non-HS areas are obtained by minimizing the difference between the numbers of macrocell users after and before the HS occurs. Then an algorithm is proposed to maximize the average user throughput by jointly optimizing the locations of additional small cells and user associations of all cells. Simulation results show that the proposed algorithm can maintain the average user throughput above a threshold with excellent fairness among all users even for a very high density of HS users

Advanced Technologies for Energy Saving, Wireless Backhaul and Mobility Management in Heterogeneous Networks

In recent years, due to the increasing number of existing and new devices and applications, the wireless industry has experienced an explosion of data traffic usage. As a result, new wireless technologies have been developed to address the capacity crunch. Long-Term Evolution-Licensed Assisted Access (LTE-LAA) is developed to provide the tremendous capacity by extending LTE to 5 GHz unlicensed spectrum. Hyper-dense small cells deployment is another promising technique that can provide a ten to one hundred times capacity gain by bringing small cells closer to mobile user equipments [1]. In this thesis, I focus on three problems related to these two techniques. In Chapter 3, I present a novel activation and sleep mechanism for energy efficient small cell heterogeneous networks (HetNets). In the cell-edge area of a macrocell, the coverage area of a sleeping small-cell will be covered by a range of expanded small-cells nearby. In contrast, in areas close to the macrocell, user equipment (UE) associated with a sleeping small cell will be distributed to the macrocell. Furthermore, the enhanced inter-cell interference coordination (eICIC) technique is used to support range-expanded small cells to avoid Quality of Service (QoS) degradation. Under both hexagonal and stochastic geometry based models, it is demonstrated that the proposed sleeping mechanism significantly reduces the energy consumption of the network compared with the conventional methods while guaranteeing the QoS requirements. Small cells are currently connected to limited backhaul to reduce the deployment and operational costs. In Chapter 4, an optimisation scheme is proposed for small cells to utilise the bandwidth of macrocells as wireless backhaul. I provide the numerical analysis of the performance of both the targeted small cell and the whole network. In Chapter 5, the mobility management (MM) of heterogeneous and LTE-LAA networks are investigated. To avoid Ping-Pong handover (PPHO) and reduce handover failure rate in HetNets, a self-optimisation algorithm is developed to change the handover parameters of a base station automagically. Furthermore, the MM of LTE-LAA networks is analysed. A new handover mechanism is proposed for LTE-LAA networks. Compared with the conventional LTE networks, LTE-LAA networks trigger the handover not only by using UE mobility, but also by the availability of the unlicensed band. A comprehensive analysis of the handover triggering event and handover procedure is presented. Simulation results show that by introducing handover triggered by available unlicensed band, the ratio of handover to unlicensed spectrum has a significant improvement. Therefore, a noticeable enhanced throughput of UEs is achievable by LTE-LAA networks

Tutorial on LTE/LTE-A Cellular Network Dimensioning Using Iterative Statistical Analysis

LTE is the fastest growing cellular technology and is expected to increase its footprint in the coming years, as well as progress toward LTE-A. The race among operators to deliver the expected quality of experience to their users is tight and demands sophisticated skills in network planning. Radio network dimensioning (RND) is an essential step in the process of network planning and has been used as a fast, but indicative, approximation of radio site count. RND is a prerequisite to the lengthy process of thorough planning. Moreover, results from RND are used by players in the industry to estimate preplanning costs of deploying and running a network; thus, RND is, as well, a key tool in cellular business modelling. In this work, we present a tutorial on radio network dimensioning, focused on LTE/LTE-A, using an iterative approach to find a balanced design that mediates among the three design requirements: coverage, capacity, and quality. This approach uses a statistical link budget analysis methodology, which jointly accounts for small and large scale fading in the channel, as well as loading due to traffic demand, in the interference calculation. A complete RND manual is thus presented, which is of key importance to operators deploying or upgrading LTE/LTE-A networks for two reasons. It is purely analytical, hence it enables fast results, a prime factor in the race undertaken. Moreover, it captures essential variables affecting network dimensions and manages conflicting targets to ensure user quality of experience, another major criterion in the competition. The described approach is compared to the traditional RND using a commercial LTE network planning tool. The outcome further dismisses the traditional RND for LTE due to unjustified increase in number of radio sites and related cost, and motivates further research in developing more effective and novel RND procedures

Robust Planning and Operation of Multi-Cell Homogeneous and Heterogeneous Networks

International audienceIn this work, we propose a robust planning tool that allocates power statically in homogeneous and heterogeneous cellular networks with non-regular base station (BTS) placement, to mitigate interference and improve overall performance. Each BTS will use the total available spectrum, but it will divide it into multiple sub-bands, and each BTS will transmit with a specific pre-computed power on each sub-band. We refer to such a power allocation as a power map. Our offline planning tool computes a robust power map for a given topology, by solving a non-convex, non-linear optimization problem, through simple transformations, based on geometric programming. The power map is computed based solely on the network topology, and it is made available to all BTSs that use it throughout the network operation to perform scheduling using a fast quasi-optimal online algorithm that we propose. We evaluate our planning tool for different homogeneous and heterogeneous networks (HetNets), first in a static setting where scheduling is performed optimally and then in a dynamic setting when scheduling is performed with our online scheduler. Results show that our solution significantly outperforms a classical equal power/fixed frequency reuse scheme in terms of sum-rate, by up to 30% in homogeneous networks and by up to 70% in HetNets

Drone-Assisted Wireless Communications

In order to address the increased demand for any-time/any-where wireless connectivity, both academic and industrial researchers are actively engaged in the design of the fifth generation (5G) wireless communication networks. In contrast to the traditional bottom-up or horizontal design approaches, 5G wireless networks are being co-created with various stakeholders to address connectivity requirements across various verticals (i.e., employing a top-to-bottom approach). From a communication networks perspective, this requires obliviousness under various failures. In the context of cellular networks, base station (BS) failures can be caused either due to a natural or synthetic phenomenon. Natural phenomena such as earthquake or flooding can result in either destruction of communication hardware or disruption of energy supply to BSs. In such cases, there is a dire need for a mechanism through which capacity short-fall can be met in a rapid manner. Drone empowered small cellular networks, or so-called \quotes{flying cellular networks}, present an attractive solution as they can be swiftly deployed for provisioning public safety (PS) networks. While drone empowered self-organising networks (SONs) and drone small cell networks (DSCNs) have received some attention in the recent past, the design space of such networks has not been extensively traversed. So, the purpose of this thesis is to study the optimal deployment of drone empowered networks in different scenarios and for different applications (i.e., in cellular post-disaster scenarios and briefly in assisting backscatter internet of things (IoT)). To this end, we borrow the well-known tools from stochastic geometry to study the performance of multiple network deployments, as stochastic geometry provides a very powerful theoretical framework that accommodates network scalability and different spatial distributions. We will then investigate the design space of flying wireless networks and we will also explore the co-existence properties of an overlaid DSCN with the operational part of the existing networks. We define and study the design parameters such as optimal altitude and number of drone BSs, etc., as a function of destroyed BSs, propagation conditions, etc. Next, due to capacity and back-hauling limitations on drone small cells (DSCs), we assume that each coverage hole requires a multitude of DSCs to meet the shortfall coverage at a desired quality-of-service (QoS). Hence, we consider the clustered deployment of DSCs around the site of the destroyed BS. Accordingly, joint consideration of partially operating BSs and deployed DSCs yields a unique topology for such PS networks. Hence, we propose a clustering mechanism that extends the traditional Mat\'{e}rn and Thomas cluster processes to a more general case where cluster size is dependent upon the size of the coverage hole. As a result, it is demonstrated that by intelligently selecting operational network parameters such as drone altitude, density, number, transmit power and the spatial distribution of the deployment, ground user coverage can be significantly enhanced. As another contribution of this thesis, we also present a detailed analysis of the coverage and spectral efficiency of a downlink cellular network. Rather than relying on the first-order statistics of received signal-to-interference-ratio (SIR) such as coverage probability, we focus on characterizing its meta-distribution. As a result, our new design framework reveals that the traditional results which advocate lowering of BS heights or even optimal selection of BS height do not yield consistent service experience across users. Finally, for drone-assisted IoT sensor networks, we develop a comprehensive framework to characterize the performance of a drone-assisted backscatter communication-based IoT sensor network. A statistical framework is developed to quantify the coverage probability that explicitly accommodates a dyadic backscatter channel which experiences deeper fades than that of the one-way Rayleigh channel. We practically implement the proposed system using software defined radio (SDR) and a custom-designed sensor node (SN) tag. The measurements of parameters such as noise figure, tag reflection coefficient etc., are used to parametrize the developed framework

Foam evolution inspired modeling for staged construction of ultra-dense small cell networks

Small cells (SCs) are expected to be ultra-densely deployed in or close to the traffic hot-spots in the fifth generation (5G) mobile networks to provide wireless capacity cost-effectively. Traffic hot-spots change over time, which means SCs cannot be deployed in a one-off manner as macrocells normally do, rather they should be constructed in a staged process. Hence, mathematical models that capture the time-varying staged-construction process, are urgently needed for operators to effectively predict the construction period, but are currently lacking. In this paper, inspired by the foam bursting process-a natural phenomenon that can be observed in daily life such as hand-washing, we first propose a novel model that can predict the time-varying expectation and logarithmic variance of SC coverage areas. Then, we verify the model by real network deployment cases. Additionally, in order to extract parameters from historical base station deployment data, a parameter estimation algorithm is designed and verified. The findings of the paper reveal that mobile operators should construct ultra-dense SC networks in a staged manner like how larger foams split into smaller ones

A Distributed SON-Based User-Centric Backhaul Provisioning Scheme

5G definition and standardization projects are well underway, and governing characteristics and major challenges have been identified. A critical network element impacting the potential performance of 5G networks is the backhaul, which is expected to expand in length and breadth to cater to the exponential growth of small cells while offering high throughput in the order of gigabit per second and less than 1 ms latency with high resilience and energy efficiency. Such performance may only be possible with direct optical fiber connections that are often not available country-wide and are cumbersome and expensive to deploy. On the other hand, a prime 5G characteristic is diversity, which describes the radio access network, the backhaul, and also the types of user applications and devices. Thus, we propose a novel, distributed, self-optimized, end-to-end user-cell-backhaul association scheme that intelligently associates users with candidate cells based on corresponding dynamic radio and backhaul conditions while abiding by users' requirements. Radio cells broadcast multiple bias factors, each reflecting a dynamic performance indicator (DPI) of the end-to-end network performance such as capacity, latency, resilience, energy consumption, and so on. A given user would employ these factors to derive a user-centric cell ranking that motivates it to select the cell with radio and backhaul performance that conforms to the user requirements. Reinforcement learning is used at the radio cells to optimise the bias factors for each DPI in a way that maximise the system throughput while minimising the gap between the users' achievable and required end-to-end quality of experience (QoE). Preliminary results show considerable improvement in users' QoE and cumulative system throughput when compared with the state-of-the-art user-cell association schemes

Contribution to the optimization of 4G mobile communications by means of advanced carrier aggregation strategies

Mobile broadband subscriptions and data traffic have increasingly grown in the past years with the deployment of the 3G and 4G technologies and the massive use of mobile devices. In this sense, LTE-A has been presented as the next step in wireless communications where higher data rates are targeted and fully packet switched services are held. The ultimate goal of 4G and the forthcoming 5G technology is to increase the Quality of Experience (QoE) of users. In this context, several challenges open up to face the increased bandwidth demands in both uplink (UL) and downlink (DL). To this end, LTE-A has proposed the use of Carrier Aggregation (CA) which allows the simultaneous data transmission in separate fragments of spectrum. The improvements brought by CA in the DL can be almost straightforward appreciable, since the evolved Node B (eNB) is in charge of transmissions, and power availability is not typically an issue. Conversely, the UL presents many open challenges to introduce aggregated transmissions, since it relies on the user terminal for transmission procedures. Lower transmission power and increased interference variability turn the UL more complex than the DL. For this reason, this Ph.D. thesis provides a contribution to the field of CA for UL mobile systems. The novelties here presented address the main limitations the UL encounters when introducing CA; new methods and strategies are proposed with the final aim of enhancing the UL communications with the use of increased bandwidth transmissions, and reducing the unbalanced data rate between the UL and DL. Throughout an exhaustive literature review, the main research opportunities to successfully implement CA in the UL were identified. In particular, three main blocks can be recognized. First, the need for introducing intelligent Radio Resource Management procedures that provide the user with increased QoE, specially in the cell edge, where users are more likely to be power limited, and CA is typically discarded. Consequently, the first part of this dissertation places emphasis on topics related to scheduling and the power limitations to face the increased bandwidth. In this sense, mechanisms that tackle the throughput improvement are proposed and scheduling schemes that specifically assess the gain or deterioration of CA are designed. Indeed, these strategies strongly rely on an accurate Channel State Information (CSI); it is of utmost importance to possess precise CSI to effectively support these assessments. In this line, the second part deals with the imperfect CSI where the efficient use of reference signals provides a high value. Channel prediction techniques have been proposed with the use of the splines method. However, the increased variability of interferences and the high delay in measurements still impairs the CSI accuracy. In this manner, interference management methods are introduced to support the CSI acquisition process. Finally, since CA constitutes the most transverse topic of the new features added to the 4G standard, the last block of research focuses on the opportunities that emerge with the use of CA in the context of heterogeneous networks, and new system designs are addressed. It is proposed to use dual connectivity in the form of decoupled uplink and downlink connections in a CA context, where aggregated carriers may have different coverage footprints. An analysis of two different cell association cases that arise has been driven. Stochastic geometry is used to study the system analytically, propagation conditions in the different tiers and frequencies are considered and the different association cases are compared to a classical downlink received power association rule. Conclusions show that decoupling the uplink provides the system with outstanding gains, however, being connected to the cell that receives the highest received power may not always be profitable, since issues like interferences or load conditions shall be also considered.El número de usuarios móviles y el tráfico de datos generado han aumentado en los últimos años con el despliegue de redes 3G y 4G y el uso masivo de dispositivos móviles. De este modo, LTE-A surge como el siguiente escalón de las comunicaciones móviles, dónde se apunta a mayores velocidades de transmisión y los servicios se basan en la conmutación de paquetes. El objetivo principal de las redes 4G y de la inminente red 5G es mejorar la experiencia del usuario. En este contexto, se presentan nuevos retos para hacer frente a las demandas de incrementar el ancho de banda en ambos enlaces: ascendente (UL) y descendente (DL). Por ello, LTE-A propone el uso de portadoras agregadas (Carrier Aggregation (CA)), tecnología que permite la transmisión simultánea en dos fragmentos del espectro. Las mejoras que aporta CA en el DL son casi inmediatas dado que las transmisiones corren a cargo de la base, la cual no sufre la falta de potencia. Al contrario, el UL presenta más retos para introducir CA, ya que es el terminal quién se encarga de la transmisión. La baja disponibilidad de potencia y la alta variabilidad de la interferencia lo convierten en un entorno mucho más complejo. Por ello, esta disertación presenta una contribución al campo de CA en el UL de comunicaciones móviles. Las novedades presentadas tratan las principales limitaciones para incorporar CA; se proponen nuevos métodos y estrategias con el objetivo de mejorar las comunicaciones en el UL mediante el uso de CA; todo ello, para reducir el desajuste que existe entre la velocidad de transmisión del UL y DL. Mediante una extensa revisión de la literatura, se han detectado las principales líneas de investigación y potenciales mejoras para incorporar CA exitosamente. Se han identificado tres grandes bloques de investigación. Primero, la necesidad de introducir estrategias de gestión de recursos inteligentes, que proporcionen al usuario una mejora de la experiencia, especialmente en el límite de la celda. Es allí donde los usuarios tienen una mayor probabilidad de estar limitados en potencia, razón por la que se les aparta de CA. Consecuentemente, la primera parte de esta tesis pone énfasis en la asignación de recursos y las limitaciones en potencia por parte del usuario para hacer frente a un incremento del ancho de banda. Se proponen mecanismos que mejoran la velocidad de transmisión evaluando las ganancias o pérdidas de incorporar CA a la transmisión. Para apoyar el funcionamiento de estas estrategias de asignación, y asegurar su máximo rendimiento, es necesario un método que proporcione un conocimiento preciso y fidedigno del estado del canal (Channel State Information (CSI)). De este modo, la segunda parte de la investigación lidia con el CSI, donde el uso eficiente de las señales de referencia es de gran importancia. Se proponen técnicas de predicción de señal mediante el uso de Splines; sin embargo, la alta variabilidad de las interferencias y el gran retardo entre dos muestras de CSI perjudican la precisión. Por ello, se introducen métodos de gestión de interferencias que apoyan el proceso de adquisición del CSI. Finalmente, dado que CA es una de las funciones más transversales de las introducidas por el estándar 4G, la última parte de investigación se centra en las oportunidades que surgen con su uso en las redes heterogéneas. Se propone el uso de la conectividad dual, desacoplando el UL del DL junto con CA, donde el área de cobertura de las portadoras puede ser diferente. Se analizan dos escenarios de asociación posibles. Con el uso de geometría estocástica se estudia analíticamente el sistema, considerando diferentes condiciones de propagación en los distintos tipos de celda y frecuencias; los escenarios de asociación se comparan a uno tradicional, en el cual los usuarios se asocian en función de la potencia recibida de las bases. Las conclusiones destacan que el desacoplo aporta mejoras en el UL. Sin embargo, temas como interferencias o carga deben también considera