On the performance of multi-tier Heterogeneous networks under LoS and NLoS transmissions

Heterogeneous networks (HetNets) with a multi-tier structure have been considered as a promising method to provide high quality of service to mobile users. The dense deployment of small-cell base stations (BSs) implies short distances between BSs and users. It is therefore likely that users will see line-of-sight (LoS) links from its serving BS and even nearby interfering BSs, which has not been considered in performance analysis for multi-tier HetNets yet. In this paper, we study a dense multi-tier HetNet with LoS and non-line-of-sight (NLoS) transmissions based on a multislope path loss model. The spatial locations of BSs of any given network tier and those of mobile users are modeled as independent spatial Poisson point processes (SPPPs). We derive the expression of downlink coverage probability for the multi-tier HetNet, based on which we calculate the area spectral efficiency (ASE) and energy efficiency (EE) of the HetNet. Our analytical results demonstrate that in an extremely dense HetNet, both the ASE and EE of the HetNet will drop quickly with further increase of the small-cell density due to the dominance of LoS interfering small-cell links

On the performance of multi-tier Heterogeneous networks under LoS and NLoS transmissions

Heterogeneous networks (HetNets) with a multi-tier structure have been considered as a promising method to provide high quality of service to mobile users. The dense deployment of small-cell base stations (BSs) implies short distances between BSs and users. It is therefore likely that users will see line-of-sight (LoS) links from its serving BS and even nearby interfering BSs, which has not been considered in performance analysis for multi-tier HetNets yet. In this paper, we study a dense multi-tier HetNet with LoS and non-line-of-sight (NLoS) transmissions based on a multislope path loss model. The spatial locations of BSs of any given network tier and those of mobile users are modeled as independent spatial Poisson point processes (SPPPs). We derive the expression of downlink coverage probability for the multi-tier HetNet, based on which we calculate the area spectral efficiency (ASE) and energy efficiency (EE) of the HetNet. Our analytical results demonstrate that in an extremely dense HetNet, both the ASE and EE of the HetNet will drop quickly with further increase of the small-cell density due to the dominance of LoS interfering small-cell links

ENERGY-EFFICIENT DESIGN OF HETEROGENEOUS CELLULAR NETWORKS USING STOCHASTIC GEOMETRY

Ph.DDOCTOR OF PHILOSOPH

Heterogeneous Cellular Networks Mixed with LoS and NLoS Transmissions

In the last decades, the rapid increase of user traffc demand for better user experience has pushed the traditional macrocell-only networks being evolving to modern heterogeneous networks(HetNets) with a multi-tier structure. The dense deployment of small-cell base stations (BSs) implies short distances between BSs and users. It is therefore likely that users will see line-of-sight (LoS) links from its serving BS and even nearby interfering BSs, which has not been considered in performance analysis for multi-tier HetNets yet. In this thesis, the dense multi-tier HetNet with LoS and non-line-of-sight (NLoS) transmissions based on a multi-slope path loss model is analyzed. The spatial locations of BSs of any given network tier and those of mobile users are modeled as independent spatial Poisson point processes (PPPs). The expressions of downlink coverage probability are divided for a multi-tier HetNet, based on that the calculations of the area spectral effciency (ASE) and energy effciency (EE) are further proposed. The results demonstrate that in an extremely dense HetNet, both the ASE and EE of the HetNet will drop quickly with further increase of the small-cell density due to the dominance of LoS interfering small-cell links. Following that, the investigation is moved to the probabilistic events of LoS and NLoS transmissions. Four transmission scenarios are simulated with different path loss models, including a linear LoS probability function, a suburban area, a millimetre wave transmission and a 3D path loss model. Accordingly, a user-centric BS clustering strategy is proposed for a non-coherent joint transmissions (JTs) in dense small-cell networks, based on the idea of grouping the BSs with their LoS probabilities to such user above a predefined threshold. The proposed BS clustering strategy is evaluated in the above four transmission environments. Our simulation results show that the coverage probability and spectrum effciency (SE) achieved by the proposed user-centric BS clustering strategy achieve a rapid growth rate with the increasing BS density, and even at extremely high BS densities in all four considered environments. Lastly, following the proposed BS clustering strategy above, a further developed clustering strategy called multi-BS multi-user-equipment (UE) clustering is proposed to allow multiple BSs to serve multiple UEs simultaneously. The main idea of this clustering strategy is to boost network performance in terms of coverage probability and SE at high BS density without sacrificing the ASE. Utilizing stochastic geometry, the closed form expressions of the network performance in terms of coverage probability, SE, ASE and EE are derived in a downlink small-cell network. The results show that the proposed clustering strategy achieves high coverage probability and linear increasing SE and ASE in ultra dense networks at same time

Interference Coordination in Heterogeneous Networks: Stochastic Geometry Based Modelling and Performance Analysis

Recently data traffic has experienced explosive increase with the proliferation of wireless devices and the popularity of media-based free services. The academic and industry of mobile communications have predicted an estimated $1000$x increase in traffic volume for the forthcoming 5G networks. This traffic explosion stimulates the deployment of heterogeneous networks (HetNets) with small cells (SCs) underlying in the traditional macrocells, which has been considered as a promising technique to contribute to the $1000$x traffic capacity gain. Initially, licensed spectrum bands are expected to be used in SCs, thus the SC deployment introduces the cross-tier interference between SCs and macrocells, which degrades the downlink signal to interference plus noise ratio (SINR) of user equipments (UEs) severely, especially for the edge UEs in a ultra-densely deployed scenario. To alleviate this cross-tier interference between SCs and macrocells, unlicensed spectrum bands are advocated to be used in SCs. Specifically, with the aid of carrier aggregation, the $5$ gigahertz (GHz) unlicensed band has become an option for SCs in the Long Term Evolution (LTE)-Unlicensed (LTE-U) scheme, but the $5$ Ghz unlicensed band has already been used by WiFi networks. Thus downlink cross-tier interference also occurs between LTE-U and WiFi networks. Accordingly, downlink cross-tier interference is inevitable no matter licensed or unlicensed spectrum band (i.e., 5 GHz) is used in SCs, and interference coordination schemes, such as further enhanced inter-cell interference coordination (FeICIC) for macrocells and SCs, and Licensed Assisted Access (LAA) for WiFi networks and LTE-U networks, have been proposed to mitigate these cross-tier interferences. In this dissertation, we mainly focus on the modelling and performance analysis of HetNets with the aforementioned two interference coordination schemes (i.e., FeICIC and LTE-LAA) under the stochastic geometry framework. Firstly, as the configuration of reduced power subframe (RPS)-related parameters was not well investigated in a two-tier HetNet adopting RPSs and cell range expansion (CRE), we derive the analytical expressions of the downlink coverage probability and rate coverage probability in such a HetNet. The optimal settings for the area of macrocell center regions, the area of SC range expansion regions, and the transmit power of RPSs for maximizing the rate coverage probability are analysed. As compared with the rate coverage probability in the two-tier HetNet with almost blank subframes (ABSs), which is proposed in the previous version of FeICIC, i.e., the enhanced inter-cell interference coordination (eICIC), the results show that ABSs outperform RPSs in terms of the rate coverage probability in the two-tier HetNet with the optimal range expansion bias, but lead to a heavier burden on the SC backhaul. However, with static typical range expansion biases, RPSs provide better rate coverage probability than ABSs in the two-tier HetNet. Secondly, the conventional FeICIC scheme ignores the potential of RPSs being adopted in both tiers of a two-tier HetNet without CRE, which is envisioned to improve the SINR level of edge UEs in both tiers. Accordingly, we study the downlink coverage probability and rate coverage probability of a two-tier HetNet applying with our proposed scheme. The results reveal that adopting RPSs in both tiers not only improves the coverage probabilities of edge UEs, but also increases the rate coverage probability of the whole two-tier HetNet. Thirdly, in both previous works, strict subframe alignment (SA) was assumed throughout the whole network, which is difficult to maintain between neighbouring cells in reality. Consequently, we propose a novel subframe misalignment (SM) model for a two-tier HetNet adopting RPSs with SM offsets restricted within a subframe duration, and analyse the coverage probability under the effects of RPSs and SM. The numerical results indicate that the strict SA requirement can be relaxed by up to $20\%$ of the subframe duration with a loss of below $5\%$ in terms of the downlink coverage probability. Lastly, since stochastic-geometry-based analysis of the coexisting LTE-LAA and WiFi networks, which adopt the carrier-sense multiple access with collision avoidance (CSMA/CA) as the medium access control (MAC) scheme and share multiple unlicensed channels (UCs), was missing, we analyse the downlink throughput and spectral efficiency (SE) of the coexisting LTE-LAA and WiFi networks versus the network density and the number of UCs based on the Matern hard core process. The throughput and SE are obtained as functions of the downlink successful transmission probability (STP), of which analytical expressions are derived for both LTE-LAA and WiFi UEs. The results show that the throughput and SE of the whole coexisting LTE-LAA and WiFi networks can be improved significantly with an increasing number of accessible UCs. Based on the numerical results, insights into the trade-off between the throughput and SE against the number of accessible UCs are provided. All the derived results have been validated by Monte Carlo simulation in Matlab, and the conclusions observed from the results can provide guidelines for the future deployments of the FeICIC and LTE-LAA interference coordination schemes in HetNets

Stochastic Geometry Based Analysis of Capacity, Mobility and Energy Efficiency for Dense Heterogeneous Networks

In recent years, the increase in the population of mobile users and the advances in computational capabilities of mobile devices have led to an exponentially increasing traffic load on the wireless networks. This trend is foreseen to continue in the future due to the emerging applications such as cellular Internet of things (IoT) and machine type communications (MTC). Since the spectrum resources are limited, the only promising way to keep pace with the future demand is through aggressive spatial reuse of the available spectrum which can be realized in the networks through dense deployment of small cells. There are many challenges associated with such densely deployed heterogeneous networks (HetNets). The main challenges which are considered in this research work are capacity enhancement, velocity estimation of mobile users, and energy efficiency enhancement. We consider different approaches for capacity enhancement of the network. In the first approach, using stochastic geometry we theoretically analyze time domain inter-cell interference coordination techniques in a two-tier HetNet and optimize the parameters to maximize the capacity of the network. In the second approach, we consider optimization of the locations of aerial bases stations carried by the unmanned aerial vehicles (UAVs) to enhance the capacity of the network for public safety and emergency communications, in case of damaged network infrastructure. In the third approach, we introduce a subsidization scheme for the service providers through which the network capacity can be improved by using regulatory power of the government. Finally, we consider the approach of device-to-device communications and multi-hop transmissions for enhancing the capacity of a network. Velocity estimation of high speed mobile users is important for effective mobility management in densely deployed small cell networks. In this research, we introduce two novel methods for the velocity estimation of mobile users: handover-count based velocity estimation, and sojourn time based velocity estimation. Using the tools from stochastic geometry and estimation theory, we theoretically analyze the accuracy of the two velocity estimation methods through Cramer-Rao lower bounds (CRLBs). With the dense deployment of small cells, energy efficiency becomes crucial for the sustained operation of wireless networks. In this research, we jointly study the energy efficiency and the spectral efficiency in a two-tier HetNet. We optimize the parameters of inter-cell interference coordination technique and study the trade-offs between the energy efficiency and spectral efficiency of the HetNet

NOVEL USER-CENTRIC ARCHITECTURES FOR FUTURE GENERATION CELLULAR NETWORKS: DESIGN, ANALYSIS AND PERFORMANCE OPTIMIZATION

Ambitious targets for aggregate throughput, energy efficiency (EE) and ubiquitous user experience are propelling the advent of ultra-dense networks. Inter-cell interference and high energy consumption in an ultra-dense network are the prime hindering factors in pursuit of these goals. To address this challenge, we investigate the idea of transforming network design from being base station-centric to user-centric. To this end, we develop mathematical framework and analyze multiple variants of the user-centric networks, with the help of advanced scientific tools such as stochastic geometry, game theory, optimization theory and deep neural networks. We first present a user-centric radio access network (RAN) design and then propose novel base station association mechanisms by forming virtual dedicated cells around users scheduled for downlink. The design question that arises is what should the ideal size of the dedicated regions around scheduled users be? To answer this question, we follow a stochastic geometry based approach to quantify the area spectral efficiency (ASE) and energy efficiency (EE) of a user-centric Cloud RAN architecture. Observing that the two efficiency metrics have conflicting optimal user-centric cell sizes, we propose a game theoretic self-organizing network (GT-SON) framework that can orchestrate the network between ASE and EE focused operational modes in real-time in response to changes in network conditions and the operator's revenue model, to achieve a Pareto optimal solution. The designed model is shown to outperform base-station centric design in terms of both ASE and EE in dense deployment scenarios. Taking this user-centric approach as a baseline, we improve the ASE and EE performance by introducing flexibility in the dimensions of the user-centric regions as a function of data requirement for each device. So instead of optimizing the network-wide ASE or EE, each user device competes for a user-centric region based on its data requirements. This competition is modeled via an evolutionary game and a Vickrey-Clarke-Groves auction. The data requirement based flexibility in the user-centric RAN architecture not only improves the ASE and EE, but also reduces the scheduling wait time per user. Offloading dense user hotspots to low range mmWave cells promises to meet the enhance mobile broadband requirement of 5G and beyond. To investigate how the three key enablers; i.e. user-centric virtual cell design, ultra-dense deployments and mmWave communication; are integrated in a multi-tier Stienen geometry based user-centric architecture. Taking into account the characteristics of mmWave propagation channel such as blockage and fading, we develop a statistical framework for deriving the coverage probability of an arbitrary user equipment scheduled within the proposed architecture. A key advantage observed through this architecture is significant reduction in the scheduling latency as compared to the baseline user-centric model. Furthermore, the interplay between certain system design parameters was found to orchestrate the ASE-EE tradeoff within the proposed network design. We extend this work by framing a stochastic optimization problem over the design parameters for a Pareto optimal ASE-EE tradeoff with random placements of mobile users, macro base stations and mmWave cells within the network. To solve this optimization problem, we follow a deep learning approach to estimate optimal design parameters in real-time complexity. Our results show that if the deep learning model is trained with sufficient data and tuned appropriately, it yields near-optimal performance while eliminating the issue of long processing times needed for system-wide optimization. The contributions of this dissertation have the potential to cause a paradigm shift from the reactive cell-centric network design to an agile user-centric design that enables real-time optimization capabilities, ubiquitous user experience, higher system capacity and improved network-wide energy efficiency