Self-organising network management for heterogeneous LTE-advanced networks

This thesis was submitted for the award of Doctor of Philosophy and awarded by Brunel University LondonSince 2004, when the Long Term Evolution (LTE) was first proposed to be publicly available in the year 2009, a plethora of new characteristics, techniques and applications have been constantly enhancing it since its first release, over the past decade. As a result, the research aims for LTE-Advanced (LTE-A) have been released to create a ubiquitous and supportive network for mobile users. The incorporation of heterogeneous networks (HetNets) has been proposed as one of the main enhancements of LTE-A systems over the existing LTE releases, by proposing the deployment of small-cell applications, such as femtocells, to provide more coverage and quality of service (QoS) within the network, whilst also reducing capital expenditure. These principal advantages can be obtained at the cost of new challenges such as inter-cell interference, which occurs when different network applications share the same frequency channel in the network. In this thesis, the main challenges of HetNets in LTE-A platform have been addressed and novel solutions are proposed by using self-organising network (SON) management approaches, which allows the cooperative cellular systems to observe, decide and amend their ongoing operation based on network conditions. The novel SON algorithms are modelled and simulated in OPNET modeler simulation software for the three processes of resource allocation, mobility management and interference coordination in multi-tier macro-femto networks. Different channel allocation methods based on cooperative transmission, frequency reuse and dynamic spectrum access are investigated and a novel SON sub-channel allocation method is proposed based on hybrid fractional frequency reuse (HFFR) scheme to provide dynamic resource allocation between macrocells and femtocells, while avoiding co-tier and cross-tier interference. Mobility management is also addressed as another important issue in HetNets, especially in hand-ins from macrocell to femtocell base stations. The existing research considers a limited number of methods for handover optimisation, such as signal strength and call admission control (CAC) to avoid unnecessary handovers, while our novel SON handover management method implements a comprehensive algorithm that performs sensing process, as well as resource availability and user residence checks to initiate the handover process at the optimal time. In addition to this, the novel femto over macro priority (FoMP) check in this process also gives the femtocell target nodes priority over the congested macrocells in order to improve the QoS at both the network tiers. Inter-cell interference, as the key challenge of HetNets, is also investigated by research on the existing time-domain, frequency-domain and power control methods. A novel SON interference mitigation algorithm is proposed, which is based on enhanced inter-cell interference coordination (eICIC) with power control process. The 3-phase power control algorithm contains signal to interference plus noise ratio (SINR) measurements, channel quality indicator (CQI) mapping and transmission power amendments to avoid the occurrence of interference due to the effects of high transmission power. The results of this research confirm that if heterogeneous systems are backed-up with SON management strategies, not only can improve the network capacity and QoS, but also the new network challenges such as inter-cell interference can also be mitigated in new releases of LTE-A network

Load balancing using cell range expansion in LTE advanced heterogeneous networks

The use of heterogeneous networks is on the increase, fueled by consumer demand for more data. The main objective of heterogeneous networks is to increase capacity. They offer solutions for efficient use of spectrum, load balancing and improvement of cell edge coverage amongst others. However, these solutions have inherent challenges such as inter-cell interference and poor mobility management. In heterogeneous networks there is transmit power disparity between macro cell and pico cell tiers, which causes load imbalance between the tiers. Due to the conventional user-cell association strategy, whereby users associate to a base station with the strongest received signal strength, few users associate to small cells compared to macro cells. To counter the effects of transmit power disparity, cell range expansion is used instead of the conventional strategy. The focus of our work is on load balancing using cell range expansion (CRE) and network utility optimization techniques to ensure fair sharing of load in a macro and pico cell LTE Advanced heterogeneous network. The aim is to investigate how to use an adaptive cell range expansion bias to optimize Pico cell coverage for load balancing. Reviewed literature points out several approaches to solve the load balancing problem in heterogeneous networks, which include, cell range expansion and utility function optimization. Then, we use cell range expansion, and logarithmic utility functions to design a load balancing algorithm. In the algorithm, user and base station associations are optimized by adapting CRE bias to pico base station load status. A price update mechanism based on a suboptimal solution of a network utility optimization problem is used to adapt the CRE bias. The price is derived from the load status of each pico base station. The performance of the algorithm was evaluated by means of an LTE MATLAB toolbox. Simulations were conducted according to 3GPP and ITU guidelines for modelling heterogeneous networks and propagation environment respectively. Compared to a static CRE configuration, the algorithm achieved more fairness in load distribution. Further, it achieved a better trade-off between cell edge and cell centre user throughputs. [Please note: this thesis file has been deferred until December 2016

On Improving Performance of Victim Macrocell Users in LTE HetNets with Closed Access Femtocells

Todays wireless and cellular networks demand a minimum data rate requirements for its users, as the users have apparently become dependent on mobile networks with the advent smartphones, tablets, and other wireless gadgets. These high expectations from users have given rise in traf- c demand. Cellular operators are also looking for solutions to eradicate the network issues like call drops, choppy videos, and slow downloads. All of these trends will continue and have fuelled the interest of researchers in wireless and cellular networks. In order to attain the high data de- mand from users, operators are deploying new solutions in a coverage prone and highly populated cell areas. 3rd Generation Partnership Project (3GPP) introduced Heterogeneous networks (Het- Nets) in LTE-Advanced (Long Term Evolution - Advanced) for improving the experience of mobile users. The HetNets launched new network topologies, which are cost-e ective and also improves the data rate of mobile users. However, dense deployment of these new network nodes can also bring a lot of challenges i.e., interference control and management of new network nodes. Hence, 3GPP speci ed various interference mitigation technologies, which includes ICIC (Intercell inter- ference coordination), Enhanced Intercell interference coordination (eICIC), and Further Enhanced Intercell interference coordination (feICIC). In this thesis, we focus on the cross-tier interference between Macrocell and Femtocell, and the performance enhancement of Victim Macrocell users. We also proposed a centralized algorithm, which provides coordination between interfering Femtocell (Closed Access Mode) and Macrocell, and o er a joint Almost Blank Subframe (ABSF) and power control scheme for Femtocell muting. The two prime metric discussed in our thesis are; a) attuning the transmission power during ABSF for Femtocell and then calculating the number of ABSF re- quired, and b) determining appropriate subframes for muting an arbitrary Femtocell. Centralized algorithm tracks the state of Macrocell users. A Macrocell user is referred as Victim Macrocell user if the signal-to-interference-plus-noise ratio (SINR) value of Macrocell user degrades from the required threshold value. In this work, we performed only Femtocell muting to show the e ect of dense deployment of Femtocells on Macrocell users. During ABSF muting Femtocell automatically adjusts its transmission power depending upon the level of interference su ered by Victim Macrocell users, which also minimizes the unnecessary degradation in Femtocell users performance. In order to increase the favorable chances of scheduling Victim Macrocell users during ABSF by its serving Macrocell, the centralized algorithm mutes Femtocells in a round robin fashion and eradicates un- necessary Femtocell muting. Our proposed scheme, RrMute compared with various other schemes and the simulation results show that RrMute enhances the performance of Victim Macrocell users, while simultaneously not jeopardizing the performance of Femtocell users

Algoritmos de aprendizado de máquina para coordenação de interferência entre células

The current LTE and LTE-A deployments require larger efforts to achieve the radio resource management. This, due to the increase of users and the constantly growing demand of services. For this reason, the automatic optimization is a key point to avoid issues such as the inter-cell interference. This paper presents several proposals of machine-learning algorithms focused on this automatic optimization problem. The research works seek that the cellular systems achieve their self-optimization, a key concept within the self-organized networks, where the main objective is to achieve that the networks to be capable to automatically respond to the particular needs in the dynamic network traffic scenarios.Los despliegues actuales de LTE y LTE-A requieren mayor esfuerzo para la gestión de recursos radio debido al incremento de usuarios y a la gran demanda de servicios; en ese escenario, la optimización automática es un punto clave para evitar problemas como la interferencia inter-celda. El presente trabajo recopila propuestas de algoritmos de aprendizaje automático [machine learning] enfocados en resolver este problema. Las investigaciones buscan que los sistemas celulares consigan su auto-optimización, un concepto que se enmarca dentro del área de redes auto-organizadas [Self-Organized Networks, SON], cuyo objetivo es lograr que las redes respondan de forma automática a las necesidades de los escenarios dinámicos de tráfico de red.As implantações atuais de LTE e LTE-A exigem maior esforço para o gerenciamento de recursos rádio devido ao aumento de usuários e à alta demanda por serviços, neste cenário a otimização automática é um ponto-chave para evitar problemas como a interferência entre células. O presente trabalho coleta propostas de algoritmos de aprendizado automáticos focados na resolução deste problema. A pesquisa busca que os sistemas celulares alcancem a sua auto-otimização, um conceito que faz parte das redes auto-organizadas (Self-Organizing Networks, SON), cujo objetivo é garantir que as redes respondam automaticamente às necessidades dos cenários dinâmicos do tráfego de rede

Towards UAV Assisted 5G Public Safety Network

Ensuring ubiquitous mission-critical public safety communications (PSC) to all the first responders in the public safety network is crucial at an emergency site. The first responders heavily rely on mission-critical PSC to save lives, property, and national infrastructure during a natural or human-made emergency. The recent advancements in LTE/LTE-Advanced/5G mobile technologies supported by unmanned aerial vehicles (UAV) have great potential to revolutionize PSC. However, limited spectrum allocation for LTE-based PSC demands improved channel capacity and spectral efficiency. An additional challenge in designing an LTE-based PSC network is achieving at least 95% coverage of the geographical area and human population with broadband rates. The coverage requirement and efficient spectrum use in the PSC network can be realized through the dense deployment of small cells (both terrestrial and aerial). However, there are several challenges with the dense deployment of small cells in an air-ground heterogeneous network (AG-HetNet). The main challenges which are addressed in this research work are integrating UAVs as both aerial user and aerial base-stations, mitigating inter-cell interference, capacity and coverage enhancements, and optimizing deployment locations of aerial base-stations. First, LTE signals were investigated using NS-3 simulation and software-defined radio experiment to gain knowledge on the quality of service experienced by the user equipment (UE). Using this understanding, a two-tier LTE-Advanced AG-HetNet with macro base-stations and unmanned aerial base-stations (UABS) is designed, while considering time-domain inter-cell interference coordination techniques. We maximize the capacity of this AG-HetNet in case of a damaged PSC infrastructure by jointly optimizing the inter-cell interference parameters and UABS locations using a meta-heuristic genetic algorithm (GA) and the brute-force technique. Finally, considering the latest specifications in 3GPP, a more realistic three-tier LTE-Advanced AG-HetNet is proposed with macro base-stations, pico base-stations, and ground UEs as terrestrial nodes and UABS and aerial UEs as aerial nodes. Using meta-heuristic techniques such as GA and elitist harmony search algorithm based on the GA, the critical network elements such as energy efficiency, inter-cell interference parameters, and UABS locations are all jointly optimized to maximize the capacity and coverage of the AG-HetNet

Performance enhancement for LTE and beyond systems

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyWireless communication systems have undergone fast development in recent years. Based on GSM/EDGE and UMTS/HSPA, the 3rd Generation Partnership Project (3GPP) specified the Long Term Evolution (LTE) standard to cope with rapidly increasing demands, including capacity, coverage, and data rate. To achieve this goal, several key techniques have been adopted by LTE, such as Multiple-Input and Multiple-Output (MIMO), Orthogonal Frequency-Division Multiplexing (OFDM), and heterogeneous network (HetNet). However, there are some inherent drawbacks regarding these techniques. Direct conversion architecture is adopted to provide a simple, low cost transmitter solution. The problem of I/Q imbalance arises due to the imperfection of circuit components; the orthogonality of OFDM is vulnerable to carrier frequency offset (CFO) and sampling frequency offset (SFO). The doubly selective channel can also severely deteriorate the receiver performance. In addition, the deployment of Heterogeneous Network (HetNet), which permits the co-existence of macro and pico cells, incurs inter-cell interference for cell edge users. The impact of these factors then results in significant degradation in relation to system performance. This dissertation aims to investigate the key techniques which can be used to mitigate the above problems. First, I/Q imbalance for the wideband transmitter is studied and a self-IQ-demodulation based compensation scheme for frequencydependent (FD) I/Q imbalance is proposed. This combats the FD I/Q imbalance by using the internal diode of the transmitter and a specially designed test signal without any external calibration instruments or internal low-IF feedback path. The instrument test results show that the proposed scheme can enhance signal quality by 10 dB in terms of image rejection ratio (IRR). In addition to the I/Q imbalance, the system suffers from CFO, SFO and frequency-time selective channel. To mitigate this, a hybrid optimum OFDM receiver with decision feedback equalizer (DFE) to cope with the CFO, SFO and doubly selective channel. The algorithm firstly estimates the CFO and channel frequency response (CFR) in the coarse estimation, with the help of hybrid classical timing and frequency synchronization algorithms. Afterwards, a pilot-aided polynomial interpolation channel estimation, combined with a low complexity DFE scheme, based on minimum mean squared error (MMSE) criteria, is developed to alleviate the impact of the residual SFO, CFO, and Doppler effect. A subspace-based signal-to-noise ratio (SNR) estimation algorithm is proposed to estimate the SNR in the doubly selective channel. This provides prior knowledge for MMSE-DFE and automatic modulation and coding (AMC). Simulation results show that this proposed estimation algorithm significantly improves the system performance. In order to speed up algorithm verification process, an FPGA based co-simulation is developed. Inter-cell interference caused by the co-existence of macro and pico cells has a big impact on system performance. Although an almost blank subframe (ABS) is proposed to mitigate this problem, the residual control signal in the ABS still inevitably causes interference. Hence, a cell-specific reference signal (CRS) interference cancellation algorithm, utilizing the information in the ABS, is proposed. First, the timing and carrier frequency offset of the interference signal is compensated by utilizing the cross-correlation properties of the synchronization signal. Afterwards, the reference signal is generated locally and channel response is estimated by making use of channel statistics. Then, the interference signal is reconstructed based on the previous estimate of the channel, timing and carrier frequency offset. The interference is mitigated by subtracting the estimation of the interference signal and LLR puncturing. The block error rate (BLER) performance of the signal is notably improved by this algorithm, according to the simulation results of different channel scenarios. The proposed techniques provide low cost, low complexity solutions for LTE and beyond systems. The simulation and measurements show good overall system performance can be achieved