Mobility management in multi-RAT multiI-band heterogeneous networks

Support for user mobility is the raison d'etre of mobile cellular networks. However, mounting pressure for more capacity is leading to adaption of multi-band multi-RAT ultra-dense network design, particularly with the increased use of mmWave based small cells. While such design for emerging cellular networks is expected to offer manyfold more capacity, it gives rise to a new set of challenges in user mobility management. Among others, frequent handovers (HO) and thus higher impact of poor mobility management on quality of user experience (QoE) as well as link capacity, lack of an intelligent solution to manage dual connectivity (of user with both 4G and 5G cells) activation/deactivation, and mmWave cell discovery are the most critical challenges. In this dissertation, I propose and evaluate a set of solutions to address the aforementioned challenges. The beginning outcome of our investigations into the aforementioned problems is the first ever taxonomy of mobility related 3GPP defined network parameters and Key Performance Indicators (KPIs) followed by a tutorial on 3GPP-based 5G mobility management procedures. The first major contribution of the thesis here is a novel framework to characterize the relationship between the 28 critical mobility-related network parameters and 8 most vital KPIs. A critical hurdle in addressing all mobility related challenges in emerging networks is the complexity of modeling realistic mobility and HO process. Mathematical models are not suitable here as they cannot capture the dynamics as well as the myriad parameters and KPIs involved. Existing simulators also mostly either omit or overly abstract the HO and user mobility, chiefly because the problems caused by poor HO management had relatively less impact on overall performance in legacy networks as they were not multi-RAT multi-band and therefore incurred much smaller number of HOs compared to emerging networks. The second key contribution of this dissertation is development of a first of its kind system level simulator, called SyntheticNET that can help the research community in overcoming the hurdle of realistic mobility and HO process modeling. SyntheticNET is the very first python-based simulator that fully conforms to 3GPP Release 15 5G standard. Compared to the existing simulators, SyntheticNET includes a modular structure, flexible propagation modeling, adaptive numerology, realistic mobility patterns, and detailed HO evaluation criteria. SyntheticNET’s python-based platform allows the effective application of Artificial Intelligence (AI) to various network functionalities. Another key challenge in emerging multi-RAT technologies is the lack of an intelligent solution to manage dual connectivity with 4G as well 5G cell needed by a user to access 5G infrastructure. The 3rd contribution of this thesis is a solution to address this challenge. I present a QoE-aware E-UTRAN New Radio-Dual Connectivity (EN-DC) activation scheme where AI is leveraged to develop a model that can accurately predict radio link failure (RLF) and voice muting using the low-level measurements collected from a real network. The insights from the AI based RLF and mute prediction models are then leveraged to configure sets of 3GPP parameters to maximize EN-DC activation while keeping the QoE-affecting RLF and mute anomalies to minimum. The last contribution of this dissertation is a novel solution to address mmWave cell discovery problem. This problem stems from the highly directional nature of mmWave transmission. The proposed mmWave cell discovery scheme builds upon a joint search method where mmWave cells exploit an overlay coverage layer from macro cells sharing the UE location to the mmWave cell. The proposed scheme is made more practical by investigating and developing solutions for the data sparsity issue in model training. Ability to work with sparse data makes the proposed scheme feasible in realistic scenarios where user density is often not high enough to provide coverage reports from each bin of the coverage area. Simulation results show that the proposed scheme, efficiently activates EN-DC to a nearby mmWave 5G cell and thus substantially reduces the mmWave cell discovery failures compared to the state of the art cell discovery methods

ON ANALYTICAL MODELING OF MOBILITY SIGNALLING IN ULTRA DENSE HETNETS

Multi-band and multi-tier network densification is being considered as the most promising solution to overcome the capacity crunch problem in emerging cellular networks. To this end, small cells (SCs) are being deployed within macro cells (MC) to off-load some of the users associated with the MCs. This deployment scenario gives birth to several new problems. Amongst others, handovers (HOs), signalling overhead and mobility management are becoming increasingly critical challenges. Frequent HOs in ultra-dense SC deployments can lead to a degraded mobility performance and increase signalling overhead significantly. Recently, a new cellular architecture with control/data plane separation has been proposed to overcome these challenges. However, the state of the art analysis of the feasibility of the CDSA remains mostly qualitative. There is dire need for mathematical models to analyze the performance of various aspects of CDSA and quantify its gains, if any, compared to conventional architecture. In this dissertation, we derive several analytical models to compare HO performance in the control/data separation architecture (CDSA) and conventionally deployed networks under various scenarios and configurations. Our developed mathematical framework advances the state of the art by considering HO success, HO failure and no HO scenarios. The proposed models can be used to quantify HO signalling as a function of key cellular system design parameter such as cell density, session duration, velocity, HO duration(s) and intercell overlap coverage factor. Using the developed analytical models, we perform a comparative analysis of HO signalling generated during various HO scenarios in CDSA and conventionally deployed networks. Building on the insights drawn from this analysis, we introduce new parameters for improving the HO execution process in emerging cellular networks viz-a-viz 5G and beyond. These new parameters, when tuned optimally, can significantly reduce the HO signalling load. Closed form expressions are also derived for continuous and continual (intermittent) mobility scenarios, while considering both HO success and HO failure likelihoods. In addition, we propose an analytical model which enables more radio resource efficient network planning by quantifying HO signalling and success probabilities as function of intercell overlap coverage factor. Analysis indicates that cell density, actual HO time duration and average velocity can be used as the key metrics to optimally plan intercell overlap coverage factor in order to minimize mobility signalling load. Numerical results and analysis based on the developed overall analytical framework indicate that, compared to conventional networks, CDSA offers promising gains in terms HO performance and reduced HO signaling overhead

Enhanced Mobile Networking using Multi-connectivity and Packet Duplication in Next-Generation Cellular Networks

Modern cellular communication systems need to handle an enormous number of users and large amounts of data, including both users as well as system-oriented data. 5G is the fifth-generation mobile network and a new global wireless standard that follows 4G/LTE networks. The uptake of 5G is expected to be faster than any previous cellular generation, with high expectations of its future impact on the global economy. The next-generation 5G networks are designed to be flexible enough to adapt to modern use cases and be highly modular such that operators would have the flexibility to provide selective features based on user demand that could be implemented without investment in additional infrastructure. Thus, the underlying cellular network that is capable of delivering these expectations must be able to handle high data rates with low latency and ultra-reliability to fulfill these growing needs. Communication in the sub-6 GHz range cannot provide high throughputs due to the scarcity of spectrum in these bands. Using frequencies in FR2 or millimeter wave (mmWave) range for communication can provide large data rates and cover densely populated areas, but only over short distances as they are susceptible to blockages. This is why dense deployments of mmWave base stations are being considered to achieve very high data rates. But, such architectures lack the reliability needed to support many V2X applications, especially under mobility scenarios. As we have discussed earlier, 5G and beyond 5G networks must also account for UE\u27s mobility as they are expected to maintain their level of performance under different mobility scenarios and perform better than traditional networks. Although 5G technology has developed significantly in recent years, there still exists a critical gap in understanding how all these technologies would perform under mobility. There is a need to analyze and identify issues that arise with mobility and come up with solutions to overcome these hurdles without compromising the performance of these networks. Multi-connectivity (MC) refers to simultaneous connectivity with multiple radio access technologies or bands and potentially represents an important solution for the ongoing 5G deployments towards improving their performance. To address the network issues that come with mobility and fill that gap, this dissertation investigates the impact of multi-connectivity on next-generation networks from three distinct perspectives, 1) mobility enhancement using multi-connectivity in 5G networks, 2) improving reliability in mobility scenarios using multi-Connectivity with packet duplication, and 3) single grant multiple uplink scheme for performance improvement in mobility scenarios. The traditional macro-cell architecture of cellular networks that cover large geographical areas will struggle to deliver the dense coverage, low latency, and high bandwidth required by some 5G applications. Thus, 5G networks must utilize ultra-dense deployment of access points operating at higher mmWave frequency bands. But, for such dense networks, user mobility could be particularly challenging as it would reduce network efficiency and user-perceived service quality due to frequent handoffs. Multi-connectivity is seen as a key enabler in improving the performance of these next-generation networks. It enhances the system performance by providing multiple simultaneous links between the user equipment (UE) and the base stations (BS) for data transfer. Also, it eliminates the time needed to deal with frequent handoffs, link establishment, etc. Balancing the trade-offs among handoff rate, service delay, and achievable coverage/data rate in heterogeneous, dense, and diverse 5G cellular networks is, therefore, an open challenge. Hence, in this dissertation, we analyze how mobility impacts the performance of current Ultra-dense mmWave network (UDN) architecture in a city environment and discuss improvements for reducing the impact of mobility to meet 5G specifications using multi-connectivity. Current handover protocols, by design, suffer from interruption even if they are successful and, at the same time, carry the risk of failures during execution. The next-generation wireless networks, like 5G New Radio, introduce even stricter requirements that cannot be fulfilled with the traditional hard handover concept. Another expectation from these services is extreme reliability that will not tolerate any mobility-related failures. Thus, in this dissertation, we explore a novel technique using packet duplication and evaluate its performance under various mobility scenarios. We study how packet duplication can be used to meet the stringent reliability and latency requirements of modern cellular networks as data packets are duplicated and transmitted concurrently over two independent links. The idea is to generate multiple instances (duplicates) of a packet and transmit them simultaneously over different uncorrelated channels with the aim of reducing the packet failure probability. We also propose enhancements to the packet duplication feature to improve radio resource utilization. The wide variety of use cases in the 5G greatly differs from the use cases considered during the design of third-generation (3G) and fourth-generation (4G) long-term evolution (LTE) networks. Applications like autonomous driving, IoT applications, live video, etc., are much more uplink intensive as compared to traditional applications. However, the uplink performance is often, by design, lower than the downlink; hence, 5G must improve uplink performance. Hence, to meet the expected performance levels, there is a need to explore flexible network architectures for 5G networks. In this work, we propose a novel uplink scheme where the UE performs only a single transmission on a common channel, and every base station that can receive this signal would accept and process it. In our proposed architecture, a UE is connected to multiple mmWave capable distributed units (DUs), which are connected to a single gNB-central unit. In an ultra-dense deployment with multiple mmWave base stations around the UE, this removes the need to perform frequent handovers and allows high mobility with reduced latency. We develop and evaluate the performance of such a system for high throughput and reliable low latency communication under various mobility scenarios. To study the impact of mobility on next-generation networks, this work develops and systematically analyzes the performance of the 5G networks under mobility. We also look into the effect of increasing the number of users being served on the network. As a result, these studies are intended to understand better the network requirements for handling mobility and network load with multi-connectivity. This dissertation aims to achieve clarity and also proposes solutions for resolving these real-world network mobility issues

D4.3 Final Report on Network-Level Solutions

Research activities in METIS reported in this document focus on proposing solutions to the network-level challenges of future wireless communication networks. Thereby, a large variety of scenarios is considered and a set of technical concepts is proposed to serve the needs envisioned for the 2020 and beyond. This document provides the final findings on several network-level aspects and groups of solutions that are considered essential for designing future 5G solutions. Specifically, it elaborates on: -Interference management and resource allocation schemes -Mobility management and robustness enhancements -Context aware approaches -D2D and V2X mechanisms -Technology components focused on clustering -Dynamic reconfiguration enablers These novel network-level technology concepts are evaluated against requirements defined by METIS for future 5G systems. Moreover, functional enablers which can support the solutions mentioned aboveare proposed. We find that the network level solutions and technology components developed during the course of METIS complement the lower layer technology components and thereby effectively contribute to meeting 5G requirements and targets.Aydin, O.; Valentin, S.; Ren, Z.; Botsov, M.; Lakshmana, TR.; Sui, Y.; Sun, W.... (2015). D4.3 Final Report on Network-Level Solutions. http://hdl.handle.net/10251/7675