78 research outputs found
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
heterogeneous public safety network architecture based on ran slicing
Efficient communications are of paramount importance to improve public safety (PS) operations allowing better coordination, higher situation awareness, lower response times, and higher efficiency during emergency. Consequently, the evolution of PS communication networks toward commercial broadband networks is widely well accepted. However, this evolution has to cope with several challenges, such as the provision of sufficient communication capacity, coverage, and resilience as well as deployment costs and efficient exploitation of radio resources. This has triggered the need of new architectural solutions. In this paper, we propose a heterogeneous network communication architecture where both infrastructures and spectrum are shared between PS and commercial operators thus reducing deployment costs and times, and addressing the main challenges of PS communications. The shared radio access network (RAN) is managed by means of network slicing and resources virtualization. The proposed architecture is based on a three-tier scheduler that allows to manage different network layers and different RAN slices. Numerical results derived by means computer simulations are provided in order to highlight the efficiency and flexibility of the proposed architecture in comparison with benchmark alternatives
Generalized Coordinated Multipoint Framework for 5G and Beyond
The characteristic feature of 5G is the diversity of its services for
different user needs. However, the requirements for these services are
competing in nature, which impresses the necessity of a coordinated and
flexible network architecture. Although coordinated multipoint (CoMP) systems
were primarily proposed to improve the cell edge performance in 4G, their
collaborative nature can be leveraged to support the diverse requirements and
enabling technologies of 5G and beyond networks. To this end, we propose
generalization of CoMP to a proactive and efficient resource utilization
framework capable of supporting different user requirements such as
reliability, latency, throughput, and security while considering network
constraints. This article elaborates on the multiple aspects, inputs, and
outputs of the generalized CoMP (GCoMP) framework. Apart from user
requirements, the GCoMP decision mechanism also considers the CoMP scenario and
network architecture to decide upon outputs such as CoMP technique or
appropriate coordinating clusters. To enable easier understanding of the
concept, popular use cases, such as vehicle-to-everything (V2X) communication
and eHealth, are studied. Additionally, interesting challenges and open areas
in GCoMP are discussed.Comment: 11 pages, 7 figure
Self-Evolving Integrated Vertical Heterogeneous Networks
6G and beyond networks tend towards fully intelligent and adaptive design in
order to provide better operational agility in maintaining universal wireless
access and supporting a wide range of services and use cases while dealing with
network complexity efficiently. Such enhanced network agility will require
developing a self-evolving capability in designing both the network
architecture and resource management to intelligently utilize resources, reduce
operational costs, and achieve the coveted quality of service (QoS). To enable
this capability, the necessity of considering an integrated vertical
heterogeneous network (VHetNet) architecture appears to be inevitable due to
its high inherent agility. Moreover, employing an intelligent framework is
another crucial requirement for self-evolving networks to deal with real-time
network optimization problems. Hence, in this work, to provide a better insight
on network architecture design in support of self-evolving networks, we
highlight the merits of integrated VHetNet architecture while proposing an
intelligent framework for self-evolving integrated vertical heterogeneous
networks (SEI-VHetNets). The impact of the challenges associated with
SEI-VHetNet architecture, on network management is also studied considering a
generalized network model. Furthermore, the current literature on network
management of integrated VHetNets along with the recent advancements in
artificial intelligence (AI)/machine learning (ML) solutions are discussed.
Accordingly, the core challenges of integrating AI/ML in SEI-VHetNets are
identified. Finally, the potential future research directions for advancing the
autonomous and self-evolving capabilities of SEI-VHetNets are discussed.Comment: 25 pages, 5 figures, 2 table
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
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