2,380 research outputs found
A Hierarchical Communication Architecture for Oceanic Survelliance Applications
The interest in monitoring applications using underwater sensor networks has been growing in recent years. The severe communication restrictions imposed by underwater channels make that efficient monitoring be a challenging task. Though a lot of research has been conducted on underwater sensor networks, there are only few concrete applications to a real-world case study. In this work, hence, we propose a general three tier architecture leveraging low cost wireless technologies for acoustic communications between underwater sensors and standard technologies, Zigbee and Wireless Fidelity (WiFi), for water surface communications. We have selected a suitable Medium Access Control (MAC) layer, after making a comparison with some common MAC protocols. Thus the performance of the overall system in terms of Signals Discarding Rate (SDR), signalling delay at the surface gateway as well as the percentage of true detection have been evaluated by simulation, pointing out good results which give evidence in applicability’s favour
Cellular Underwater Wireless Optical CDMA Network: Potentials and Challenges
Underwater wireless optical communications is an emerging solution to the
expanding demand for broadband links in oceans and seas. In this paper, a
cellular underwater wireless optical code division multiple-access (UW-OCDMA)
network is proposed to provide broadband links for commercial and military
applications. The optical orthogonal codes (OOC) are employed as signature
codes of underwater mobile users. Fundamental key aspects of the network such
as its backhaul architecture, its potential applications and its design
challenges are presented. In particular, the proposed network is used as
infrastructure of centralized, decentralized and relay-assisted underwater
sensor networks for high-speed real-time monitoring. Furthermore, a promising
underwater localization and positioning scheme based on this cellular network
is presented. Finally, probable design challenges such as cell edge coverage,
blockage avoidance, power control and increasing the network capacity are
addressed.Comment: 11 pages, 10 figure
5G: 2020 and Beyond
The future society would be ushered in a new communication era with the emergence of 5G. 5G would be significantly different, especially, in terms of architecture and operation in comparison with the previous communication generations (4G, 3G...). This book discusses the various aspects of the architecture, operation, possible challenges, and mechanisms to overcome them. Further, it supports users? interac- tion through communication devices relying on Human Bond Communication and COmmunication-NAvigation- SENsing- SErvices (CONASENSE).Topics broadly covered in this book are; • Wireless Innovative System for Dynamically Operating Mega Communications (WISDOM)• Millimeter Waves and Spectrum Management• Cyber Security• Device to Device Communicatio
An efficient multichannel wireless sensor networks MAC protocol based on IEEE 802.11 distributed co-ordinated function.
This research aimed to create new knowledge and pioneer a path in the area relating to future trends in the WSN, by resolving some of the issues at the MAC layer in Wireless Sensor Networks. This work introduced a Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks.
This work commenced by surveying different protocols: contention-based MAC protocols, transport layer protocols, cross-layered design and multichannel multi-radio assignments. A number of existing protocols were analysed, each attempting to resolve one or more problems faced by the current layers.
The 802.15.4 performed very poorly at high data rate and at long range. Therefore 802.15.4 is not suitable for sensor multimedia or surveillance system with streaming data for future multichannel multi-radio systems.
A survey on 802.11 DCF - which was designed mainly for wireless networks –supports and confirm that it has a power saving mechanism which is used to synchronise nodes. However it uses a random back-off mechanism that cannot provide deterministic upper bounds on channel access delay and as such cannot support real-time traffic. The weaknesses identified by surveying this protocol form the backbone of this thesis
The overall aim for this thesis was to introduce multichannel with single radio as a new paradigm for IEEE 802.11 Distributed Coordinated Function (DCF) in wireless sensor networks (WSNs) that is used in a wide range of applications, from military application, environmental monitoring, medical care, smart buildings and other industry and to extend WSNs with multimedia capability which sense for instance sounds or motion, video sensor which capture video events of interest.
Traditionally WSNs do not need high data rate and throughput, since events are normally captured periodically. With the paradigm shift in technology, multimedia streaming has become more demanding than data sensing applications as such the need for high data rate protocol for WSN which is an emerging technology in this area. The IEEE 802.11 can support data rates up to 54Mbps and 802.11 DCF was designed specifically for use in wireless networks.
This thesis focused on designing an algorithm that applied multichannel to IEEE 802.11 DCF back-off algorithm to reduce the waiting time of a node and increase throughput when attempting to access the medium. Data collection in WSN tends to suffer from heavy congestion especially nodes nearer to the sink node. Therefore, this thesis proposes a contention based MAC protocol to address this problem from the inspiration of the 802.11 DCF backoff algorithm resulting from a comparison of IEEE 802.11 and IEEE 802.15.4 for Future Green Multichannel Multi-radio Wireless Sensor Networks
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Radio network management in cognitive LTE-Femtocell Systems
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.There is a strong uptake of femtocell deployment as small cell application
platforms in the upcoming LTE networks. In such two-tier networks of LTEfemtocell
base stations, a large portion of the assigned spectrum is used
sporadically leading to underutilisation of valuable frequency resources.
Novel spectrum access techniques are necessary to solve these current spectrum
inefficiency problems. Therefore, spectrum management solutions should have
the features to improve spectrum access in both temporal and spatial manner.
Cognitive Radio (CR) with the Dynamic Spectrum Access (DSA) is considered
to be the key technology in this research in order to increase the spectrum
efficiency. This is an effective solution to allow a group of Secondary Users
(SUs) to share the radio spectrum initially allocated to the Primary User (PUs) at
no interference.
The core aim of this thesis is to develop new cognitive LTE-femtocell systems
that offer a 4G vision, to facilitate the radio network management in order to
increase the network capacity and further improve spectrum access probabilities.
In this thesis, a new spectrum management model for cognitive radio networks is
considered to enable a seamless integration of multi-access technology with
existing networks. This involves the design of efficient resource allocation
algorithms that are able to respond to the rapid changes in the dynamic wireless
environment and primary users activities. Throughout this thesis a variety of
network upgraded functions are developed using application simulation
scenarios. Therefore, the proposed algorithms, mechanisms, methods, and system
models are not restricted in the considered networks, but rather have a wider
applicability to be used in other technologies.
This thesis mainly investigates three aspects of research issues relating to the
efficient management of cognitive networks: First, novel spectrum resource
management modules are proposed to maximise the spectrum access by rapidly
detecting the available transmission opportunities. Secondly, a developed pilot
power controlling algorithm is introduced to minimise the power consumption by
considering mobile position and application requirements. Also, there is
investigation on the impact of deploying different numbers of femtocell base
stations in LTE domain to identify the optimum cell size for future networks.
Finally, a novel call admission control mechanism for mobility management is
proposed to support seamless handover between LTE and femtocell domains.
This is performed by assigning high speed mobile users to the LTE system to
avoid unnecessary handovers.
The proposed solutions were examined by simulation and numerical analysis to
show the strength of cognitive femtocell deployment for the required
applications. The results show that the new system design based on cognitive
radio configuration enable an efficient resource management in terms of
spectrum allocation, adaptive pilot power control, and mobile handover. The
proposed framework and algorithms offer a novel spectrum management for self organised LTE-femtocell architecture.
Eventually, this research shows that certain architectures fulfilling spectrum
management requirements are implementable in practice and display good
performance in dynamic wireless environments which recommends the
consideration of CR systems in LTE and femtocell networks
Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions
The ever-increasing number of resource-constrained Machine-Type Communication
(MTC) devices is leading to the critical challenge of fulfilling diverse
communication requirements in dynamic and ultra-dense wireless environments.
Among different application scenarios that the upcoming 5G and beyond cellular
networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the
unique technical challenge of supporting a huge number of MTC devices, which is
the main focus of this paper. The related challenges include QoS provisioning,
handling highly dynamic and sporadic MTC traffic, huge signalling overhead and
Radio Access Network (RAN) congestion. In this regard, this paper aims to
identify and analyze the involved technical issues, to review recent advances,
to highlight potential solutions and to propose new research directions. First,
starting with an overview of mMTC features and QoS provisioning issues, we
present the key enablers for mMTC in cellular networks. Along with the
highlights on the inefficiency of the legacy Random Access (RA) procedure in
the mMTC scenario, we then present the key features and channel access
mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT.
Subsequently, we present a framework for the performance analysis of
transmission scheduling with the QoS support along with the issues involved in
short data packet transmission. Next, we provide a detailed overview of the
existing and emerging solutions towards addressing RAN congestion problem, and
then identify potential advantages, challenges and use cases for the
applications of emerging Machine Learning (ML) techniques in ultra-dense
cellular networks. Out of several ML techniques, we focus on the application of
low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss
some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future
publication in IEEE Communications Surveys and Tutorial
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