18 research outputs found
Leveraging Cognitive Radio Networks Using Heterogeneous Wireless Channels
The popularity of ubiquitous Internet services has spurred the fast growth of wireless communications by launching data hungry multimedia applications to mobile devices. Powered by spectrum agile cognitive radios, the newly emerged cognitive radio networks (CRN) are proposed to provision the efficient spectrum reuse to improve spectrum utilization. Unlicensed users in CRN, or secondary users (SUs), access the temporarily idle channels in a secondary and opportunistic fashion while preventing harmful interference to licensed primary users (PUs). To effectively detect and exploit the spectrum access opportunities released from a wide spectrum, the heterogeneous wireless channel characteristics and the underlying prioritized spectrum reuse features need to be considered in the protocol design and resource management schemes in CRN, which plays a critical role in unlicensed spectrum sharing among multiple users.
The purpose of this dissertation is to address the challenges of utilizing heterogeneous wireless channels in CRN by its intrinsic dynamic and diverse natures, and build the efficient, scalable and, more importantly, practical dynamic spectrum access mechanisms to enable the cost-effective transmissions for unlicensed users. Note that the spectrum access opportunities exhibit the diversity in the time/frequency/space domain, secondary transmission schemes typically follow three design principles including 1) utilizing local free channels within short transmission range, 2) cooperative and opportunistic transmissions, and 3) effectively coordinating transmissions in varying bandwidth. The entire research work in this dissertation casts a systematic view to address these principles in the design of the routing protocols, medium access control (MAC) protocols and radio resource management schemes in CRN.
Specifically, as spectrum access opportunities usually have small spatial footprints, SUs only communicate with the nearby nodes in a small area. Thus, multi-hop transmissions in CRN are considered in this dissertation to enable the connections between any unlicensed users in the network. CRN typically consist of intermittent links of varying bandwidth so that the decision of routing is closely related with the spectrum sensing and sharing operations in the lower layers. An efficient opportunistic cognitive routing (OCR) scheme is proposed in which the forwarding decision at each hop is made by jointly considering physical characteristics of spectrum bands and diverse activities of PUs in each single band. Such discussion on spectrum aware routing continues coupled with the sensing selection and contention among multiple relay candidates in a multi-channel multi-hop scenario. An SU selects the next hop relay and the working channel based upon location information and channel usage statistics with instant link quality feedbacks. By evaluating the performance of the routing protocol and the joint channel and route selection algorithm with extensive simulations, we determine the optimal channel and relay combination with reduced searching complexity and improved spectrum utilization.
Besides, we investigate the medium access control (MAC) protocol design in support of multimedia applications in CRN. To satisfy the quality of service (QoS) requirements of heterogeneous applications for SUs, such as voice, video, and data, channels are selected to probe for appropriate spectrum opportunities based on the characteristics and QoS demands of the traffic along with the statistics of channel usage patterns. We propose a QoS-aware MAC protocol for multi-channel single hop scenario where each single SU distributedly determines a set of channels for sensing and data transmission to satisfy QoS requirements. By analytical model and simulations, we determine the service differentiation parameters to provision multiple levels of QoS.
We further extend our discussion of dynamic resource management to a more practical deployment case. We apply the experiences and skills learnt from cognitive radio study to cellular communications. In heterogeneous cellular networks, small cells are deployed in macrocells to enhance link quality, extend network coverage and offload traffic. As different cells focus on their own operation utilities, the optimization of the total system performance can be analogue to the game between PUs and SUs in CRN. However, there are unique challenges and operation features in such case. We first present challenging issues including interference management, network coordination, and interworking between cells in a tiered cellular infrastructure. We then propose an adaptive resource management framework to improve spectrum utilization and mitigate the co-channel interference between macrocells and small cells. A game-theory-based approach is introduced to handle power control issues under constrained control bandwidth and limited end user capability. The inter-cell interference is mitigated based upon orthogonal transmissions and strict protection for macrocell users.
The research results in the dissertation can provide insightful lights on flexible network deployment and dynamic spectrum access for prioritized spectrum reuse in modern wireless systems. The protocols and algorithms developed in each topic, respectively, have shown practical and efficient solutions to build and optimize CRN
Mobile Ad Hoc Networks
Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms
Mobile Ad Hoc Networks
Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms
Distributed scheduling algorithms for LoRa-based wide area cyber-physical systems
Low Power Wide Area Networks (LPWAN) are a class of wireless communication protocols that work over long distances, consume low power and support low datarates. LPWANs have been designed for monitoring applications, with sparse communication from nodes to servers and sparser from servers to nodes. Inspite of their initial design, LPWANs have the potential to target applications with higher and stricter requirements like those of Cyber-Physical Systems (CPS). Due to their long-range capabilities, LPWANs can specifically target CPS applications distributed over a wide-area, which is referred to as Wide-Area CPS (WA-CPS). Augmenting WA-CPSs with wireless communication would allow for more flexible, low-cost and easily maintainable deployment. However, wireless communications come with problems like reduced reliability and unpredictable latencies, making them harder to use for CPSs.
With this intention, this thesis explores the use of LPWANs, specifically LoRa, to meet the communication and control requirements of WA-CPSs. The thesis focuses on using LoRa due to its high resilience to noise, several communication parameters to choose from and a freely modifiable communication stack and servers making it ideal for research and deployment. However, LoRaWAN suffers from low reliability due to its ALOHA channel access method. The thesis posits that "Distributed algorithms would increase the protocol's reliability allowing it to meet the requirements of WA-CPSs". Three different application scenarios are explored in this thesis that leverage unexplored aspects of LoRa to meet their requirements. The application scenarios are delay-tolerant vehicular networks, multi-stakeholder WA-CPS deployments and water distribution networks. The systems use novel algorithms to facilitate communication between the nodes and gateways to ensure a highly reliable system. The results outperform state-of-art techniques to prove that LoRa is currently under-utilised and can be used for CPS applications.Open Acces
Teoria de jogos para utilização efetiva dos recursos em aplicações para 5G
Doutoramento em Engenharia Eletrotécnica - TelecomunicaçõesEsta tese tem como objetivo fornecer afirmações conclusivas em relação a
utilização eficiente de recursos para redes e aplicações de 5G (5a geração)
com recurso a teoria dos jogos. Neste contexto, investigamos dois cenários
principais, um relativo a comunicações móveis e um outro relativo a redes
inteligentes. Uma métrica importante para o desenho das redes móveis
emergentes é a eficiência energética, com particular ênfase no lado do dispositivo
móvel, onde as tecnologias das baterias são ainda limitadas. Alguns
trabalhos de investigação relacionados têm demonstrado que a cooperação
pode ser um paradigma útil no sentido de resolver o problema do défice
energético. Contudo, pretendemos ir mais além, ao definir a cooperação e
os utilizadores móveis como um grupo de jogadores racionais, que podem
atuar sobre estratégias e utilidades, por forma a escolher a retransmissão
mais apropriada para poupança de energia. Esta interpretação presta-se Ã
aplicação da teoria dos jogos, e recorremos assim aos jogos coalicionais para
solucionar conflitos de interesse entre dispositivos cooperantes, empregando
Programação Linear (LP) para resolver o problema da selecção da retransmissão e derivar a principal solução do jogo. Os resultados mostram que a escolha do jogo de retransmissão coalicional proposto pode potencialmente duplicar a duração da bateria, numa era em que a próxima geração de dispositivos móveis necessitará de cada vez mais energia para suportar serviços
e aplicações cada vez mais sofisticados. O segundo cenário investiga a resposta
da procura em aplicações smart grid, que está a ganhar interesse sob
a égide do 5G e que é considerada uma abordagem promissora, incentivando
os utilizadores a consumir electricidade de forma mais uniforme em horas de
vazio. Recorremos novamente à teoria dos jogos, imaginando as interacções
estratégicas entre a empresa fornecedora de energia eléctrica e os potenciais
utilizadores finais como um jogo de forma extensiva. São abordados
dois programas em tempo real de resposta à procura: Day-Ahead Pricing
(DAP) e Convex Pricing Tariffs. A resposta dos consumidores residenciais
conscientes dos preços destas tarifas, é formulada como um problema
de Mixed Integer Linear Programming (MILP) ou Quadratic Programming
(QP), nos quais as soluções potenciais são o agendamento dos seus electrodomésticos inteligentes de modo a minimizar os seus gastos diários de electricidade, satisfazendo as suas necessidades diárias de energia e nÃveis
de conforto. Os resultados demonstram que implementar o programa DAP
pode reduzir a razão Peak-to-Average (PAR) at e 71% e as faturas de consumo
das casas inteligentes at e 32%. Para além disso, a aplicação de tarifas
convexas em tempo real pode melhorar ainda mais estas métricas de desempenho,
alcançando uma redução de 80% do PAR e uma economia de
mais de 50% na faturação da energia residencial.This research thesis aims to provide conclusive statements towards effective
resource utilization for 5G (5th Generation) mobile networks and applications
using game theory. In this context, we investigate two key scenarios
pertaining to mobile communications and smart grids. A pivotal design
driver for the upcoming era of mobile communications is energy efficiency,
with particular emphasis on the mobile side where battery technology is still
limited. Related works have shown that cooperation can be a useful engineering
paradigm to take a step towards solving the energy deficit. However,
we go beyond by envisaging cooperation and mobile users as a game of rational
players, that can act on strategies and utilities in order to choose the
most appropriate relay for energy saving. This interpretation lends itself to
the application of game theory, and we look at coalitional games to settle
conflicts of interest among cooperating user equipments, and employ Linear
Programming (LP) to solve the relay selection problem and to derive the
core solution of the game. The results reveal that adopting the proposed
coalitional relaying game can potentially double battery lifetime, in an era
where the next wave of next generation handsets will be more energy demanding
supporting sophisticated services and applications. The second
scenario investigates demand response in smart grid applications, which is
also gaining momentum under the umbrella of 5G, which is a promising
approach urging end-users to consume electricity more evenly during nonpeak
hours of the day. Again, we resort to game theory and picture the
strategic interactions between the electric utility company and the potential
end-users as an extensive form game. Two real-time demand response
programmes are addressed, namely Day-Ahead Pricing (DAP) and convex
pricing tariffs. The response of price-aware residential consumers to these
programmes is formulated as Mixed Integer Linear Programming (MILP)
or Quadratic Programming (QP) problem, which optimally schedule their
smart home appliances so as to minimise their daily electricity expenses
while satisfying their daily energy needs and comfort levels. The results
demonstrate that implementing the DAP programme can reduce the Peakto-
Average Ratio (PAR) of demand by up to 71% and cut smart households
bill by 32%. Moreover, applying real-time convex pricing tariffs can push
these performance metrics even further, achieving 80% PAR reduction and
more than 50% saving on the household electricity bill
PRAM: Penalized Resource Allocation Method for Video Services
The human visual system response to picture quality degradation due to packet loss is very different from the responses of objective quality measures. While video quality due to packet loss may be impaired by at most for one Group of Pictures (GOP), its subjective quality degradation may last for several GOPs. This has a great impact on resource allocation strategies, which normally make decisions on instantaneous conditions of multiplexing buffer. This is because, when the perceptual impact of degraded video quality is much longer than its objective degradation period, any assigned resources to the degraded flow is wasted. This paper, through both simulations and analysis shows that, during resource allocation, if the quality of a video stream is significantly degraded, it is better to penalize this degraded flow from getting its full bandwidth share and instead assign the remaining share to other flows preventing them from undergoing quality degradation
Scaling Laws for Vehicular Networks
Equipping automobiles with wireless communications and networking capabilities is becoming the frontier in the evolution to the next generation intelligent transportation systems (ITS). By means of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, information generated by the vehicle-borne computer, vehicle control system, on-board sensors, or roadside infrastructure, can be effectively disseminated among vehicles/infrastructure in proximity or to vehicles/infrastructure multiple hops away, known as vehicular networks (VANETs), to enhance the situational awareness of vehicles and provide motorist/passengers with an information-rich travel environment. Scaling law for throughput capacity and delay in wireless networks has been considered as one of the most fundamental issues, which characterizes the trend of throughput/delay behavior when the network size increases. The study of scaling laws can lead to a better understanding of intrinsic properties of wireless networks and theoretical guidance on network design and deployment. Moreover, the results could also be applied to predict network performance, especially for the large-scale vehicular networks. However, map-restricted mobility and spatio-temporal dynamics of vehicle density dramatically complicate scaling laws studies for VANETs. As an effort to lay a scientific foundation of vehicular networking, my thesis investigates capacity scaling laws for vehicular networks with and without infrastructure, respectively.
Firstly, the thesis studies scaling law of throughput capacity and end-to-end delay for a social-proximity vehicular network, where each vehicle has a restricted mobility region around a specific social spot and services are delivered in a store-carry-and-forward paradigm. It has been shown that although the throughput and delay may degrade in a high vehicle density area, it is still possible to achieve almost constant scaling for per vehicle throughput and end-to-end delay.
Secondly, in addition to pure ad hoc vehicular networks, the thesis derives the capacity scaling laws for networks with wireless infrastructure, where services are delivered uniformly from infrastructure to all vehicles in the network. The V2V communication is also required to relay the downlink traffic to the vehicles outside the coverage of infrastructure. Three kinds of infrastructures have been considered, i.e., cellular base stations, wireless mesh backbones (a network of mesh nodes, including one mesh gateway), and roadside access points. The downlink capacity scaling is derived for each kind of infrastructure. Considering that the deployment/operation costs of different infrastructure are highly variable, the capacity-cost tradeoffs of different deployments are examined. The results from the thesis demonstrate the feasibility of deploying non-cellular infrastructure for supporting high-bandwidth vehicular applications.
Thirdly, the fundamental impact of traffic signals at road intersection on drive-thru Internet access is particularly studied. The thesis analyzes the time-average throughput capacity of a typical vehicle driving through randomly deployed roadside Wi-Fi networks. Interestingly, we show a significant throughput gain for vehicles stopping at intersections due to red signals. The results provide a quick and efficient way of determining the Wi-Fi deployment scale according to required quality of services.
In summary, the analysis developed and the scaling laws derived in the thesis provide should be very useful for understanding the fundamental performance of vehicular networks
7. GI/ITG KuVS Fachgespräch Drahtlose Sensornetze
In dem vorliegenden Tagungsband sind die Beiträge des Fachgesprächs Drahtlose Sensornetze 2008 zusammengefasst. Ziel dieses Fachgesprächs ist es, Wissenschaftlerinnen und Wissenschaftler aus diesem Gebiet die Möglichkeit zu einem informellen Austausch zu geben – wobei immer auch Teilnehmer aus der Industrieforschung willkommen sind, die auch in diesem Jahr wieder teilnehmen.Das Fachgespräch ist eine betont informelle Veranstaltung der GI/ITG-Fachgruppe „Kommunikation und Verteilte Systeme“ (www.kuvs.de). Es ist ausdrücklich keine weitere Konferenz mit ihrem großen Overhead und der Anforderung, fertige und möglichst „wasserdichte“ Ergebnisse zu präsentieren, sondern es dient auch ganz explizit dazu, mit Neueinsteigern auf der Suche nach ihrem Thema zu diskutieren und herauszufinden, wo die Herausforderungen an die zukünftige Forschung überhaupt liegen.Das Fachgespräch Drahtlose Sensornetze 2008 findet in Berlin statt, in den Räumen der Freien Universität Berlin, aber in Kooperation mit der ScatterWeb GmbH. Auch dies ein Novum, es zeigt, dass das Fachgespräch doch deutlich mehr als nur ein nettes Beisammensein unter einem Motto ist.Für die Organisation des Rahmens und der Abendveranstaltung gebührt Dank den beiden Mitgliedern im Organisationskomitee, Kirsten Terfloth und Georg Wittenburg, aber auch Stefanie Bahe, welche die redaktionelle Betreuung des Tagungsbands übernommen hat, vielen anderen Mitgliedern der AG Technische Informatik der FU Berlin und natürlich auch ihrem Leiter, Prof. Jochen Schiller
Distributed algorithms for optimized resource management of LTE in unlicensed spectrum and UAV-enabled wireless networks
Next-generation wireless cellular networks are morphing into a massive Internet
of Things (IoT) environment that integrates a heterogeneous mix of wireless-enabled
devices such as unmanned aerial vehicles (UAVs) and connected vehicles.
This unprecedented transformation will not only drive an exponential growth in
wireless traffic, but it will also lead to the emergence of new wireless service
applications that substantially differ from conventional multimedia services. To
realize the fifth generation (5G) mobile networks vision, a new wireless radio
technology paradigm shift is required in order to meet the quality of service
requirements of these new emerging use cases. In this respect, one of the major
components of 5G is self-organized networks. In essence, future cellular networks
will have to rely on an autonomous and self-organized behavior in order to manage
the large scale of wireless-enabled devices. Such an autonomous capability can be
realized by integrating fundamental notions of artificial intelligence (AI) across
various network devices.
In this regard, the main objective of this thesis is to propose novel self-organizing
and AI-inspired algorithms for optimizing the available radio resources
in next-generation wireless cellular networks. First, heterogeneous networks that
encompass licensed and unlicensed spectrum are studied. In this context, a deep
reinforcement learning (RL) framework based on long short-term memory cells is
introduced. The proposed scheme aims at proactively allocating the licensed assisted
access LTE (LTE-LAA) radio resources over the unlicensed spectrum while
ensuring an efficient coexistence with WiFi. The proposed deep learning algorithm
is shown to reach a mixed-strategy Nash equilibrium, when it converges.
Simulation results using real data traces show that the proposed scheme can yield
up to 28% and 11% gains over a conventional reactive approach and a proportional
fair coexistence mechanism, respectively. In terms of priority fairness, results
show that an efficient utilization of the unlicensed spectrum is guaranteed when
both technologies, LTE-LAA and WiFi, are given equal weighted priorities for
transmission on the unlicensed spectrum. Furthermore, an optimization formulation
for LTE-LAA holistic traffic balancing across the licensed and the unlicensed
bands is proposed. A closed form solution for the aforementioned optimization
problem is derived. An attractive aspect of the derived solution is that it can be
applied online by each LTE-LAA small base station (SBS), adapting its transmission behavior in each of the bands, and without explicit communication with
WiFi nodes. Simulation results show that the proposed traffic balancing scheme
provides a better tradeoff between maximizing the total network throughput and
achieving fairness among all network
ows compared to alternative approaches
from the literature. Second, UAV-enabled wireless networks are investigated. In
particular, the problems of interference management for cellular-connected UAVs
and the use of UAVs for providing backhaul connectivity to SBSs are studied.
Speci cally, a deep RL framework based on echo state network cells is proposed
for optimizing the trajectories of multiple cellular-connected UAVs while minimizing
the interference level caused on the ground network. The proposed algorithm
is shown to reach a subgame perfect Nash equilibrium upon convergence. Moreover,
an upper and lower bound for the altitude of the UAVs is derived thus
reducing the computational complexity of the proposed algorithm. Simulation
results show that the proposed path planning scheme allows each UAV to achieve
a tradeoff between minimizing energy efficiency, wireless latency, and the interference
level caused on the ground network along its path. Moreover, in the context
of UAV-enabled wireless networks, a UAV-based on-demand aerial backhaul network
is proposed. For this framework, a network formation algorithm, which is
guaranteed to reach a pairwise stable network upon convergence, is presented.
Simulation results show that the proposed scheme achieves substantial performance
gains in terms of both rate and delay reaching, respectively, up to 3.8 and
4-fold increase compared to the formation of direct communication links with the
gateway node. Overall, the results of the different proposed schemes show that
these schemes yield significant improvements in the total network performance
as compared to current existing literature. In essence, the proposed algorithms
can also provide self-organizing solutions for several resource management problems
in the context of new emerging use cases in 5G networks, such as connected
autonomous vehicles and virtual reality headsets