1,488 research outputs found
An Agent-Based Model for Secondary Use of Radio Spectrum
Wireless communications rely on access to radio spectrum. With a continuing proliferation of wireless applications and services, the spectrum resource becomes scarce. The measurement studies of spectrum usage, however, reveal that spectrum is being used sporadically in many geographical areas and times. In an attempt to promote efficiency of spectrum usage, the Federal Communications Commission has supported the use of market mechanism to allocate and assign radio spectrum. We focus on the secondary use of spectrum defined as a temporary access of existing licensed spectrum by a user who does not own a spectrum license. The secondary use of spectrum raises numerous technical, institutional, economic, and strategic issues that merit investigation. Central to the issues are the effects of transaction costs associated with the use of market mechanism and the uncertainties due to potential interference.The research objective is to identify the pre-conditions as to when and why the secondary use would emerge and in what form. We use transaction cost economics as the theoretical framework in this study. We propose a novel use of agent-based computational economics to model the development of the secondary use of spectrum. The agent-based model allows an integration of economic and technical considerations to the study of pre-conditions to the secondary use concept. The agent-based approach aims to observe the aggregate outcomes as a result of interactions among agents and understand the process that leads to the secondary use, which can then be used to create policy instruments in order to obtain the favorable outcomes of the spectrum management
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Media Policy and Independent Journalism in Greece
Today, Greece is the European Union member state where journalism and the media face their most acute crisis. This study identifies the urgent problems facing media policy in Greece and how they affect independent journalism.
Since the 1980s and ’90s, deregulation has increased the viewing choices for audiences in Greece. At the same time, the legal and regulatory framework has helped concentrate ownership of press, television, and radio outlets. Private channels operate with temporary licenses and independent regulatory authorities function superficially and ambivalently. As a result, the market has been dominated by a handful of powerful newspaper interests, which have
expanded into audiovisual and online media. Recent laws have further liberalized media ownership and cross-ownership.
Media Policy and Independent Journalism in Greece, based partly on in-depth interviews with key actors, explores these issues and more in this six-chapter report
Radio Spectrum and the Disruptive Clarity OF Ronald Coase.
In the Federal Communications Commission, Ronald Coase (1959) exposed deep foundations via normative argument buttressed by astute historical observation. The government controlled scarce frequencies, issuing sharply limited use rights. Spillovers were said to be otherwise endemic. Coase saw that Government limited conflicts by restricting uses; property owners perform an analogous function via the "price system." The government solution was inefficient unless the net benefits of the alternative property regime were lower. Coase augured that the price system would outperform the administrative allocation system. His spectrum auction proposal was mocked by communications policy experts, opposed by industry interests, and ridiculed by policy makers. Hence, it took until July 25, 1994 for FCC license sales to commence. Today, some 73 U.S. auctions have been held, 27,484 licenses sold, and 17 billion in U.S. welfare losses have been averted. Not bad for the first 50 years of this, or any, Article appearing in Volume II of the Journal of Law & Economics.
Compression Ratio Learning and Semantic Communications for Video Imaging
Camera sensors have been widely used in intelligent robotic systems.
Developing camera sensors with high sensing efficiency has always been
important to reduce the power, memory, and other related resources. Inspired by
recent success on programmable sensors and deep optic methods, we design a
novel video compressed sensing system with spatially-variant compression
ratios, which achieves higher imaging quality than the existing snapshot
compressed imaging methods with the same sensing costs. In this article, we
also investigate the data transmission methods for programmable sensors, where
the performance of communication systems is evaluated by the reconstructed
images or videos rather than the transmission of sensor data itself. Usually,
different reconstruction algorithms are designed for applications in high
dynamic range imaging, video compressive sensing, or motion debluring. This
task-aware property inspires a semantic communication framework for
programmable sensors. In this work, a policy-gradient based reinforcement
learning method is introduced to achieve the explicit trade-off between the
compression (or transmission) rate and the image distortion. Numerical results
show the superiority of the proposed methods over existing baselines
Resource Allocation for D2D Communications Based on Matching Theory
PhDDevice-to-device (D2D) communications underlaying a cellular infrastructure takes advantage
of the physical proximity of communicating devices and increasing resource utilisation.
However, adopting D2D communications in complex scenarios poses substantial
challenges for the resource allocation design. Meanwhile, matching theory has emerged
as a promising framework for wireless resource allocation which can overcome some limitations
of game theory and optimisation. This thesis focuses on the resource allocation
optimisation for D2D communications based on matching theory.
First, resource allocation policy is designed for D2D communications underlaying cellular
networks. A novel spectrum allocation algorithm based on many-to-many matching
is proposed to improve system sum rate. Additionally, considering the quality-of-service
(QoS) requirements and priorities of di erent applications, a context-aware resource allocation
algorithm based on many-to-one matching is proposed, which is capable of providing
remarkable performance enhancement in terms of improved data rate, decreased
packet error rate (PER) and reduced delay.
Second, to improve resource utilisation, joint subchannel and power allocation problem
for D2D communications with non-orthogonal multiple access (NOMA) is studied. For
the subchannel allocation, a novel algorithm based on the many-to-one matching is
proposed for obtaining a suboptimal solution. Since the power allocation problem is
non-convex, sequential convex programming is adopted to transform the original power
allocation problem to a convex one. The proposed algorithm is shown to enhance the
network sum rate and number of accessed users.
Third, driven by the trend of heterogeneity of cells, the resource allocation problem for
NOMA-enhanced D2D communications in heterogeneous networks (HetNets) is investigated. In such a scenario, the proposed resource allocation algorithm is able to closely
approach the optimal solution within a limited number of iterations and achieves higher
sum rate compared to traditional HetNets schemes.
Thorough theoretical analysis is conducted in the development of all proposed algorithms,
and performance of proposed algorithm is evaluated via comprehensive simulations.
This thesis concludes that matching theory based resource allocation for D2D communications
achieves near-optimal performance with acceptable complexity. In addition,
the application of D2D communications in NOMA and HetNets can improve system
performance in terms of sum rate and users connectivity
Enhancing the museum experience with a sustainable solution based on contextual information obtained from an on-line analysis of users’ behaviour
Human computer interaction has evolved in the last years in order to enhance users’ experiences and provide more intuitive and usable systems. A major leap through in this scenario is obtained by embedding, in the physical environment, sensors capable of detecting and processing users’ context (position, pose, gaze, ...). Feeded by the so collected information flows, user interface paradigms may shift from stereotyped gestures
on physical devices, to more direct and intuitive ones that reduce the semantic gap between the action and the corresponding system reaction or even anticipate the user’s needs, thus limiting the overall learning effort and increasing user satisfaction. In order to make this process effective, the context of the user (i.e. where s/he is, what is s/he doing, who s/he is, what are her/his preferences and also actual perception and needs) must be properly understood. While collecting data on some aspects can be easy, interpreting them all in a meaningful way in order to improve the overall user experience is much harder. This is more evident when we consider informal learning environments like museums, i.e. places that are designed to elicit visitor response towards the artifacts on display and the cultural themes proposed. In such a situation, in fact, the system should adapt to the attention paid by the user choosing the appropriate content for the user’s purposes, presenting an intuitive interface to navigate it. My research goal is focused on collecting, in a simple,unobtrusive, and sustainable way, contextual information about the visitors with the purpose of creating more engaging and personalized experiences
A framework for Adaptive Capability Profiling
This thesis documents research providing improvements in the field of accessibility modelling, which will be of particular interest as computing becomes increasingly ubiquitous. It is argued that a new approach is required that takes into account the dynamic relationship between users, their technology (both hardware and software) and any additional Assistive Technologies (ATs) that may be required. In addition, the approach must find a balance between fidelity and transportability.
A theoretical framework has been developed that is able to represent both users and technology in symmetrical (hierarchical) recursive profiles, using a vocabulary that moves from device-specific to device-agnostic capabilities. The research has resulted in the development of a single unified solution that is able to functionally assess the accessibility of interactions through the use of pattern matching between graph-based profiles. A self-efficacy study was also conducted, which identified the inability of older people to provide the data necessary to drive a system based on the framework. Subsequently, the ethical considerations surrounding the use of automated data collection agents were discussed and a mechanism for representing contextual information was also included. Finally, real user data was collected and processed using a practically implemented prototype to provide an evaluation of
the approach.
The thesis represents a contribution through its ability to both: (1) accommodate the collection of data from a wide variety of sources, and (2) support accessibility assessments at varying levels of abstraction in order to identify if/where assistance may be necessary. The resulting approach has contributed to a work-package of the Sus-IT project, under the New Dynamics of Ageing (NDA) programme of research in the UK. It has also been presented to a W3C Research and Development Working Group symposium on User Modelling for Accessibility (UM4A). Finally, dissemination has been taken forward through its inclusion as an invited paper presented during a subsequent parallel session within the 8th International Conference on Universal Access in Human-Computer Interaction
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