Spectrum Trading: An Abstracted Bibliography

This document contains a bibliographic list of major papers on spectrum trading and their abstracts. The aim of the list is to offer researchers entering this field a fast panorama of the current literature. The list is continually updated on the webpage \url{http://www.disp.uniroma2.it/users/naldi/Ricspt.html}. Omissions and papers suggested for inclusion may be pointed out to the authors through e-mail (\textit{[email protected]})

Simple Approximations of the SIR Meta Distribution in General Cellular Networks

Compared to the standard success (coverage) probability, the meta distribution of the signal-to-interference ratio (SIR) provides much more fine-grained information about the network performance. We consider general heterogeneous cellular networks (HCNs) with base station tiers modeled by arbitrary stationary and ergodic non-Poisson point processes. The exact analysis of non-Poisson network models is notoriously difficult, even in terms of the standard success probability, let alone the meta distribution. Hence we propose a simple approach to approximate the SIR meta distribution for non-Poisson networks based on the ASAPPP ("approximate SIR analysis based on the Poisson point process") method. We prove that the asymptotic horizontal gap $G_0$ between its standard success probability and that for the Poisson point process exactly characterizes the gap between the $b$th moment of the conditional success probability, as the SIR threshold goes to $0$. The gap $G_0$ allows two simple approximations of the meta distribution for general HCNs: 1) the per-tier approximation by applying the shift $G_0$ to each tier and 2) the effective gain approximation by directly shifting the meta distribution for the homogeneous independent Poisson network. Given the generality of the model considered and the fine-grained nature of the meta distribution, these approximations work surprisingly well.Comment: This paper has been accepted in the IEEE Transactions on Communications. 14 pages, 13 figure

Simple Approximations of the SIR Meta Distribution in General Cellular Networks

International audienceCompared to the standard success (coverage) probability , the meta distribution of the signal-to-interference ratio (SIR) provides much more fine-grained information about the network performance. We consider general heterogeneous cellular networks (HCNs) with base station tiers modeled by arbitrary stationary and ergodic non-Poisson point processes. The exact analysis of non-Poisson network models is notoriously difficult, even in terms of the standard success probability, let alone the meta distribution. Hence we propose a simple approach to approximate the SIR meta distribution for non-Poisson networks based on the ASAPPP ("approximate SIR analysis based on the Poisson point process") method. We prove that the asymptotic horizontal gap $G_0$ between its standard success probability and that for the Poisson point process exactly characterizes the gap between the $b$th moment of the conditional success probability, as the SIR threshold goes to 0. The gap $G_0$ allows two simple approximations of the meta distribution for general HCNs: 1) the per-tier approximation by applying the shift $G_0$ to each tier and 2) the effective gain approximation by directly shifting the meta distribution for the homogeneous independent Poisson network. Given the generality of the model considered and the fine-grained nature of the meta distribution, these approximations work surprisingly well

An Evolutionary Approach to Adaptive Image Analysis for Retrieving and Long-term Monitoring Historical Land Use from Spatiotemporally Heterogeneous Map Sources

Land use changes have become a major contributor to the anthropogenic global change. The ongoing dispersion and concentration of the human species, being at their orders unprecedented, have indisputably altered Earth’s surface and atmosphere. The effects are so salient and irreversible that a new geological epoch, following the interglacial Holocene, has been announced: the Anthropocene. While its onset is by some scholars dated back to the Neolithic revolution, it is commonly referred to the late 18th century. The rapid development since the industrial revolution and its implications gave rise to an increasing awareness of the extensive anthropogenic land change and led to an urgent need for sustainable strategies for land use and land management. By preserving of landscape and settlement patterns at discrete points in time, archival geospatial data sources such as remote sensing imagery and historical geotopographic maps, in particular, could give evidence of the dynamic land use change during this crucial period. In this context, this thesis set out to explore the potentials of retrospective geoinformation for monitoring, communicating, modeling and eventually understanding the complex and gradually evolving processes of land cover and land use change. Currently, large amounts of geospatial data sources such as archival maps are being worldwide made online accessible by libraries and national mapping agencies. Despite their abundance and relevance, the usage of historical land use and land cover information in research is still often hindered by the laborious visual interpretation, limiting the temporal and spatial coverage of studies. Thus, the core of the thesis is dedicated to the computational acquisition of geoinformation from archival map sources by means of digital image analysis. Based on a comprehensive review of literature as well as the data and proposed algorithms, two major challenges for long-term retrospective information acquisition and change detection were identified: first, the diversity of geographical entity representations over space and time, and second, the uncertainty inherent to both the data source itself and its utilization for land change detection. To address the former challenge, image segmentation is considered a global non-linear optimization problem. The segmentation methods and parameters are adjusted using a metaheuristic, evolutionary approach. For preserving adaptability in high level image analysis, a hybrid model- and data-driven strategy, combining a knowledge-based and a neural net classifier, is recommended. To address the second challenge, a probabilistic object- and field-based change detection approach for modeling the positional, thematic, and temporal uncertainty adherent to both data and processing, is developed. Experimental results indicate the suitability of the methodology in support of land change monitoring. In conclusion, potentials of application and directions for further research are given

High-Power Microwave/ Radio-Frequency Components, Circuits, and Subsystems for Next-Generation Wireless Radio Front-Ends

As the wireless communication systems evolve toward the future generation, intelligence will be the main signature/trend, well known as the concepts of cognitive and software-defined radios which offer ultimate data transmission speed, spectrum access, and user capacity. During this evolution, the human society may experience another round of `information revolution\u27. However, one of the major bottlenecks of this promotion lies in hardware realization, since all the aforementioned intelligent systems are required to cover a broad frequency range to support multiple communication bands and dissimilar standards. As the essential part of the hardware, power amplifiers (PAs) capable of operating over a wide bandwidth have been identified as the key enabling technology. This dissertation focuses on novel methodologies for designing and realizing broadband high-power PAs, their integration with high-quality-factor (high-Q) tunable filters, and relevant investigations on the reliabilities of these tunable devices. It can be basically divided into three major parts: 1.Broadband High-Efficiency Power Amplifiers. Obtaining high PA efficiency over a wide bandwidth is very challenging, because of the difficulty of performing broadband multi-harmonic matching. However, high efficiency is the critical feature for high-performance PAs due to the ever-increasing demands for environmental friendliness, energy saving, and longer battery life. In this research, novel design methodologies of broad-band highly efficient PAs are proposed, including the first-ever mode-transferring PA theory, novel matching network topology, and wideband reconfigurable PA architecture. These techniques significantly advance the state-of-the-art in terms of bandwidth and efficiency. 2.Co-Design of PAs and High-Q Tunable Filters. When implementing the intelligent communication systems, the conventional approach based on independent RF design philosophy suffers from many inherent defects, since no global optimization is achieved leading to degraded overall performance. An attractive method to solve these difficulties is to co-design critical modules of the transceiver chain. This dissertation presents the first-ever co-design of PAs and tunable filters, in which the redundant inter-module matching is entirely eliminated, leading to minimized size & cost and maximized overall performance. The saved hardware resources can be further transferred to enhance system functionalities. Moreover, we also demonstrate that co-design of PAs and filters can lead to more functionalities/benefits for the wireless systems, e.g. efficient and linear amplification of dual-carrier (or multi-carrier) signals. 3.High-Power/Non-Linear Study on Tunable Devices. High-power limitation/power handling is an everlasting theme of tunable devices, as it determines the operational life and is the threshold for actual industrial applications. Under high-power operation, the high RF voltage can lead to failures like tuners\u27 mechanical deflections and gas discharge in the small air spacing of the cavity. These two mechanisms are studied independently with their instantaneous and long-term effects on the device performance. In addition, an anti-biased topology of electrostatic RF MEMS varactors and tunable filters is proposed and experimentally validated for reducing the non-linear effect induced by bias-noise. These investigations will enlighten the designers on how to avoid and/or minimize the non-ideal effects, eventually leading to longer life cycle and performance sustainability of the tunable devices