This paper presents a systematic approach to exploiting TV white space (TVWS) for device-to-device (D2D) communications with the aid of the existing cellular infrastructure. The goal is to build a location-specific TVWS database, which provides a lookup table service for any D2D link to determine its maximum permitted emission power (MPEP) in an unlicensed digital TV (DTV) band. To achieve this goal, the idea of mobile crowd sensing is first introduced to collect active spectrum measurements from massive personal mobile devices. Considering the incompleteness of crowd measurements, we formulate the problem of unknown measurements recovery as a matrix completion problem and apply a powerful fixed point continuation algorithm to reconstruct the unknown elements from the known elements. By joint exploitation of the big spectrum data in its vicinity, each cellular base station further implements a nonlinear support vector machine algorithm to perform irregular coverage boundary detection of a licensed DTV transmitter. With the knowledge of the detected coverage boundary, an opportunistic spatial reuse algorithm is developed for each D2D link to determine its MPEP. Simulation results show that the proposed approach can successfully enable D2D communications in TVWS while satisfying the interference constraint from the licensed DTV services. In addition, to our best knowledge, this is the first try to explore and exploit TVWS inside the DTV protection region resulted from the shadowing effect. Potential application scenarios include communications between internet of vehicles in the underground parking and D2D communications in hotspots such as subway, game stadiums, and airports.
As opposed to propagation model estimates, there are few related work that use actual measurements to build spatial TVWS maps or database. One representative research work has been done by the European project FARAMIR (during 2010-2012) (see, e.g., @cite_32 @cite_33 @cite_44 @cite_43 ), where extensive spectrum measurements have been conducted at several locations in Europe to provide a valuable basis for spectrum use modeling in time, frequency, and space, and to increase the radio environmental and spectral awareness of future wireless systems. @cite_46 and @cite_23 , a large set of active measurements have been collected to evaluate the accuracy of propagation models in making radio link predictions, where a conclusion has been reached that these models can be used for nationwide coverage planning, but perform poorly at predicting accurate path loss even in relatively simple outdoor environments and more complex models that consider a larger number of variables (e.g., terrain, climactic, soil conductivity, etc) do not necessarily make better predictions. These studies reinforce the motivation of this paper, which extends those studies by developing effective data mining algorithms to build TVWS database from actual measurements.
@cite_33 @cite_32 @cite_44 @cite_43 @cite_23 @cite_46
2109542432 2110360611 2110002846 1993843131
Most spectrum distribution proposals today develop their allocation algorithms that use conflict graphs to capture interference relationships. The use of conflict graphs, however, is often questioned by the wireless community because of two issues. First, building conflict graphs requires significant overhead and hence generally does not scale to outdoor networks, and second, the resulting conflict graphs do not capture accumulative interference. In this paper, we use large-scale measurement data as ground truth to understand just how severe these issues are in practice, and whether they can be overcome. We build "practical" conflict graphs using measurement-calibrated propagation models, which remove the need for exhaustive signal measurements by interpolating signal strengths using calibrated models. These propagation models are imperfect, and we study the impact of their errors by tracing the impact on multiple steps in the process, from calibrating propagation models to predicting signal strength and building conflict graphs. At each step, we analyze the introduction, propagation and final impact of errors, by comparing each intermediate result to its ground truth counterpart generated from measurements. Our work produces several findings. Calibrated propagation models generate location-dependent prediction errors, ultimately producing conservative conflict graphs. While these "estimated conflict graphs" lose some spectrum utilization, their conservative nature improves reliability by reducing the impact of accumulative interference. Finally, we propose a graph augmentation technique that addresses any remaining accumulative interference, the last missing piece in a practical spectrum distribution system using measurement-calibrated conflict graphs. The wireless sensor networks community, has now an increased understanding of the need for realistic link layer models. Recent experimental studies have shown that real deployments have a "transitional region" with highly unreliable links, and that therefore the idealized perfect-reception-within-range models used in common network simulation tools can be very misleading. In this paper, we use mathematical techniques from communication theory to model and analyze the low power wireless links. The primary contribution of this work is the identification of the causes of the transitional region, and a quantification of their influence. Specifically, we derive expressions for the packet reception rate as a function of distance, and for the width of the transitional region. These expressions incorporate important channel and radio parameters such as the path loss exponent and shadowing variance of the channel; and the modulation and encoding of the radio. A key finding is that for radios using narrow-band modulation, the transitional region is not an artifact of the radio non-ideality, as it would exist even with perfect-threshold receivers because of multi-path fading. However, we hypothesize that radios with mechanisms to combat multi-path effects, such as spread-spectrum and diversity techniques, can reduce the transitional region. In this paper we analyze the efficacy of basic path loss models at predicting median path loss in urban environments. We attempt to bound the practical error of these models and look at how they may hinder practical wireless applications, and in particular dynamic spectrum access networks. This analysis is made using a large set of measurements from production networks in two US cities. We are able to show quantitatively what many experienced radio engineers understand: these models perform poorly at predicting path loss in even relatively simple outdoor environments and are of little practical use aside from making crude estimates of coverage in the least demanding applications. As a solution, we advocate a renewed focus on measurement-based, adaptive path loss models built on appropriate statistical methods. Accurate channel models are extremely important for the design of communications systems. Knowledge of the features of the channel provides communications system designers with the ability to predict the performance of the system for specific modulations, channel coding, and signal processing. This paper presents a statistical characterization of an Ultra-Wideband (UWB) propagation channel in an underground mine. Measurements were carried out in the 2---5 GHz frequency band. Various communication links were considered including both line-of-sight (LOS) and non-LOS (NLOS) scenarios. The measurement procedure allows us to characterize both the large-scale and the small-scale statistics of the channel. The aim here is to study in more details the statistical characteristics of the UWB propagation channel in an underground mine and to provide insight for future statistical channel modeling works. Channel characteristics examined include the distance and frequency dependency of path loss, shadowing fading statistics, and multipath temporal-domain parameter statistics such as the mean excess delay and the RMS delay spread. This work has been carried out by the underground communications research laboratory LRCS (The LRCS laboratory aims to develop research programs related to wireless telecommunications in underground mines. Research is conducted at its own facility as well as the CANMET experimental mine in Val-d'Or, Quebec, Canada), and the experimental mine CANMET (Canadian Center for Minerals and Energy Technology) in Val-d'or, Canada.