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In wireless digital communications, the sender and receiver typically know the modulation scheme with which they will be communicating. Automatic modulation identification is the ability to identify the modulation in a communication system with little to no prior knowledge of the modulation scheme. Many techniques for modulation identification operate on many assumptions including that the input signal is base-banded, the carrier frequency is known and that the signal is narrow-band (i.e. neighboring signals in the wide-band are excluded). This work provides the blind processing of an arbitrary wide-band signal to allow such assumptions. The challenges of such a front-end or pre-processor include detecting signals which can appear at any frequency, with any band-width at any given time and for any arbitrary duration. This work takes as its input a wide-band signal with a random number of sub-signals, each turning on and o at random times and each at random locations in the frequency domain. The output of the system is a collection of signals corresponding to each sub-signal brought down to base-band, isolated in the frequency and time domains, nominally sampled and with estimates of key parameters.

Aim of this master's thesis is the creation of serial communication interface for FITkit. This serial interface is a full duplex industrial bus based on 20mA loop circuit and it should allow connection of two FITkits by RS-485. Aim of this paper is to design simple software allowing communication of two FITkits and to secure this communication on RS-485 link against interference or transfer errors.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第19505号 / 理博第4165号 / 新制||理||1598(附属図書館) / 32541 / 京都大学大学院理学研究科地球惑星科学専攻 / (主査)教授 津田 敏隆, 教授 石川 裕彦, 教授 余田 成男 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

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Three new and efficient carrier frequency offset estimators are created for the case of disjoint pilot symbol blocks. The estimators are efficient in both a statistical sense and a computational sense. They are formulated to reduce computational cost for use in real-time applications, such as FPGA (field programmable gate array) devices. A reduced cost maximum likelihood (ML) frequency estimator is described. It is a generalization of the approximate ML estimator for a single block of pilot symbols. A number of recent ML estimation techniques are integrated with the purpose of reducing the computational cost while preserving estimation performance. The estimator incorporates multirate signal processing methods, FFT periodogram searches, and directed periodogram searches. The subsequent relationships between FFT lengths, resampling rates, and search iterations is established. The proposed estimator exhibits very good accuracy, operating range, and a low SNR threshold, and has low cost. A data-aided frequency estimator based on the measurement of phase increments, is also derived. It has extremely low cost, but a high SNR threshold. However, its formulation is such that a careful analysis of the range error problem may be performed. From this analysis certain conclusions are made about proper pilot symbol organization, and these conclusions are applicable to other frequency estimators. The third estimator is a generalization of the autocorrelation frequency estimation technique. The generalizations are needed to account for the spacings between the pilot blocks. A novel iterative approach, incorporating a Kalman filter, is used to improve operating range. It is shown that the autocorrelation frequency estimator exhibits good accuracy while maintaining a useful operating range. Real-time architectures are described for the ML and autocorrelation frequency estimators using disjoint pilot blocks. The computational cost and estimation performance of the proposed estimators are analyzed and it is shown that they give estimation performance near to theoretical limits, while preserving wide operating range. We see that the autocorrelation estimator is appropriate for small numbers of pilot symbols, while the ML estimator is appropriate for large numbers of pilot symbols. The new frequency estimators are the first to be derived (for the case of disjoint blocks of pilot symbols) such that computational cost is kept low, while still achieving high accuracy, a wide operating range, and low SNR thresholds.

The radio frequency spectrum is becoming increasingly crowded and research efforts are being made both from the side of communication and from radar to allow for sharing of the radio frequency spectrum. In this thesis, suitable methods for classifying incoming signals as either communication signals or radar signals using machine learning are evaluated, with the purpose of filtering communication signals in radar warning receiver systems. To this end, a dataset of simulated communication and radar signals is generated for evaluation. The methods are evaluated in terms of both accuracy and computational complexity since both of these aspects are critical in a radar warning receiver setting. The results show that a deep learning model can be designed to outperform expert feature-based models in terms of accuracy, as has previously been confirmed in other fields. In terms of computational complexity, however, they are vastly outperformed by a model based on ensemble decision trees. As such, a deep learning model may be too complex for the task of filtering communication signals from radar signals in a radar warning receiver setting. The classification accuracy needs to be weighed against the model size and classification time. Future work should focus on optimizing the feature extraction implementation for a more fair classification time comparison, as well as evaluating the models on recorded data. / Radiospektrumet blir alltmer belastat och forskningsinsatser görs inom både kommunikation och radar för att tillåta delning av spektrumet. I denna rapport utvärderas lämpliga metoder för att klassificera inkommande signaler som antingen kommunikation eller radar med hjälp av maskininlärning, med syftet att filtrera ut kommunikationssignaler i radarvarnare. För detta ändamål genereras ett dataset med simulerade kommunikations- och radarsignaler för att jämföra modellerna. Metoderna utvärderas med avseende på både precision och beräkningskomplexitet, eftersom att båda aspekterna är kritiska egenskaper i en radarvarnare. Resultaten visar att en djupinlärningsmodell kan utformas för att överträffa modeller baserade på expertdesignade särdrag med avseende på träffsäkerhet, såsom tidigare visats inom andra områden. Avseende beräkningskomplexitet, är däremot modellen baserad på en ensemble av beslutsträd överlägsen. Detta innebär möjligen att en djupinlärningsmodell är allt för komplex för syftet att filtrera bort kommunikationssignaler från radarsignaler i en radarvarnare. Modellens träffsäkerhet bör vägas mot dess storlek och tiden för klassificering. Framtida arbete bör inriktas på att optimera beräkningen av särdragen för en mer rättvis jämförelse av tiden som krävs för klassificering, samt att utvärdera modellerna på inspelad data.

Time synchronization is critical for the operation of radio base stations (RBS) in telecommunication companies. Global navigation satellite system (GNSS) is an existing technology to provide precise timing information to distributed RBSs. GNSS timing receiver is used for providing higher timing accuracy than normal GNSS receiver in this synchronization domain.In this thesis, an experiment method for GNSS timing receiver performance in urban canyon has been designed and implemented to evaluate information and the quality of the one pulse per second (1PPS) signal generated by two different GNSS timing receivers. Multi-path signals and the gathered satellite geometry caused by poor sky visibility is identified as the main influential factors to the performance of the GNSS timing receivers. A mathematical model has been built for estimating the multi-path effect. GNSS planning tools are used to simulate the number of line-of-sight (LOS) satellites and Dilution of Precision (DOP) value.Sentinel is a 1PPS signal analyzing equipment from Calnex. Sentinel has an embedded rubidium clock, GNSS antenna, and receiver, and it can produce 1PPS signals to be used as a reference. In this report, we installed our GNSS antenna of Sentinel on the roof and test GNSS antenna in two specified positions representing urban canyon and rooftop. Recorded NMEA messages from GNSS receiver can help us to study the number of visible satellites, PDOP value and multi-path signals in realistic situations.The results show how the noise and time phase of 1PPS signals will be influenced in urban canyons. Since, the geometry of used satellites is similar to the rooftop situation, the multi-path effect of signals is identified as the main reason of this difference.This information is useful when telecommunication companies want to install their radio base station in urban canyons. It will help Ericsson to understand how their GNSS timing receiver is working and how the urban canyon will influence its performance. / Tidssynkronisering är kritisk för driften av radiobasstationer (RBS) i telekommunikationsföretag. Global Navigation Satellite System (GNSS) är en befintlig teknik för att ge exakt tidsinformation till distribuerade basstationer. GNSS-baserade tidsmottagare används för att ge högre timing-noggrannhet än vanlig GNSS mottagare i denna synkroniseringsdomän. I denna avhandling har en experimentmetod för GNSS-timingmottagarnas prestanda i urban canyon utformats och implementerats för att utvärdera den genererade informationen och kvaliteten på en puls per sekund-signal (1PPS). Flervägssignaler och den samlade satellitgeometrin som orsakas av dålig himmelsynlighet identifieras som de mest inflytelserika faktorerna för GNSS-tidsmottagarnas prestanda. En matematisk modell har donstruerats för att estimera multi-path-effekten. GNSS-planeringsverktyg används för att simulera antalet LOS-satelliter och DOP-värde (Dilution of Precision). Sentinel är en 1PPS signalanalysutrustning från Calnex. Sentinel har en inbyggd rubidiumklocka, GNSS-antenn och mottagare, och den kan producera 1PPS-signaler som ska användas som referens. I den här rapporten installerade vi vår GNSS-antenn på Sentinel på taket och GNSS-testantennen i två angivna positioner som representerar urban canyon och tak. Inspelade NMEA-meddelanden från GNSS-mottagare kan hjälpa oss att studera antalet synliga satelliter, PDOP-värde och flervägssignaler i realistiska scenarier. Resultatet visar att ljud- och tidsfasen för 1PPS-signaler påverkas i urban canyons. Eftersom satellitgeometrin liknar den för antenner placerade på taket, så är identifieras flervägsutbredningen som huvudorsak för denna skillnad. Denna information är användbar när telekommunikationsföretag vill installera sina radiobasstationer i urban canyons. Det kommer att hjälpa Ericsson att förstå hur deras GNSS-timingmottagare arbetar och hur urban canyon påverkar dess prestanda.

Over the last ten years, Ultra-Wide Band (UWB) technology has attracted tremendous research attention. Frequency allocation of 3.1-10.6 GHz for UWB application by FCC made it apparent that UWB will be the technology for future wireless high speed communication applications. With the promise of high data rates (high channel capacity), UWB also offers advantages such as communication security, high multi-path resolution, good penetration capability, ability to coexist with other communication schemes in the same band, and finally, circuit simplicity. The theoretical advantages of UWB has made it a great candidate for short distance communications, however, UWB communications have many challenges, for example, sub-nanosecond pulse generation, timing sensitivity of modulation and synchronization, flat antenna performance over a wide bandwidth, effect of existing systems on UWB systems. In order to experiment with various UWB modulation schemes, and to study transmitter and receiver structures, an accurate channel model need be established. In this dissertation, our first contribution is to evaluate and implement two major statistical channel models. The first model is proposed by AT\&T Labs and is in the form of an autoregressive IIR filter. Although this is an accurate channel model to represent UWB behavior, it is proposed before the allocation of 3.1-10.6 GHz frequency band, hence, it could not simulate the correct frequency spectrum. The second model is proposed by Saleh and Valenzuela, which has been widely accepted by UWB community to be the most accurate channel model for UWB systems. Recently disbanded task group 802.15.3a which was assigned to standardize a UWB communication scheme has also accepted the latter model. Our second contribution is to derive optimal pulses for PPM signals. Using the accurate channel model in computer simulations, we experimented on various UWB communication schemes. We found that the traditional UWB pulses being used in pulse position modulated UWB systems did not perform optimally. A set of optimized UWB pulses and the methodology to calculate optimal pulses for any modulation index for PPM systems have been proposed in this dissertation. It is found that the optimal pulse can improve the performance of UWB systems by as much as 0.7 dB. With the PPM pulse optimization, the theoretical performance limits of PPM systems are derived. The third contribution from this dissertation is to design near optimal practical implementable receiver structures. Some of the results obtained from PPM pulse optimization are found to be theoretical and not practical. More practical approach to the receiver structures were needed for industrial interest. We proposed simple sub-optimal receiver structures that are able to perform only a few dB less than the optimal receivers are proposed. These simple, low-cost receiver structures are strong alternatives to the complex traditional optimal receivers.