Proactive and nondisruptive channel probing is investigated for the measurement of channel power, amplifier channel gain, and optical signal-to-noise ratio (OSNR) without disrupting established wavelength-division multiplexed channels. Using a nondisruptive probe signal over a three-span link, wavelength switching-induced power excursions are predicted to be within +/- 0.2 dB, and OSNR as high as 20 dB is accurately measured with a maximum of 0.5 dB error.

The aim of the thesis is to find out the most suitable channel estimation algorithms for the existing MIMO-OFDM SDR platform. Starting with the analysis of several prevalent channel estimation algorithms, MSE performance are compared under different scenarios. As a result of the hardware independent analysis, the complexvalued matrix computations involved in the algorithms are decomposed to real FLoating-point OPerations (FLOPs). Four feasible algorithms are selected for hardware dependent discussion based on the proposed hardware architecture. The computational latency is exposed as a manner of case study.

Next generation wireless systems will support higher data rates, improved spectral efficiency, and less latency. Massive multiple-input multiple-output (MIMO) is proposed to satisfy these demands. In massive MIMO, many benefits come from employing hundreds of antennas at the base station (BS) and serving dozens of user terminals (UTs) per cell. As the number of antennas increases at the BS, the channel becomes sparse. By exploiting sparse channel in massive MIMO, compressive sensing (CS) methods can be implemented to estimate the channel. In CS methods, the length of pilot sequences can be shortened compared to pilot-based methods. In this paper, a novel channel estimation algorithm based on a CS method called elastic net is proposed. Channel estimation accuracy of pilot-based, lasso, and elastic-net based methods in massive MIMO are compared. It is shown that the elastic-net based method gives the best performance in terms of error for the less pilot symbols and SNR values.

Abstract Advanced receiver structures capable of suppressing multiple-access interference in code-division multiple-access (CDMA) systems operating in frequency-selective fading channels are considered in this thesis. The aim of the thesis is to develop and validate novel receiver concepts suitable for future wideband cellular CDMA systems. Data detection and synchronization both for downlink and uplink receivers are studied. The linear minimum mean squared error (LMMSE) receivers are derived and analyzed in frequency-selective fading channels. Different versions of the LMMSE receivers are shown to be suitable for different data rates. The precombining LMMSE receiver, whichis also suitable for relatively fast fading channels, is shown to improve the performance of the conventional RAKE receivers signicantly in the FRAMES wideband CDMA concept. It is observed that the performance of the conventional RAKE receivers is degraded signicantly with highest data rates due to multiple-access interference (MAI) as well as due to inter-path interference. Based on a general convergence analysis, it is observed that the postcombining LMMSE receivers are mainly suited to the high data rate indoor systems. The blind adaptive LMMSE-RAKE receiverdeveloped for relatively fast fading frequency-selective channels gives superior rate of convergence and bit error rate (BER) performance in comparison to other blind adaptive receivers based on least mean squares algorithms. The minimum variance method based delay estimation in blind adaptive receivers is shown to result in improved delay acquisition performance in comparison to the conventional matched filter and subspace based acquisition schemes. A novel delay tracking algorithm suitable to blind least squares receivers is also proposed. The analysis shows improved tracking performance in comparison to the standard delay-locked loops. Parallel interference cancellation (PIC) receivers are developed for the uplink. Data detection, channel estimation, delay acquisition, delay tracking, inter-cell interference suppression, and array processing in PIC receivers are considered. A multistage data detector with the tentative data decision and the channel estimate feedback from the last stage is developed. Adaptive channel estimation filters are used to improve the channel estimation accuracy. The PIC method is also applied to the timing synchronization of the receiver. It is shown that the PIC based delay acquisition and tracking methods can be used to improve the performance of the conventional synchronization schemes. Although the overall performance of the PIC receiver is relatively good in the single-cell case, its performance is signicantly degraded in a multi-cell environment due to unknown signal components which degrade the MAI estimates and subsequently the cancellation efficiency. The blind receiver concepts developed for the downlink are integrated into the PIC receivers for inter-cell interference suppression. The resulting LMMSE-PIC receiver is capable of suppressing residual interference and results in good BER performance in the presence of unknown signal components.

This thesis focused on testing whether persistent encryption of Fibre Channel is doable and what kind of security it provides. It has been shown that intercepting, analysing and modifying Fibre Channel traffic is possible without any noticeable performance loss as long as latency is kept within certain boundaries. If latency are outside those boundaries extreme performance loss are to be expected. This latency demand puts further restrictions on the cryptography to be used. Two platforms were simulated, implemented and explained. One for intercepting and modifying Fibre Channel and one for analysing Fibre Channel traffic using Linux and Wireshark.

Chemical reactions involving small number of reacting molecules are noisy processes. They are simulated using stochastic simulation algorithms like the Gillespie SSA, which are valid when the reaction environment is well-mixed. This is not the case in reactions occuring on biological media like cell membranes, where alternative simulation methods have to be used to account for the crowded nature of the reacting environment. Ion channels, which are membrane proteins controlling the flow of ions into and out of the cell, offer excellent single molecule conditions to test stochastic simulation schemes in crowded biological media. Single molecule reactions are of great importance in determining the functions of biological molecules. Access to their experimental data have increased the scope of com-putational modeling of biological processes. Recently, single molecule experiments have revealed the non-Markovian nature of chemical reactions, due to a phenomenon called `dynamic disorder', which makes the rate constants a deterministic function of time or a random process. This happens when there are additional slow scale conformational transitions, giving the molecule a memory of its previous states. In a previous work, the hTREK1 two pore domain potassium channel was revealed to have long term memory in its kinetics, prompting alternate non-Markovian schemes to analyze its gating. Traditionally, ion channel gating is modeled as Markovian transitions between fixed states. In this work, we have used single channel data from hTREK1 ion channel and have provided a simple diffusion model for its gating. The main assumption of this model is that the ion channel diffuses through a continuum of states on its potential energy landscape, which is derived from the steady state probability distribution of ionic current recorded from patch clamp experiments. A stochastic differential equation (SDE) driven by Gaussian white noise is proposed to model this motion in an asymmetric double well potential. The method is computationally very simple and efficient and reproduces the amplitude histogram very well. For the case when ligands are added, leading to incorporation of long term memory in the kinetics, the SDE is modified to run on coloured noise. This has been done by introducing an auxiliary variable into the equation. It has been shown that increasing the noise correlation with ligand concentration improves the fits to the experimental data. This has been validated for several datasets. These methods are more advantageous for simulation than the Markovian models as they are true to the physical picture of gating and also computationally very efficient. Reproducing the whole raw data trace takes no more than a few seconds with our scheme, with the only input being the amplitude histogram and four parameters. Finally a quantitative model based on a modified version of the Chemical Langevin equation is given, which works on random rate parameters. This model is computationally simple to implement and reproduces the catalytic activity of the channel as a function of time. From the computational analysis undertaken in this work, we can infer that ion channel activity can be modeled using the framework of non-Markovian processes, lending credence to the recent understanding that single molecule reactions are basically processes with long-term memory. Since the ion channel is basically a protein, we can also hypothesize that the some of the properties that make proteins so vital to living organ-isms could be attributed to long-term memory in their folding kinetics, giving them the ability to sample specific regions of their conformation space, which are of interest to biological functions.

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第15344号 / 工博第3223号 / 新制||工||1485(附属図書館) / 27822 / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 細田 尚, 教授 後藤 仁志, 准教授 米山 望 / 学位規則第4条第1項該当

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第15408号 / 工博第3287号 / 新制||工||1495(附属図書館) / 27886 / 京都大学大学院工学研究科合成・生物化学専攻 / (主査)教授 森 泰生, 教授 濵地 格, 教授 跡見 晴幸 / 学位規則第4条第1項該当

Abstract The multiple–input multiple–output (MIMO) technique, applying several transmit and receive antennas in wireless communications, has emerged as one of the most prominent technical breakthroughs of the last decade. Wideband MIMO parameter estimation and its applications to the MIMO orthogonal frequency division multiplexing (MIMO–OFDM) channel estimation and mobile positioning are studied in this thesis. Two practical MIMO channel models, i.e., correlated-receive independent-transmit channel and correlated-transmit-receive channel, and associated space-time parameter estimation algorithms are considered. Thanks to the specified structure of the proposed training signals for multiple transmit antennas, the iterative quadrature maximum likelihood (IQML) algorithm is applied to estimate the time delay and spatial signature for the correlated-receive independent-transmit MIMO channels. For the correlated-transmit-receive MIMO channels, the spatial signature matrix corresponding to a time delay can be further decomposed in such a way that the angle of arrival (AOA) and the angle of departure (AOD) can be estimated simultaneously by the 2-D unitary ESPRIT algorithm. Therefore, the combination of the IQML algorithm and the 2-D unitary ESPRIT algorithm provides a novel solution to jointly estimate the time delay, the AOA and the AOD for the correlated-transmit-receive MIMO channels. It is demonstrated from the numerical examples that the proposed algorithms can obtain good performance at a reasonable cost. Considering the correlated-receive independent-transmit MIMO channels, channel coefficient estimation for the MIMO–OFDM system is studied. Based on the parameters of the correlated-receive independent-transmit MIMO channels, the channel statistics in terms of the correlation matrix are developed. By virtue of the derived channel statistics, a joint spatial-temporal (JST) filtering based MMSE channel estimator is proposed which takes full advantage of the channel correlation properties. The mean square error (MSE) of the proposed channel estimator is analyzed, and its performance is also demonstrated by Monte Carlo computer simulations. It is shown that the proposed JST minimum mean square error (MMSE) channel estimator outperforms the more conventional temporal MMSE channel estimator in terms of the MSE when the signals in the receive antenna array elements are significantly correlated. The closed form bit error probability of the space-time block coded OFDM system with correlation at the receiver is also developed by taking the channel estimation errors and channel statistics, i.e., correlation at the receiver, into account. Mobile positioning in the non-line of sight (NLOS) scenarios is studied. With the knowledge of the time delay, the AOA and the AOD associated with each NLOS propagation path, a novel geometric approach is proposed to calculate the MS's position by only exploiting two NLOS paths. On top of this, the least squares and the maximum likelihood (ML) algorithms are developed to utilize multiple NLOS paths to improve the positioning accuracy. Moreover, the ML algorithm is able to estimate the scatterers' positions as well as those of the MSs. The Cramer-Rao lower bound related to the position estimation in the NLOS scenarios is derived. It is shown both analytically and through computer simulations that the proposed algorithms are able to estimate the mobile position only by employing the NLOS paths.

Abstract The problem of receiving direct sequence (DS) spread spectrum, binary phase shift keyed (BPSK) information in pulsed noise and continuous wave (CW) jamming is studied in additive white noise. An automatic gain control is not modelled. The general system theory of receiver analysis is first presented and previous literature is reviewed. The study treats the problem of decision making after matched filter or integrate and dump demodulation. The decision methods have a great effect on system performance with pulsed jamming. The following receivers are compared: hard, soft, quantized soft, signal level based erasure, and chip combiner receivers. The analysis is done using a channel parameter D, and bit error upper bound. Simulations were done in original papers using a convolutionally coded DS/BPSK system. The simulations confirm that analytical results are valid. Final conclusions are based on analytical results. The analysis is done using a Chernoff upper bound and a union bound. The analysis is presented with pulsed noise and CW jamming. The same kinds of methods can also be used to analyse other jamming signals. The receivers are compared under pulsed noise and CW jamming along with white gaussian noise. The results show that noise jamming is more harmful than CW jamming and that a jammer should use a high pulse duty factor. If the jammer cannot optimise a pulse duty factor, a good robust choice is to use continuous time jamming. The best performance was achieved by the use of the chip combiner receiver. Just slightly worse was the quantized soft and signal level based erasure receivers. The hard decision receiver was clearly worse. The soft decision receiver without jammer state information was shown to be the most vulnerable to pulsed jamming. The chip combiner receiver is 3 dB worse than an optimum receiver (the soft decision receiver with perfect channel state information). If a simple implementation is required, the hard decision receiver should be used. If moderate complex implementation is allowed, the quantized soft decision receiver should be used. The signal level based erasure receiver does not give any remarkable improvement, so that it is not worth using, because it is more complex to implement. If receiver complexity is not limiting factor, the chip combiner receiver should be used. Uncoded DS/BPSK systems are vulnerable to jamming and a channel coding is an essential part of antijam communication system. Detecting the jamming and erasing jammed symbols in a channel decoder can remove the effect of pulsed jamming. The realization of erasure receivers is rather easy using current integrated circuit technology.