Due to wealth of advantages offered by short range ultra wideband (UWB) technology, such as capacity improvement, fading reduction and localization, it has gathered a considerable attention. Distinct UWB qualities also pose many system design challenges like difficulties in using digital processing, complex channel estimation and different propagation characteristics. The main objective of the thesis is to develop and evaluate efficient modulation and detection schemes for impulse radio (IR) UWB with a focus on wireless sensor networks characterized by low cost and low power consumption. The content of the thesis comprises of five parts. In Part I, a coherent RAKE and non-coherent energy detector (ED) and transmitted reference (TR) receivers are examined and their bit-error-rate (BER) performance is evaluated using channels measured in an industrial environment. In specific, selective RAKE (SRake) and partial RAKE (PRake) for both maximal ratio combining (MRC) and equal gain combining (EGC) are compared. Based on the analysis and simulation results, it is concluded the SRake with EGC is to be preferred, whereas the best complexity/performance trade-off is provided by the ED based receivers. Part II presents several signaling and detection schemes; the proposed schemes are recursive TR (R-TR), dual-doublet TR (DDTR), doublet-shift TR (DSTR) and binary pulse position modulation (BPPM)/DSTR. Analysis and simulations verify that the proposed schemes may be preferred over the conventional TR in terms of BER, energy efficiency and/or implementation complexity. Part III presents a non-coherent kurtosis detector (KD) and a fourth-order detector (FD), which can discriminate between Gaussian noise and non-Gaussian IR-UWB signals by directly estimating the fourth-order moment of the received signal. Empirical evaluations and simulations using channel measurements conducted in a corridor, an office and a laboratory environment verify that performance of the proposed FD receiver is slightly better than the ED in the low SNR region and its performance improves as the SNR increases. Part IV presents a robust weighted ED (WED) in which the weighting coefficients are estimated adaptively based on the received stochastic data. Simulation results confirm that performance of the proposed weight estimation method is close to that of a data-aided (DA) scheme. Finally, Part V focuses on a multi-user scenario and develops a weighted code-multiplexed TR (WCM-TR) receiver employing the robust adaptive weight estimation scheme. Secondly, a BPPM/CM-TR UWB system is presented to mitigate inter-frame interference (IFI) and multi-user interference (MUI) from other asynchronous users. The BPPM/CM-TR system is 3 dB energy-efficient and improves the BER performance by mitigating MUI/IFI in the high SNR region, while for the low SNR case and single-user scenario, a dual-mode BPPM/CM-TR system is suggested

Wireless sensor networks have attracted the interest of the process industry. A process plant typically contains thousands of devices, monitoring or controlling the process. Today, all these devices are usually connected with wires. Using wireless technology simplifies deployment of new devices in a network and eliminates the need for extensive wiring. But wireless communication is also more sensitive than its wired counterpart. Therefore work is needed to make wireless sensor networks a viable option in many applications. Important issues are, for example, robustness, energy efficiency, and latency. One of the leading communication protocols for industrial wireless sensor networks is the WirelessHART protocol. This thesis investigates three ways of improving performance of the protocol, in terms of reliability and energy requirements. First, the structure of a WirelessHART packet is studied and the removal of certain fields is suggested to make the communication overhead smaller. Second, forward error correcting codes are evaluated using simulations in MATLAB. Third, measurement experiments in actual industrial environments are conducted where radio signals are transmitted and received. The variability of the received signal strength is measured and the effect that polarization diversity has on the signal variability is analyzed. The findings indicate that substantial improvements can be attained by employing polarization diversity, which can reduce channel variability and increase the expected signal strength significantly. The improvements in channel gain can be on the order of several tens of dB. The evaluations of forward error correcting codes show that the reliability is improved, with a channel gain of 3 dB. The study of the WirelessHART packet structure indicate that the packet sizes can be reduced by 15%. In turn, this also reduces energy requirements and packet error rates by 15%. This is equivalent to a gain in SNR on the order of a tenth of a dB.

Smart antenna is a potential performance enhancement tool in a communications link that can be used at either end (transmitter or receiver) of the link in the form of beamforming or diversity operation. While receive smart antenna techniques and operations have matured over the years, transmit smart antenna is relatively a new concept that has seen its growth over the past few years. Both these smart antenna operations have been traditionally designed for base station applications. But with the advent of high-speed processors, transmit smart antenna can also be feasible at a small wireless terminal (SWT). This dissertation studied the feasibility of using smart antenna at a SWT. Both smart transmit and receive antennas are studied, including multiple input and multiple output (MIMO) systems, however the emphasis is placed on transmit smart antennas. The study includes algorithm developments and performance evaluations in both flat fading and frequency selective channels. Practical issues, i.e., latency and amount of feedback, related to transmit smart antenna operation are discussed. Various channel measurements are presented to assess the performance of a transmit smart antenna in a real propagation environment. These include vector channel measurements for narrowband and wideband signals, channel reciprocity, and effect of antenna element spacing on diversity performance. Real-time demonstrations of transmit smart antenna have been performed and presented, and, the applicability of the proposed techniques in the Third Generation standards and wireless local area networks (WLAN) is discussed. Receive beamforming with a small number of antenna elements (which is usually the case for a SWT) is analyzed in an interference-limited environment. / Ph. D.

<p>In recent years, multiple-input multiple-output (MIMO)systems appear to be very promising since they can provide highdata rates in environments with sucient scattering byexploiting the spatial domain. To design a real MIMO wirelesssystem and predict its performance under certain circumstances,it is necessary to have accurate MIMO wireless channel modelsfor dierent scenarios. This thesis presents dierent models forindoor MIMO radio propagation channels based on 5.2 GHz indoorMIMO channel measurements.The recent research on MIMO radio channel modeling isbriey reviewed in this thesis. The models are categorized intonon-physical and physical models. The non-physical modelsprimarily rely on the statistical characteristics of MIMOchannels obtained from the measured data while the physicalmodels describe the MIMO channel (or its distribution) via somephysical parameters. The relationships between dierent modelsare also discussed.For the narrowband case, a non line-of-sight (NLOS)indoor MIMO channel model is presented. The model is based on aKronecker structure of the channel covariance matrix and thefact that the channel is complex Gaussian. It is extended tothe line-of-sight (LOS) scenario by estimating and modeling thedominant component separately.As for the wideband case, two NLOS MIMO channel modelsare proposed. The rst model uses the power delay prole and theKronecker structure of the second order moments of each channeltap to model the wideband MIMO channel while the second modelcombines a simple single-input single-output (SISO) model withthe same Kronecker structure of the second order moments.Monte-Carlo simulations are used to generate indoor MIMOchannel realizations according to the above models. The resultsare compared with the measured data and good agreement has beenobserved.</p>

Millimeter wave (mm-Wave) systems have become very attractive recently as lower frequency spectrums used for mobile device communications have been experiencing a “spectral crunch” due to the dissemination of smartphones. Channel characterization of the outdoor urban environment, where networks for mobile devices require the highest data capacity, has been quite scarce and even non-existent for cellular (rooftop to ground) setting measurements. Our project characterizes the urban environment at 38 GHz in a cellular setting and 38 and 60 GHz in a peer-to-peer setting. A sliding correlator channel sounder with an 800 MHz RF bandwidth at 38 GHz and 1.5 GHz RF bandwidth at 60 GHz was constructed to measure the channel using a bandwidth that is larger than the expected bandwidths of future mm-Wave channels. Directional antennas were utilized during the measurements to imitate mm-Wave systems using beam steering antenna arrays, which also allowed for AOA characterization. Path loss and RMS delay spread statistics are provided. Finally, an outage study was performed to test the outage likelihood in an urban environment with many multi-story buildings. / text

In recent years, multiple-input multiple-output (MIMO)systems appear to be very promising since they can provide highdata rates in environments with sucient scattering byexploiting the spatial domain. To design a real MIMO wirelesssystem and predict its performance under certain circumstances,it is necessary to have accurate MIMO wireless channel modelsfor dierent scenarios. This thesis presents dierent models forindoor MIMO radio propagation channels based on 5.2 GHz indoorMIMO channel measurements.The recent research on MIMO radio channel modeling isbriey reviewed in this thesis. The models are categorized intonon-physical and physical models. The non-physical modelsprimarily rely on the statistical characteristics of MIMOchannels obtained from the measured data while the physicalmodels describe the MIMO channel (or its distribution) via somephysical parameters. The relationships between dierent modelsare also discussed.For the narrowband case, a non line-of-sight (NLOS)indoor MIMO channel model is presented. The model is based on aKronecker structure of the channel covariance matrix and thefact that the channel is complex Gaussian. It is extended tothe line-of-sight (LOS) scenario by estimating and modeling thedominant component separately.As for the wideband case, two NLOS MIMO channel modelsare proposed. The rst model uses the power delay prole and theKronecker structure of the second order moments of each channeltap to model the wideband MIMO channel while the second modelcombines a simple single-input single-output (SISO) model withthe same Kronecker structure of the second order moments.Monte-Carlo simulations are used to generate indoor MIMOchannel realizations according to the above models. The resultsare compared with the measured data and good agreement has beenobserved. / <p>NR 20140805</p>

<div>Millimeter-wave (mmWave) bands have become the most promising candidate for enlarging the usable radio spectrum in future wireless networks such as 5G. Since frequent and location-specific blockages are expected for mmWaves, the challenge is understanding the propagation characteristics of mmWave signals and accordingly predicting the channel state information. This research direction has garnered great attention worldwide from industry, academia, and government. However, the majority of current research on mmWave communications has focused on urban areas with high population densities, with very few measurement campaigns in suburban and rural environments. These environments are extremely important for future wireless applications in areas including residential welfare, digital agriculture, and transportation. To fill in this research gap, we developed broadband mmWave channel sounding systems and carried out intensive measurement campaigns at 28 GHz, covering clear line-of-sight as well as non-line-of-sight scenarios over buildings and foliage clutters, to fully characterize the mmWave propagation in suburban and rural environments.</div><div><br></div><div>Moreover, the accuracy provided by traditional statistical models is insufficient for next-generation wireless networks with higher-frequency carriers, because they are unable to predict abrupt channel changes caused by site-specific blockages. To overcome this issue, we explored the possibility of utilizing site-specific geographic features such as buildings and trees in improving mmWave propagation models. A new channel modeling methodology highlighting site-specific parameter evaluation based on easily obtainable data sources (e.g., LiDAR) was proposed for accurate, fast, and automated channel state predictions. Accordingly, an overall root mean square error (RMSE) improvement of 11.79 dB was achieved in a one-building blockage scenario and a regional RMSE improvement of over 20 dB was observed in a coniferous forest. This approach also enables channel simulations for large-scale system performance evaluation, demonstrating a powerful and promising approach for planning and tuning future wide-area wireless networks. The simulation results showed that network densification alone is not enough for closing the digital gap, especially with mmWaves because of the impractical number of required towers. They also backed up supplementary solutions including private data relays, e.g., via drones and portable towers.</div>

Multiple-Input, Multiple-Output (MIMO) processing techniques for wireless communication are of interest for next-generation systems because of their potential to dramatically improve capacity in some propagation environments. When used in applications such as wireless LAN and cellular telephony, the MIMO processing methods must be adapted for the situation where a base station is communicating with many users simultaneously. This dissertation focuses on the downlink of such a channel, where the base station and all of the users have antenna arrays. If the transmitter has advance knowledge of the users' channel transfer functions, it can use that information to minimize the interuser interference due to the signals that are simultaneously transmitted to other users. If the transmitter assumes that all receivers treat the interference as noise, finding a solution that optimizes the use of resources is very difficult. This work proposes two classes of solutions to this problem. First, by forcing some or all of the interference to zero, it is possible to achieve a sub-optimal solution in closed-form. Second, a class of iterative solutions can be derived by extending optimal algorithms for multi-user downlink beamforming to accommodate receivers with multiple antennas. The closed-form solutions generally require less computation, but the iterative solutions offer improved performance are more robust to channel estimation errors, and thus may be more useful in practical applications. The performance of these algorithms were tested under realistic channel conditions by testing them on channels derived from both measurement data and a statistical model of an indoor propagation environment. These tests demonstrated both the ability of the channel to support multiple users, and the expected amount of channel estimation error due to movement of the users, with promising results. The success of any multi-user MIMO processing algorithm is ultimately dependent on the degree of correlation between the users' channels. If a base station is required to support a large number of users, one way to ensure minimal correlation between users' channels is to select groups of users whose channels are most compatible. The globally optimal solution to this problem is not possible without an exhaustive search, so a channel allocation algorithm is proposed that attempts to intelligently select groups of users at a more reasonable computational cost.

This thesis presents the experimental results on the formation of flow separation from a rigid wall with a salient edge. In the case of automotive vehicles or aircrafts with rear cargo compartment doors, such salient edges are at the origin of separated wake flows resulting in increased drag and other disturbing effects. Recent studies of Ahmed et al. (1984) on simplified geometries showed the strong influence of the slant angle on the flow separations. In this study, the geometry is further simplified to examine the flow separation under two-dimensional conditions. The experimental configuration consists of a fixed horizontal front panel and an attached rear panel with variable slant angle. The experiments were carried out in a low speed water channel to analyze the flow structure by flow visualization techniques. The hydrogen bubble technique nd PIV measurements are used to obtain both qualitative and quantitative information on the flow structure. The electrolytic precipitation technique is used to analyze the flow separation in more detail. The slant angle varied between 0 and 35 degrees while the Reynolds numbers of the model was fixed to 24800 and 50500. As a function of slant angle and Reynolds number, two different types of flow separation were observed: boundary layer separation due to adverse pressure gradient and the so called &ldquo / inertial separation&rdquo / at the edge singularity. Future strategies to control the formation of the wake flow highly depend on the very different flow structure of these two types of separation.

This research focuses on radio wave propagation at millimeter-wave frequencies. A measurement based channel characterization approach is taken in the investigation. First, measurement techniques are analyzed. Three types of measurement systems are designed, and implemented in measurement campaigns: a narrowband measurement system, a wideband measurement system based on Vector Network Analyzer, and sliding correlator systems at 5.8+AH4AXA-mbox{GHz}, 38+AH4AXA-mbox{GHz} and 60+AH4AXA-mbox{GHz}. The performances of these measurement systems are carefully compared both analytically and experimentally. Next, radio wave propagation research is performed at 38+AH4AXA-mbox{GHz} for Local Multipoint Distribution Services (LMDS). Wideband measurements are taken on three cross-campus links at Virginia Tech. The goal is to determine weather effects on the wideband channel properties. The measurement results include multipath dispersion, short-term variation and signal attenuation under different weather conditions. A design technique is developed to estimate multipath characteristics based on antenna patterns and site-specific information. Finally, indoor propagation channels at 60+AH4AXA-mbox{GHz} are studied for Next Generation Internet (NGI) applications. The research mainly focuses on the characterization of space-time channel structure. Multipath components are resolved both in time of arrival (TOA) and angle of arrival (AOA). Results show an excellent correlation between the propagation environments and the channel multipath structure. The measurement results and models provide not only guidelines for wireless system design and installation, but also great insights in millimeter-wave propagation. / Ph. D.