International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Data from ARTM channel sounding test flights is examined to characterize the dynamic channel behavior of aeronautical telemetry channels. The dynamic behavior is characterized using the Doppler power spectrum. The width of the Doppler power spectrum is the Doppler bandwidth of the channel which indicates the required bandwidth of adaptive detection techniques such as adaptive equalization, adaptive modulation, adaptive channel selection and adaptive error control coding. Data collected from ARTM Flight 11 suggest a Doppler bandwidth exceeding 6.7 Hz for the channel, but greater accuracy and resolution will only be possible with more data.

With the increasing demand for more wireless multimedia applications, it is desired to design a wireless system with higher data rate. Furthermore, the frequency spectrum has become a limited and valuable resource, making it necessary to utilize the available spectrum efficiently and coexist with other wireless systems. Orthogonal frequency division multiplexing (OFDM) modulation is widely used in communication systems to meet the demand for ever increasing data rates. The major advantage of OFDM over single-carrier transmission is its ability to deal with severe channel conditions without complex equalization. However, OFDM systems suffer from a high peak to average power ratio, and they are sensitive to carrier frequency offset and Doppler spread. This dissertation first focuses on the development of intercarrier interference (ICI) reduction and signal detection algorithms for OFDM systems over time-varying channels. Several ICI reduction algorithms are proposed for OFDM systems over doubly-selective channels. The OFDM ICI reduction problem over time-varying channels is formulated as a combinatorial optimization problem based on the maximum likelihood (ML) criterion. First, two relaxation methods are utilized to convert the ICI reduction problem into convex quadratic programming (QP) problems. Next, a low complexity ICI reduction algorithm applicable to $M$-QAM signal constellations for OFDM systems is proposed. This formulates the ICI reduction problem as a QP problem with non-convex constraints. A successive method is then utilized to deduce a sequence of reduced-size QP problems. For the proposed algorithms, the QP problems are solved by limiting the search in the 2-dimensional subspace spanned by its steepest-descent and Newton directions to reduce the computational complexity. Furthermore, a low-bit descent search (LBDS) is employed to improve the system performance. Performance results are given to demonstrate that the proposed ICI reduction algorithms provide excellent performance with reasonable computational complexity. A low complexity joint semiblind detection algorithm based on the channel correlation and noise variance is proposed which does not require channel state information. The detection problem is relaxed to a continuous non-convex quadratic programming problem. Then an iterative method is utilized to deduce a sequence of reduced-size quadratic programming problems. A LBDS method is also employed to improve the solution of the derived QP problems. Results are given which demonstrate that the proposed algorithm provides similar performance with lower computational complexity compared to that of a sphere decoder. A major challenge to OFDM systems is how to obtain accurate channel state information for coherent detection of the transmitted signals. Thus several channel estimation algorithms are proposed for OFDM systems over time-invariant channels. A channel estimation method is developed to utilize the noncircularity of the input signals to obtain an estimate of the channel coefficients. It takes advantage of the nonzero cyclostationary statistics of the transmitted signals, which in turn allows blind polynomial channel estimation using second-order statistics of the OFDM symbol. A set of polynomial equations are formulated based on the correlation of the received signal which can be used to obtain an estimate of the time domain channel coefficients. Performance results are presented which show that the proposed algorithm provides better performance than the least minimum mean-square error (LMMSE) algorithm at high signal to noise ratios (SNRs), with low computational complexity. Near-optimal performance can be achieved with large OFDM systems. Finally, a CS-based time-domain channel estimation method is presented for OFDM systems over sparse channels. The channel estimation problem under consideration is formulated as a small-scale $l_1$-minimization problem which is convex and admits fast and reliable solvers for the globally optimal solution. It is demonstrated that the magnitudes as well as delays of the significant taps of a sparse channel model can be estimated with satisfactory accuracy by using fewer pilot tones than the channel length. Moreover, it is shown that a fast Fourier transform (FFT) matrix of extended size can be used as a set of appropriate basis vectors to enhance the channel sparsity. This technique allows the proposed method to be applicable to less-sparse OFDM channels. In addition, a total-variation (TV) minimization based method is introduced to provide an alternative way to solve the original sparse channel estimation problem. The performance of the proposed method is compared to several established channel estimation algorithms. / Graduate

International Telemetering Conference Proceedings / October 23-26, 2000 / Town & Country Hotel and Conference Center, San Diego, California / Parameterized data from ARTM channel sounding test flights are used to derive a parameter-based estimate of the scattering function. The Doppler bandwidth and Doppler spread, important measures of channel dynamics, can be estimated from such a scattering function. Data collected from ARTM Flight 11 suggest that the Doppler bandwidth is larger than 6.7 Hz. Even for very small collections of parameterized data, surprising agreement is shown to non-parametric scattering function estimates. This confirms modeling assumptions and offers a way to achieve significant reductions of storage requirements.

"Many current and future medical devices are wearable, using the human body as a conduit for wireless communication, which implies that human body serves as a crucial part of the transmission medium in body area networks (BANs). Implantable medical devices such as Pacemaker and Cardiac Defibrillators are designed to provide patients with timely monitoring and treatment. Endoscopy capsules, pH Monitors and blood pressure sensors are used as clinical diagnostic tools to detect physiological abnormalities and replace traditional wired medical devices. Body-mounted sensors need to be investigated for use in providing a ubiquitous monitoring environment. In order to better design these medical devices, it is important to understand the propagation characteristics of channels for in-body and on- body wireless communication in BANs. The IEEE 802.15.6 Task Group 6 is officially working on the standardization of Body Area Network, including the channel modeling and communication protocol design. This thesis is focused on the propagation characteristics of human body movements. Specifically, standing, walking and jogging motions are measured, evaluated and analyzed using an empirical approach. Using a network analyzer, probabilistic models are derived for the communication links in the medical implant communication service band (MICS), the industrial scientific medical band (ISM) and the ultra- wideband (UWB) band. Statistical distributions of the received signal strength and second order statistics are presented to evaluate the link quality and outage performance for on-body to on- body communications at different antenna separations. The Normal distribution, Gamma distribution, Rayleigh distribution, Weibull distribution, Nakagami-m distribution, and Lognormal distribution are considered as potential models to describe the observed variation of received signal strength. Doppler spread in the frequency domain and coherence time in the time domain from temporal variations is analyzed to characterize the stability of the channels induced by human body movements. The shape of the Doppler spread spectrum is also investigated to describe the relationship of the power and frequency in the frequency domain. All these channel characteristics could be used in the design of communication protocols in BANs, as well as providing features to classify different human body activities. Realistic data extracted from built-in sensors in smart devices were used to assist in modeling and classification of human body movements along with the RF sensors. Variance, energy and frequency domain entropy of the data collected from accelerometer and orientation sensors are pre- processed as features to be used in machine learning algorithms. Activity classifiers with Backpropagation Network, Probabilistic Neural Network, k-Nearest Neighbor algorithm and Support Vector Machine are discussed and evaluated as means to discriminate human body motions. The detection accuracy can be improved with both RF and inertial sensors."

In cellular communication systems, the estimation of Doppler spread has a wide range of applications such as handoff, channel assignment scheme, adaptivetransmission, power control, etc. A great quantity of Doppler spread estimation algorithms have been proposed in the literature. But there has been few investigations which gives a comprehensive comparison of these algorithms. Therefore, it is of great signicance to compare and evaluate the performance of the existing algorithms in the same simulation framework. In this report, the uplink of WCDMA is considered. Four different types of Doppler spread estimation algorithms are evaluated and compared in a link level baseband simulator. The performance and the ability to implement are considered as the metrics for evaluation. Both Rayleigh and Rician fading channel model are applied, and the effect of speed, signal to noise ratio, Rician factor and the angle of arrived line of sight component are also tested. Moreover, the computational complexity is analysed to evaluate the practical value for implementation. / Estimatering av en mobils hastighet i form av Dopplerspridning har ett brett spektrum av tillmpningar i cellulra kommunikationssystem ssom fr yttningen avmobiler mellan celler, kanaltilldelningsschema, adaptiv sndning, eektstyrning,etc. En stor mngd algoritmer fr estimering av Dopplerspriding har frslagitsi litteraturen, men det r ovanligt med heltckande jmfrelser mellan med dessaalgoritmer. Drfr r det av stor betydelse att jmfra och utvrdera resultaten avbentliga algoritmer inom ramen fr samma simuleringsvertyg.I denna rapport anvnds upplnken fr WCDMA fr utvrdering av fyra olikatyper av algoritmer fr estimering av Dopplerspridning. Metriker fr utvrderingenr prestanda och implementeringsvnlighet. Bde Rayleigh och Rician fdningskanalmodeller har utvrderas, samt eekten av mobilens hastighet, signaltill brus frhllande, Rician faktor och infallsvinkel i ppet flt scenario. Dessutomhar den berkningsmssiga komplexiteten analyseras fr att utvrdera den praktiskaanvndbarheten i riktiga system.

This thesis aims to contribute to the developments of wireless communication systems. The work generally consists of three parts: the first part is a discussion on general digital communication systems, the second part focuses on wireless channel modelling and fading mitigation techniques, and in the third part we discuss the possible application of advanced digital signal processing, especially time-frequency representation and blind source separation, to wireless communication systems. The first part considers general digital communication systems which will be incorporated in later parts. Today's wireless communication system is a subbranch of a general digital communication system that employs various techniques of A/D (Analog to Digital) conversion, source coding, error correction, coding, modulation, and synchronization, signal detection in noise, channel estimation, and equalization. We study and develop the digital communication algorithms to enhance the performance of wireless communication systems. In the Second Part we focus on wireless channel modelling and fading mitigation techniques. A modified Jakes' method is developed for Rayleigh fading channels. We investigate the level-crossing rate (LCR), the average duration of fades (ADF), the probability density function (PDF), the cumulative distribution function (CDF) and the autocorrelation functions (ACF) of this model. The simulated results are verified against the analytical Clarke's channel model. We also construct frequency-selective geometrical-based hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment with the proper statistical characteristics. The modified Clarke's model and the GBHDS model may be readily expanded to a MIMO channel model thus we study the MIMO fading channel, specifically we model the MIMO channel in the angular domain. A detailed analysis of Gauss-Markov approximation of the fading channel is also given. Two fading mitigation techniques are investigated: Orthogonal Frequency Division Multiplexing (OFDM) and spatial diversity. In the Third Part, we devote ourselves to the exciting fields of Time-Frequency Analysis and Blind Source Separation and investigate the application of these powerful Digital Signal Processing (DSP) tools to improve the performance of wireless communication systems.