Reduced Order Estimation of Time Varying Wireless Channels in Real Life Scattering Environment

This thesis deals with theoretical study and numerical simulation of 2x1 MISO system with Alamouti coding and imperfect channel estimation at the receiver. We adopt two channel models to represent scattering environment. One is Sum of Sinusoids model, which is simple, but does not properly reflect the geometry of scattering environment. The second model uses a set of Modulated Discrete Prolate Spheroidal Sequences to represent the channel in a scenario with scattering from one or more clusters with predefined geometry. The effect of clusters location on estimation quality is examined. Furthermore, we derive reduced complexity Wiener filters for slow flat fading channel estimation in pilot aided receiver. Our approach is based on the approximation of the channel covariance function to zero and second order Taylor series to reduce computational effort of the filter design. Theoretical MMSE is developed, verified through simulation and compared to one of a full Wiener filter

Channel modeling and resource allocation in OFDM systems

The increasing demand for high data rate in wireless communication systems gives rise to broadband communication systems. The radio channel is plagued by multipath propagation, which causes frequency-selective fading in broadband signals. Orthogonal Frequency-Division Multiplexing (OFDM) is a modulation scheme specifically designed to facilitate high-speed data transmission over frequency-selective fading channels. The problem of channel modeling in the frequency domain is first investigated for the wideband and ultra wideband wireless channels. The channel is converted into an equivalent discrete channel by uniformly sampling the continuous channel frequency response (CFR), which results in a discrete CFR. A necessary and sufficient condition is established for the existence of parametric models for the discrete CFR. Based on this condition, we provide a justification for the effectiveness of previously reported autoregressive (AR) models in the frequency domain of wideband and ultra wideband channels. Resource allocation based on channel state information (CSI) is known to be a very powerful method for improving the spectral efficiency of OFDM systems. Bit and power allocation algorithms have been discussed for both static channels, where perfect knowledge of CSI is assumed, and time-varying channels, where the knowledge of CSI is imperfect. In case of static channels, the optimal resource allocation for multiuser OFDM systems has been investigated. Novel algorithms are proposed for subcarrier allocation and bit-power allocation with considerably lower complexity than other schemes in the literature. For time-varying channel, the error in CSI due to channel variation is recognized as the main obstacle for achieving the full potential of resource allocation. Channel prediction is proposed to suppress errors in the CSI and new bit and power allocation schemes incorporating imperfect CSI are presented and their performance is evaluated through simulations. Finally, a maximum likelihood (ML) receiver for Multiband Keying (MBK) signals is discussed, where MBK is a modulation scheme proposed for ultra wideband systems (UWB). The receiver structure and the associated ML decision rule is derived through analysis. A suboptimal algorithm based on a depth-first tree search is introduced to significantly reduce the computational complexity of the receiver

Modeling and Prediction of Radio Channels for Orthogonal Frequency Division Multiplexing

In a wireless communication system, the channel is ever changing due to multipath properties such as excess delays and constructive and destructive interference. In a step to optimize system performance, it would be beneficial to have access to channel state information of both present subchannels' future development and subchannels outside the currently used frequency interval. In this thesis, radio channels for Orthogonal Frequency Division Multiplexing (OFDM) is concerned. Channels are modelled and a prediction algorithm appli-cable in time or frequency direction of the frequency response is developed. The algorithm derives an autoregressive (AR) model of the channel and exploits the close connection between prediction of a time discrete signal and an autoregres-sive process. The great over sampling at the receiver, compared to the maximum Doppler shift or maximum excess delay of the channel, yields it feasible to derive the model with decreased sampling rate and thus only use pilot symbols. This rate reduction gives longer accurate predictions but also an interpolation issue that is solved by Wiener filters. The mean performance of the approach is evaluated by calculating the root mean square error (RMSE) of predictions as functions of various channel and algorithm parameters. Simulations show that the algorithm is able to predict several coherence times or coherence bandwidths of a channel. The algorithm is also extended to use several OFDM symbols and an averaging finite impulse response (FIR) filter, yielding a considerable increase in prediction performance. It is also appraised as a tool for adaptive symbol mapping in a frequency interval not currently used. Results show an opportunity of substantially higher data throughput than for a mapping scheme based on the mean SNR of the channel

Doctor of Philosophy

dissertationThe demand for high speed communication has been increasing in the past two decades. Multicarrier communication technology has been suggested to address this demand. Orthogonal frequency-division multiplexing (OFDM) is the most widely used multicarrier technique. However, OFDM has a number of disadvantages in time-varying channels, multiple access, and cognitive radios. On the other hand, filterbank multicarrier (FBMC) communication has been suggested as an alternative to OFDM that can overcome the disadvantages of OFDM. In this dissertation, we investigate the application of filtered multitone (FMT), a subset of FBMC modulation methods, to slow fading and fast fading channels. We investigate the FMT transmitter and receiver in continuous and discrete time domains. An efficient implementation of FMT systems is derived and the conditions for perfect reconstruction in an FBMC communication system are presented. We derive equations for FMT in slow fading channels that allow evaluation of FMT when applied to mobile wireless communication systems. We consider using fractionally spaced per tone channel equalizers with different number of taps. The numerical results are presented to investigate the performance of these equalizers. The numerical results show that single-tap equalizers suffice for typical wireless channels. The equalizer design study is advanced by introducing adaptive equalizers which use channel estimation. We derive equations for a minimum mean square error (MMSE) channel estimator and improve the channel estimation by considering the finite duration of channel impulse response. The results of optimum equalizers (when channel is known perfectly) are compared with those of the adaptive equalizers, and it is found that a loss of 1 dB or less incurs. We also introduce a new form of FMT which is specially designed to handle doubly dispersive channels. This method is called FMT-dd (FMT for doubly dispersive channels). The proposed FMT-dd is applied to two common methods of data symbol orientation in the time-frequency space grid; namely, rectangular and hexagonal lattices. The performance of these methods along with OFDM and the conventional FMT are compared and a significant improvement in performance is observed. The FMT-dd design is applied to real-world underwater acoustic (UWA) communication channels. The experimental results from an at-sea experiment (ACOMM10) show that this new design provides a significant gain over OFDM. The feasibility of implementing a MIMO system for multicarrier UWA communication channels is studied through computer simulations. Our study emphasizes the bandwidth efficiency of multicarrier MIMO communications .We show that the value of MIMO to UWA communication is very limited

Energy-Efficient Distributed Estimation by Utilizing a Nonlinear Amplifier

abstract: Distributed estimation uses many inexpensive sensors to compose an accurate estimate of a given parameter. It is frequently implemented using wireless sensor networks. There have been several studies on optimizing power allocation in wireless sensor networks used for distributed estimation, the vast majority of which assume linear radio-frequency amplifiers. Linear amplifiers are inherently inefficient, so in this dissertation nonlinear amplifiers are examined to gain efficiency while operating distributed sensor networks. This research presents a method to boost efficiency by operating the amplifiers in the nonlinear region of operation. Operating amplifiers nonlinearly presents new challenges. First, nonlinear amplifier characteristics change across manufacturing process variation, temperature, operating voltage, and aging. Secondly, the equations conventionally used for estimators and performance expectations in linear amplify-and-forward systems fail. To compensate for the first challenge, predistortion is utilized not to linearize amplifiers but rather to force them to fit a common nonlinear limiting amplifier model close to the inherent amplifier performance. This minimizes the power impact and the training requirements for predistortion. Second, new estimators are required that account for transmitter nonlinearity. This research derives analytically and confirms via simulation new estimators and performance expectation equations for use in nonlinear distributed estimation. An additional complication when operating nonlinear amplifiers in a wireless environment is the influence of varied and potentially unknown channel gains. The impact of these varied gains and both measurement and channel noise sources on estimation performance are analyzed in this paper. Techniques for minimizing the estimate variance are developed. It is shown that optimizing transmitter power allocation to minimize estimate variance for the most-compressed parameter measurement is equivalent to the problem for linear sensors. Finally, a method for operating distributed estimation in a multipath environment is presented that is capable of developing robust estimates for a wide range of Rician K-factors. This dissertation demonstrates that implementing distributed estimation using nonlinear sensors can boost system efficiency and is compatible with existing techniques from the literature for boosting efficiency at the system level via sensor power allocation. Nonlinear transmitters work best when channel gains are known and channel noise and receiver noise levels are low.Dissertation/ThesisPh.D. Electrical Engineering 201

Interference suppression and parameter estimation in wireless communication systems over time-varing multipath fading channels

This dissertation focuses on providing solutions to two of the most important problems in wireless communication systems design, namely, 1) the interference suppression, and 2) the channel parameter estimation in wireless communication systems over time-varying multipath fading channels. We first study the interference suppression problem in various communication systems under a unified multirate transmultiplexer model. A state-space approach that achieves the optimal realizable equalization (suppression of inter-symbol interference) is proposed, where the Kalman filter is applied to obtain the minimum mean squared error estimate of the transmitted symbols. The properties of the optimal realizable equalizer are analyzed. Its relations with the conventional equalization methods are studied. We show that, although in general a Kalman filter has an infinite impulse response, the Kalman filter based decision-feedback equalizer (Kalman DFE) is a finite length filter. We also propose a novel successive interference cancellation (SIC) scheme to suppress the inter-channel interference encountered in multi-input multi-output systems. Based on spatial filtering theory, the SIC scheme is again converted to a Kalman filtering problem. Combining the Kalman DFE and the SIC scheme in series, the resultant two-stage receiver achieves optimal realizable interference suppression. Our results are the most general ever obtained, and can be applied to any linear channels that have a state-space realization, including time-invariant, time-varying, finite impulse response, and infinite impulse response channels. The second half of the dissertation devotes to the parameter estimation and tracking of single-input single-output time-varying multipath channels. We propose a novel method that can blindly estimate the channel second order statistics (SOS). We establish the channel SOS identifiability condition and propose novel precoder structures that guarantee the blind estimation of the channel SOS and achieve diversities. The estimated channel SOS can then be fit into a low order autoregressive (AR) model characterizing the time evolution of the channel impulse response. Based on this AR model, a new approach to time-varying multipath channel tracking is proposed

Channel Estimation Architectures for Mobile Reception in Emerging DVB Standards

Throughout this work, channel estimation techniques have been analyzed and proposed for moderate and very high mobility DVB (digital video broadcasting) receivers, focusing on the DVB-T2 (Digital Video Broadcasting - Terrestrial 2) framework and the forthcoming DVB-NGH (Digital Video Broadcasting - Next Generation Handheld) standard. Mobility support is one of the key features of these DVB specifications, which try to deal with the challenge of enabling HDTV (high definition television) delivery at high vehicular speed. In high-mobility scenarios, the channel response varies within an OFDM (orthogonal frequency-division multiplexing) block and the subcarriers are no longer orthogonal, which leads to the so-called ICI (inter-carrier interference), making the system performance drop severely. Therefore, in order to successfully decode the transmitted data, ICI-aware detectors are necessary and accurate CSI (channel state information), including the ICI terms, is required at the receiver. With the aim of reducing the number of parameters required for such channel estimation while ensuring accurate CSI, BEM (basis expansion model) techniques have been analyzed and proposed for the high-mobility DVB-T2 scenario. A suitable clustered pilot structure has been proposed and its performance has been compared to the pilot patterns proposed in the standard. Different reception schemes that effectively cancel ICI in combination with BEM channel estimation have been proposed, including a Turbo scheme that includes a BP (belief propagation) based ICI canceler, a soft-input decision-directed BEM channel estimator and the LDPC (low-density parity check) decoder. Numerical results have been presented for the most common channel models, showing that the proposed receiver schemes allow good reception, even in receivers with extremely high mobility (up to 0.5 of normalized Doppler frequency).Doktoretza tesi honetan, hainbat kanal estimazio teknika ezberdin aztertu eta proposatu dira mugikortasun ertain eta handiko DVB (Digital Video Broadcasting) hartzaileentzat, bigarren belaunaldiko Lurreko Telebista Digitalean DVB-T2 (Digital Video Broadcasting - Terrestrial 2 ) eta hurrengo DVB-NGH (Digital Video Broadcasting - Next Generation Handheld) estandarretan oinarrututa. Mugikortasuna bigarren belaunaldiko telebista estandarrean funtsezko ezaugarri bat da, HDTV (high definition television) zerbitzuak abiadura handiko hartzaileetan ahalbidetzeko erronkari aurre egiteko nahian. Baldintza horietan, kanala OFDM (ortogonalak maiztasun-zatiketa multiplexing ) sinbolo baten barruan aldatzen da, eta subportadorak jada ez dira ortogonalak, ICI-a (inter-carrier interference) sortuz, eta sistemaren errendimendua hondatuz. Beraz, transmititutako datuak behar bezala deskodeatzeko, ICI-a ekiditeko gai diren detektagailuak eta CSI-a (channel state information) zehatza, ICI osagaiak barne, ezinbestekoak egiten dira hartzailean. Kanalaren estimazio horretarako beharrezkoak diren parametro kopurua murrizteko eta aldi berean CSI zehatza bermatzeko, BEM (basis expansion model) teknika aztertu eta proposatu da ICI kanala identifikatzeko mugikortasun handiko DVB-T2 eszenatokitan. Horrez gain, pilotu egitura egokia proposatu da, estandarrean proposatutako pilotu ereduekin alderatuz BEM estimazioan oinarritua. ICI-a baliogabetzen duten hartzaile sistema ezberdin proposatu dira, Turbo sistema barne, non BP (belief propagation) detektagailua, soft BEM estimazioa eta LDPC (low-density parity check ) deskodetzailea uztartzen diren. Ohiko kanal ereduak erabilita, simulazio emaitzak aurkeztu dira, proposatutako hartzaile sistemak mugikortasun handiko kasuetan harrera ona dutela erakutsiz, 0.5 Doppler maiztasun normalizaturaino.Esta tesis doctoral analiza y propone diferentes técnicas de estimación de canal para receptores DVB (Digital Video Broadcasting) con movilidad moderada y alta, centrándose en el estándar de segunda generación DVB-T2 (Digital Video Broadcasting - Terrestrial 2 ) y en el próximó estándar DVB-NGH (Digital Video Broadcasting - Next Generation Handheld ). La movilidad es una de las principales claves de estas especificaciones, que tratan de lidiar con el reto de permitir la recepción de señal HDTV (high definition television) en receptores móviles. En escenarios de alta movilidad, la respuesta del canal varía dentro de un símbolo OFDM (orthogonal frequency-division multiplexing ) y las subportadoras ya no son ortogonales, lo que genera la llamada ICI (inter-carrier interference), deteriorando el rendimiento de los receptores severamente. Por lo tanto, con el fin de decodificar correctamente los datos transmitidos, detectores capaces de suprimir la ICI y una precisa CSI (channel state information), incluyendo los términos de ICI, son necesarios en el receptor. Con el objetivo de reducir el número de parámetros necesarios para dicha estimación de canal, y al mismo tiempo garantizar una CSI precisa, la técnica de estimación BEM (basis expansion model) ha sido analizada y propuesta para identificar el canal con ICI en receptores DVB-T2 de alta movilidad. Además se ha propuesto una estructura de pilotos basada en clústers, comparando su rendimiento con los patrones de pilotos establecidos en el estándar. Se han propuesto diferentes sistemas de recepción que cancelan ICI en combinación con la estimación BEM, incluyendo un esquema Turbo que incluye un detector BP (belief propagation), un estimador BEM soft y un decodificador LDPC (low-density parity check). Se han presentado resultados numéricos para los modelos de canal más comunes, demostrando que los sistemas de recepción propuestos permiten la decodificación correcta de la señal incluso en receptores con movilidad muy alta (hasta 0,5 de frecuencia de Doppler normalizada)