Ultrawideband (UWB) is one of the promising technologies for future short-range high data rate communications (e.g. for wireless personal area networks) and longer range low data rate communications (e.g. wireless sensor networks).Despite its various advantages and potentials (e.g. low-cost circuitry, unlicensed reuse of licensed spectrum, precision ranging capability etc.), UWB also has its own challenges. The goal of this dissertation is to identify and address some of those challenges, and provide a framework for practical UWB transceiver design.In this dissertation, various modulation options for UWB systems are reviewed in terms of their bit error rate (BER) performances, spectral characteristics, modem and hardware complexities, and data rates. Time hopping (TH) code designs for both synchronous (introduced an adaptive code assignment technique) and asynchronous UWB impulse radio (IR) systems are studied. An adaptive assignment of two different multiple access parame ters (number of pulses per symbol and number of pulse positions per frame)is investigated again considering both synchronous and asynchronous scenarios, and a mathematical framework is developed using Gaussian approximations of interference statistics for different scenarios. Channel estimation algorithms for multiuser UWB communication systems using symbol-spaced (proposed a technique that decreases the training size), frame-spaced (proposed a pulse-discarding algorithm for enhanced estimationperformance), and chip-spaced (using least squares (LS) estimation) sampling are analyzed.A comprehensive review on multiple accessing andinterference avoidance/cancellation for IR-UWB systems is presented.BER performances of different UWB modulation schemes in the presence of timing jitter are evaluated and compared in static and multipath fading channels, and finger estimation error, effects of jitter distribution, and effects of pulse shape are investigated. A unified performance analysis app roach for different IR-UWB transceiver types (stored-reference, transmitted-reference, and energy detector) employing various modulation options and operating at sub-Nyquist sampling rates is presented. The time-of-arrival (TOA) estimation performance of different searchback schemesunder optimal and suboptimal threshold settings are analyzed both for additive white Gaussian noise (AWGN) and multipath channels.

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Orthogonal frequency-division multiplexing (OFDM) has been adopted by many broadband wireless communication systems for the simplicity of the receiver technique to support high data rates and user mobility. However, studies also show that the advantage of OFDM over the single-carrier modulation schemes could be substantially compromised by timing or frequency estimation errors at the receiver. In this thesis we investigate the synchronization problem for practical OFDM systems using a system model generalized from the IEEE 802.11 and IEEE 802.16 standards. For preamble based synchronization schemes, which are most common in the downlink of wireless communication systems, we propose a novel timing acquisition algorithm which minimizes false alarm probability and indirectly improves correct detection probability. We then introduce a universal fractional carrier frequency offset (CFO) estimator that outperforms conventional methods at low signal to noise ratio with lower complexity. More accurate timing and frequency estimates can be obtained by our proposed frequency-domain algorithms incorporating channel knowledge. We derive four joint frequency, timing, and channel estimators with different approximations, and then propose a hybrid integer CFO estimation scheme to provide flexible performance and complexity tradeoffs. When the exact channel delay profile is unknown at the receiver, we present a successive timing estimation algorithm to solve the timing ambiguity. Both analytical and simulation results are presented to confirm the performance of the proposed methods in various realistic channel conditions. The ranging based synchronization scheme is most commonly used in the uplink of wireless communication systems. Here we propose a successive multiuser detection algorithm to mitigate multiple access interference and achieve better performance than that of conventional single-user based methods. A reduced-complexity version of the successive algorithm feasible for hardware real-time implementation is also presented in the thesis. To better understand the performance of a ranging detector from a system point of view, we develop a technique that can directly translate a detector�s missed detection probability into the maximum number of users that the method can support in one cell with a given number of ranging opportunities. The analytical results match the simulations reasonably well and show that the proposed successive algorithms allow a base station to serve more than double the number of users supported by the conventional methods. Finally, we investigate inter-carrier interference which is caused by the timevarying communication channels. We derive the bounds on the power of residual inter-carrier interference that cannot be mitigated by a frequency-domain equalizer with a given number of taps. We also propose a Turbo equalization scheme using the novel grouped Particle filter, which approaches the performance of the Maximum A Posterior algorithm with much lower complexity.

ARAÚJO, D. C. Channel estimation techniques applied to massive MIMO systems using sparsity and statistics approaches. 2016. 124 f. Tese (Doutorado em Engenharia de Teleinformática)–Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2016. / Submitted by Renato Vasconcelos (ppgeti@ufc.br) on 2017-06-21T13:52:26Z No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5) / Approved for entry into archive by Marlene Sousa (mmarlene@ufc.br) on 2017-06-21T16:17:55Z (GMT) No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5) / Made available in DSpace on 2017-06-21T16:17:55Z (GMT). No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5) Previous issue date: 2016-09-29 / Massive MIMO has the potential of greatly increasing the system spectral efficiency by employing many individually steerable antenna elements at the base station (BS). This potential can only be achieved if the BS has sufficient channel state information (CSI) knowledge. The way of acquiring it depends on the duplexing mode employed by the communication system. Currently, frequency division duplexing (FDD) is the most used in the wireless communication system. However, the amount of overhead necessary to estimate the channel scales with the number of antennas which poses a big challenge in implementing massive MIMO systems with FDD protocol. To enable both operating together, this thesis tackles the channel estimation problem by proposing methods that exploit a compressed version of the massive MIMO channel. There are mainly two approaches used to achieve such a compression: sparsity and second order statistics. To derive sparsity-based techniques, this thesis uses a compressive sensing (CS) framework to extract a sparse-representation of the channel. This is investigated initially in a flat channel and afterwards in a frequency-selective one. In the former, we show that the Cramer-Rao lower bound (CRLB) for the problem is a function of pilot sequences that lead to a Grassmannian matrix. In the frequency-selective case, a novel estimator which combines CS and tensor analysis is derived. This new method uses the measurements obtained of the pilot subcarriers to estimate a sparse tensor channel representation. Assuming a Tucker3 model, the proposed solution maps the estimated sparse tensor to a full one which describes the spatial-frequency channel response. Furthermore, this thesis investigates the problem of updating the sparse basis that arises when the user is moving. In this study, an algorithm is proposed to track the arrival and departure directions using very few pilots. Besides the sparsity-based techniques, this thesis investigates the channel estimation performance using a statistical approach. In such a case, a new hybrid beamforming (HB) architecture is proposed to spatially multiplex the pilot sequences and to reduce the overhead. More specifically, the new solution creates a set of beams that is jointly calculated with the channel estimator and the pilot power allocation using the minimum mean square error (MMSE) criterion. We show that this provides enhanced performance for the estimation process in low signal-noise ratio (SNR) scenarios. / Pesquisas em sistemas MIMO massivo (do inglês multiple-input multiple-output) ganha- ram muita atenção da comunidade científica devido ao seu potencial em aumentar a eficiência espectral do sistema comunicações sem-fio utilizando centenas de elementos de antenas na estação de base (EB). Porém, tal potencial só poderá é obtido se a EB possuir suficiente informação do estado de canal. A maneira de adquiri-lo depende de como os recursos de comunicação tempo-frequência são empregados. Atualmente, a solução mais utilizada em sistemas de comunicação sem fio é a multiplexação por divisão na frequência (FDD) dos pilotos. Porém, o grande desafio em implementar esse tipo solução é porque a quantidade de tons pilotos exigidos para estimar o canal aumenta com o número de antenas. Isso resulta na perda do eficiência espectral prometido pelo sistema massivo. Esta tese apresenta métodos de estimação de canal que demandam uma quantidade de tons pilotos reduzida, mas mantendo alta precisão na estimação do canal. Esta redução de tons pilotos é obtida porque os estimadores propostos exploram a estrutura do canal para obter uma redução das dimensões do canal. Nesta tese, existem essencialmente duas abordagens utilizadas para alcançar tal redução de dimensionalidade: uma é através da esparsidade e a outra através das estatísticas de segunda ordem. Para derivar as soluções que exploram a esparsidade do canal, o estimador de canal é obtido usando a teoria de “compressive sensing” (CS) para extrair a representação esparsa do canal. A teoria é aplicada inicialmente ao problem de estimação de canais seletivos e não-seletivos em frequência. No primeiro caso, é mostrado que limitante de Cramer-Rao (CRLB) é definido como uma função das sequências pilotos que geram uma matriz Grassmaniana. No segundo caso, CS e a análise tensorial são combinado para derivar um novo algoritmo de estimatição baseado em decomposição tensorial esparsa para canais com seletividade em frequência. Usando o modelo Tucker3, a solução proposta mapeia o tensor esparso para um tensor cheio o qual descreve a resposta do canal no espaço e na frequência. Além disso, a tese investiga a otimização da base de representação esparsa propondo um método para estimar e corrigir as variações dos ângulos de chegada e de partida, causados pela mobilidade do usuário. Além das técnicas baseadas em esparsidade, esta tese investida aquelas que usam o conhecimento estatístico do canal. Neste caso, uma nova arquitetura de beamforming híbrido é proposta para realizar multiplexação das sequências pilotos. A nova solução consite em criar um conjunto de feixes, que são calculados conjuntamente com o estimator de canal e alocação de potência para os pilotos, usand o critério de minimização erro quadrático médio. É mostrado que esta solução reduz a sequencia pilot e mostra bom desempenho e cenários de baixa relação sinal ruído (SNR).

Orientador: Yuzo Iano / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-08T10:21:08Z (GMT). No. of bitstreams: 1 Arthur_Rangel_D.pdf: 3675976 bytes, checksum: 65350df75e5a9588b1366325ac95ef62 (MD5) Previous issue date: 2007 / Resumo: Esta tese trata da otimização de receptores de TV Digital baseados em OFDM, com avaliação de desempenho em redes de retransmissão em freqüência única (SFN . Single Frequency Networks) regionais. Tal ambiente facilita a distribuição de canais, porém possui características que dificultam o trabalho do receptor. São tratados, inicialmente, de projetos de filtros canceladores de elos de realimentação em estações retransmissoras, que ocorrem quando a antena de transmissão interfere na antena de recepção. Um novo filtro, baseado em técnicas que utilizam informação temporal é proposto. Novas propostas são feitas para as partes de sincronismo, estimação e equalização de canal, e codificação/decodificação. Uma técnica, vinda da teoria de reconhecimento de padrões, é aplicada para diminuição da complexidade no processo de sincronismo temporal. Um sistema de estimação de canal 2D e equalização adaptativa, usando o LMS (Least Mean Square), é comparado com técnicas clássicas da literatura, e um ganho significativo é encontrado. Como novo esquema de codificação e decodificação é proposto um esquema iterativo, baseado em códigos turbo, com número reduzido de iterações. Tal código melhora o desempenho do sistema em relação ao uso combinado dos decodificadores Viterbi e Reed Solomon. Todas as propostas são combinadas para se avaliar o desempenho do receptor diante de condições típicas de SFN e multicaminhos típicos em recepção de TV do Brasil / Abstract: This thesis deals with the optimization of Digital TV receivers based on OFDM, with performance evaluation in regional single frequency networks (SFN). Such environment facilitates the channel distribution, however its characteristics degrade the receiver operation. Initially, projects of loop canceller filters in relay stations are treated, and they are necessary when the transmission antenna causes interference on reception antenna. A new filter, based on time information is proposed. New proposals are made for the synchronism, channel estimation and equalization, and coding/decoding. One technique, coming from the pattern recognition theory, is applied for complexity reduction in the process of time synchronism. A 2D channel estimation system and adaptive equalization, using LMS (Least Mean Square), is compared to classical techniques in the literature, and a significant gain is achieved. As a new coding and decoding scheme, an iterative system based on turbo codes is used with reduced number of iterations. Such code improves the system performance when compared to the Viterbi and Reed Solomon concatenated decoders. The proposals are combined and the performance of the proposed receiver is evaluated on typical conditions of SFN and on typical multipaths for TV reception in Brazil / Doutorado / Telecomunicações e Telemática / Doutor em Engenharia Elétrica

Submitted by isabela.moljf@hotmail.com (isabela.moljf@hotmail.com) on 2017-03-02T12:13:28Z No. of bitstreams: 1 antonioangelomissiaggiapicrone.pdf: 1988788 bytes, checksum: 6b0bc2b5525993261c14440b4ad8a007 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-03-06T19:35:07Z (GMT) No. of bitstreams: 1 antonioangelomissiaggiapicrone.pdf: 1988788 bytes, checksum: 6b0bc2b5525993261c14440b4ad8a007 (MD5) / Made available in DSpace on 2017-03-06T19:35:07Z (GMT). No. of bitstreams: 1 antonioangelomissiaggiapicrone.pdf: 1988788 bytes, checksum: 6b0bc2b5525993261c14440b4ad8a007 (MD5) Previous issue date: 2009-08-31 / Nesta dissertação é discutido e analisado o desempenho de técnicas de estimação de canais baseada em sinais piloto para modulação OFDM (Orthogonal Frequency Division Multiplexing), aplicada a transmissão de dados através de canais PLC (Power Line Communications). Os canais PLC são modelados como linear e invariante no tempo (LIT), linear e variante no tempo (LVT) e linear e ciclicamente variante no tempo (LCVT) e um modelo de ruído aditivo impulsivo gaussiano (AIGN) é considerado. São mostrados os resultados de análises de desempenhos obtidos com os estimadores de canal adaptativo e n˜ao adaptativo associados com equalizadores de canal e técnicas estratégicas de alocação de sinais piloto. Os resultados obtidos, com base no desempenho das simulações, apontam direções interessantes para melhorar as técnicas de estimação de canais baseadas em sinais piloto quando o canal PLC é LIT, LVT ou LCVT e corrompidos por ruído AIGN. / In this dissertation is discussed and analyzed the performance of pilot-assisted channel estimation techniques for OFDM (Orthogonal Frequency Division Multiplexing) modulation that is applied to data transmission through PLC (power line communications) channels. The PLC channels are modeled as linear and time-invariant (LIT), linear and time variant (LTV), and linear and cyclic time-variant (LCTV) ones when the additive impulsive gaussian noise (AIGN) is considered. Performance analysis obtained with adaptive and nonadaptive channel estimation techniques together with channel equalization and pilot signal allocation ones are provided. The results based upon performance simulation offer interesting directions to improve pilot-assisted channel estimation techniques when the PLC channel are LIT, LTV or LCTV corrupted by AIGN.

Future fifth generation (5G) cellular networks have to cope with the expected ten-fold increase in mobile data traffic between 2015 and 2021. To achieve this goal, new technologies are being considered, including massive multiple-input multiple-output (MIMO) systems and millimeter-wave (mmWave) communications. Massive MIMO involves the use of large antenna array sizes at the base station, while mmWave communications employ frequencies between 30 and 300 GHz. In this thesis we study the impact of these technologies on the performance of channel estimators. Our results show that the characteristics of the propagation channel at mmWave frequencies improve the channel estimation performance in comparison with current, low frequency-based, cellular networks. Furthermore, we demonstrate the existence of an optimal angular spread of the multipath clusters, which can be used to maximize the capacity of mmWave networks. We also propose efficient noise variance estimators, which can be employed as an input to existing channel estimators.

We consider the problem of equalizing data blocks of signals, which have been transmitted over an aeronautical channel using two different modulation schemes. The equalization is performed using the block-processing constant modulus algorithm (CMA), and in order to achieve real-time processing a Fast Fourier Transform (FFT) is used to compute the gradient of this cost function during equalization. The equalizer length is chosen to be five times of the channel length. For the first experiment, we present the result of equalizing a set of measured data, which was modulated and transmitted using the iNET packet structure with SOQPSK modulation. In this case, the CMA equalizer is first initialized using MMSE and the equalizer coefficients are then updated once, using each entire block (iNET packet). In the second experiment, we apply the FFT-based block processing equalizer to received data blocks of QPSK signals, which have been randomly generated and transmitted over an aeronautical channel. A modified constant modulus algorithm and alphabet matched algorithm (CMA + AMA) equalizer is used to recover these data blocks. For this case of QPSK signals, the equalizer performance is evaluated over 500 Monte Carlo runs, using the average symbol error rate (SER).

In the first part of the dissertation, we provide an extensive overview of sub-6 GHz wireless access technology known as massive multiple-input multiple-output (MIMO) systems, highlighting its benefits, deployment challenges, and the key enabling technologies envisaged for 5G networks. We investigate the fundamental issues that degrade the performance of massive MIMO systems such as pilot contamination, precoding, user scheduling, and signal detection. In the second part, we optimize the performance of the massive MIMO system by proposing several algorithms, system designs, and hardware architectures. To mitigate the effect of pilot contamination, we propose a pilot reuse factor scheme based on the user environment and the number of active users. The results through simulations show that the proposed scheme ensures the system always operates at maximal spectral efficiency and achieves higher throughput. To address the user scheduling problem, we propose two user scheduling algorithms bases upon the measured channel gain. The simulation results show that our proposed user scheduling algorithms achieve better error performance, improve sum capacity and throughput, and guarantee fairness among the users. To address the uplink signal detection challenge in the massive MIMO systems, we propose four algorithms and their system designs. We show through simulations that the proposed algorithms are computationally efficient and can achieve near-optimal bit error rate performance. Additionally, we propose hardware architectures for all the proposed algorithms to identify the required physical components and their interrelationships.

The need for reliable, high-throughput, mobile wireless communication technologies has never been greater as increases in the demand for on-the-go access to information, entertainment, and other electronic services continues. Two such technologies, which are at the forefront of current research efforts, are orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) systems, their union being known simply as MIMO-OFDM. The successful performance of these technologies depends upon the availability of accurate information concerning the wireless communication channel. In this dissertation, several issues related to quality of this channel state information (CSI) are studied. Specifically, the first part of this dissertation considers the design of optimal pilot signals for OFDM systems. The optimization is addressed via lower bounds on the estimation error variance, which bounds are given by formulations of the Cram'{e}r-Rao bound (CRB). The second part of this dissertation uses the CRB once again, this time as a tool for evaluating the potential performance of MIMO-OFDM channel estimation and prediction. Bounds are found for several parametric time-varying wideband MIMO-OFDM channel models, and numerical evaluations of these bounds are used to illuminate several interesting features regarding the estimation and prediction of MIMO-OFDM channels. The final part of this dissertation considers the problem of MIMO multiplexing using SVD-based methods when only imperfect CSI is available. For this purpose, general per-MIMO-subchannel signal and interference-plus-noise power expressions are derived to quantify the effects of CSI imperfections, and these expressions are then used to find robust MIMO-SVD power and bit allocations which maintain good overall performance in spite of imperfect CSI.