Bandwidth efficiency is a critical concern in wireless communications. To fully utilize the available bandwidth, the superimposed training (ST) scheme is adopted in this thesis for orthogonal frequency division multiplexing (OFDM) systems without using the cyclic prefix (CP) and the guard interval (GI). It is shown that the performance of the channel estimation using the ST scheme is the same for both the proposed architecture, denoted as OFDM-ST, and the conventional OFDM system with CP, denoted as CP-OFDM-ST. In addition, since the CP is not added in the proposed system, leading to substantial increase in both the inter-symbol interference (ISI) and the inter-carrier interference (ICI), an interference cancellation scheme is derived. To further improve the performance of channel estimation using ST scheme, the joint ML data detection and channel estimation method is investigated. The simulation results illustrate that the proposed algorithm enhances the systems performance significantly. Finally, it is demonstrated that the proposed structure has a much better effective data rate than the CP-OFDM-ST system.

The continuous phase modulation (CPM) has a constant envelope and compact output power spectrum that makes it a promising underlying technology for power and spectrum efficient broadband wireless communications. However, high implementation complexity (especially the complexity of the receiver) required to deal with the phase memory and inter-symbol interference has impeded its adoption for broadband wireless communications, and only a few simple CPM modulation schemes have mainly been used, e.g. binary MSK and GMSK. Thus, research on efficient CPM transceivers to reduce the computational and hardware complexity is important. The major contribution of this dissertation is the development of novel frequency domain processing techniques and transceiver strategies to improve power and spectral efficiency, and reduce the complexity of CPM modulation schemes. First, this dissertation presents simplified frequency domain receiver structures and decoding schemes in the frequency domain for binary and M-ary CPM block transmission. The frequency domain receivers utilize parallel and serial structures with frequency domain processing which considerably reduces hardware and computational complexity compared to conventional time-domain processing. In addition, the decoding schemes in the frequency domain eliminate the controlled phase memory through frequency domain phase equalization instead of maximum-likelihood sequential decoders, e.g. Viterbi decoders. Second, frequency domain channel estimation schemes for CPM block transmission are presented, which adopt superimposed training signals to achieve bandwidth and power efficiency while reducing the complexity. In these schemes, the proposed frequency domain channel estimation uses the superimposed training signals as a reference signal to reduce the throughput loss caused by conventionally multiplexed training signals. Superimposed training signal design is presented, and the trade-off between bandwidth efficiency and power efficiency is also analyzed. Third, block transmission schemes and frequency domain equalization methods for CPM are proposed, which consider linear processing instead of conventional decomposition-based processing. The schemes of frequency domain linear processing avoid the complexity overhead (both in computation and hardware) of conventional orthogonal- or Laurent decomposed-based equalizers. Finally, this dissertation extends CPM block transmission and frequency domain equalization to phase-coded (time-varying modulation index) CPM, which shows better error performance and bandwidth efficiency than fixed modulation index CPM's. / text

In data-dependent superimposed training (DDST) system, the data sequence subtracts a data-dependent sequence before transmission. The receiver cannot correctly find the unknown term which causes an error floor at high SNR. In this thesis, we list some helpful conditions to enhance the performance for precoding design in DDST system, and analyze the major cause of data misidentification by singular value decomposition (SVD) method. Finally, we propose a precoding matrix based on [C.-P. Li and W.-C. Huang, ¡§A constructive representation for the Fourier dual of the Zadoff¡VChu sequences,¡¨ IEEE Trans. Inf. Theory, vol. 53, no. 11, pp. 4221¡Ð4224, Nov. 2007]. The precoding matrix is constructed by an inverse discrete Fourier transform (IDFT) matrix and a diagonal matrix with the elements consist of an arbitrary perfect sequence. The proposed method satisfies these conditions and simulation results show that the data identification problem is solved.

In a MIMO system, a transmitter with perfect knowledge of the underlying channel state information (CSI) can achieve a higher channel capacity compared to transmission without CSI. When reciprocity of the wireless channel does not hold, the identification and utilization of partial CSI at the transmitter are important issues. This thesis is focused on partial CSI acquisition and utilization techniques for MIMO channels. We propose a feedback algorithm for tracking the dominant channel subspaces for MIMO systems in a continuously time-varying environment. We exploit the correlation between channel states of adjacent time instants and quantize the variation of channel states. Specifically, we model a subspace as one point in a Grassmann manifold, treat the variations in principal right singular subspaces of the channel matrices as a piecewise-geodesic process in the Grassmann manifold, and quantize the velocity matrix of the geodesic. We design a complexity-constrained MIMO OFDM system where the transmitter has knowledge of channel correlations. The transmitter is constrained to perform at most one inverse Discrete Fourier Transform per OFDM symbol on the average. We show that in the MISO case, time domain beamforming can be used to do two-dimensional eigen-beamforming. For the MIMO case, we derive design criteria for the transmitter beamforming and receiver combining weighting vectors and show some suboptimal solutions. The feedback channel may have uncertainties such as unexpected delay or error. We consider channel mean feedback with an unknown delay and propose a broadcast approach that is able to adapt to the quality of the feedback. Having considered CSI feedback problems where the receiver tries to convey its attained CSI to the transmitter, we turn to noncoherent coding design for fast fading channels, where the receiver does not have reliable CSI. We propose a data-dependent superimposed training scheme to improve the performance of training based codes. The transmitter is equipped with multiple training sequences and dynamically selects a training sequence for each data sequence to minimize channel estimation error. The set of training sequences are optimized to minimize pairwise error probability between codewords.

For channel estimation without data-induced interference in data-dependent superimposed training (DDST) scheme, the data sequence is shifted by subtracting a data-dependent sequence before added to training sequence at transmitter. The distorted term causes the data identification problem (DIP) at the receiver. In this thesis, we propose two precoding schemes based on previous work. To maintain low peak-to-average power ratio (PAPR), the precoding matrix is restricted to a diagonal matrix. The first scheme is proposed to enlarge the minimum distance between the closest codewords, termed as efficient diagonal scheme. Conditions to make sure the precoding matrix is efficient for M-ary phase shift keying (MPSK) and M-ary quadrature amplitude modulation (MQAM) modulation are listed in this paper. The second scheme pursues a lowest complexity at receiver which means the amount of searching set is reduced. It is a trade-off between the better bit error rate (BER) performance and a lower complexity at receiver. The simulation results show that PAPR have been improved and the DIP is solved in both schemes.

Orientadores: João Marcos Travassos Romano, Leandro de Campos Teixeira Gomes / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-10T02:05:39Z (GMT). No. of bitstreams: 1 UlianiNeto_Mario_M.pdf: 12916890 bytes, checksum: 53ed98252c8c6c265c985346ceaeec4f (MD5) Previous issue date: 2008 / Resumo: O objetivo deste trabalho é investigar o uso de uma marca d'água digital como sinal de referência na filtragem adaptativa supervisionada, aplicada aos problemas de equalização e identificação de canais. Ao contrário de métodos mais tradicionais, nos quais a comunicação é periodicamente interrompida para a transmissão de seqüências de treinamento, uma marca d'água é transmitida ininterruptamente, juntamente com o sinal de informação. Através da comparação entre o sinal recebido processado pelo filtro equalizador e a marca d'água original, ou entre o sinal recebido e a marca d' água processada pelo filtro identificador, os coeficientes deste filtro são continuamente adaptados para estimar e rastrear as características do canal ao longo do tempo. Tanto a transmissão de informação útil como a adaptação do filtro equalizador/identificador nunca são interrompidas. Para que o processo de detecção de uma marca d'água digital seja eficiente, é necessária a sincronização da marca no detector. Efeitos de dessincron}zação podem prejudicar a detecção, potencialmente inviabilizando a extração adequada da informação contida na marca d'água. Esta dissertação apresenta dois métodos de ressincronização para sistemas de filtragem empregando marca d'água. Ambos os métodos são baseados no uso de seqüências de treinamento embutidas na marca d'água e revertem os efeitos de uma ampla classe de ataques de dessincronização. No caso de sinais que apresentem uma interpretação sensorial (e.g. áudio, imagens, vídeo), a adição da marca d'água não deve causar distorção perceptível no sinal original. Propomos o uso de um modelo psicoacústico em conjunto com um algoritmo de conformação espectral para demonstrar a viabilidade do método quando aplicado a sinais de áudio. Resultados de simulações computacionais são apresentados para evidenciar o desempenho das propostas fr_nte a técnicas tradicionais de filtragem adaptativa supervisionada / Abstact: The objective of this work is to investigate the use of a digital watermark as a reference signal in supervised adaptive filtering, applied to the channel equalization and identification problems. Contrary to traditional adaptive methods, in which communication is periodically interrupted for the transmission of training sequences, a watermark is transmitted uninterruptedly, along with the information signal. By comparing the received signal and the watermark processed by the identification filter, or the received signal processed by the equalization filter and the original watermark, the coefficients of this filter are continuously adapted to estimate and monitor channel characteristics through time. Both the transmission of useful information and the adaptation of the identification/equalization filter are never interrupted. For the watermark detection process to be efficient, synchronization of the watermark in the detector is required. Desynchronization effects can reduce detection performance, potentially making impracticable the appropriate extraction of the information contained in the watermark. This dissertation presents two resynchronization methods for filtering systems using a watermark. Both methods are based on training sequences that are embedded in the watermark, and can reverse the effects of a large class of desynchronization attacks. The embedding of a watermark into signals with sensorial interpretation (e.g. audio, image, video) should not introduce noticeable distortion in the original signal. To achieve this when applying our method to audio signals, we propose the use of a psychoacoustic model with a spectral shaping algorithm. Simulation results are presented to illustrate the performance of the proposed method when compared to traditional supervised adaptive filtering techniques / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica