Frequency-Domain Modeling of OFDM Transmission with Insufficient Cyclic Prefix using Toeplitz Matrices

A novel mathematical framework is proposed to model Intersymbol Interference (ISI) phenomenon in wireless communication systems based on Orthogonal Frequency Division Multiplexing (OFDM) with or without cyclic prefix. The framework is based on a new formula to calculate the Fast Fourier Transform (FFT) of a triangular Toeplitz matrix, which is derived and proven in this paper. It is shown that distortion inducted by the ISI from a given subcarrier is the most significant for the closest subcarriers and the contribution decays as the distance between subcarriers grows. According to numerical experiments, knowledge of ISI coefficients concentrated around the diagonal of Channel Frequency Response (CFR) matrix improves the receiver's error floor significantly. The potential use of the framework for real-time frequency domain channel simulation was also investigated and demonstrated to be more efficient than conventional time domain Tapped Delay Line (TDL) model when a number of simulated users is high.Comment: Conference: IEEE VTC-Fall 2018, 5 pages, 3 figure

Comparative Analysis of Conventional and ICI-Self-Cancellation Digital Video Broadcasting Transceivers

Digital video broadcasting–terrestrial (DVB-T) is one of the important technologies in the communication area because of its capability of high data-rate multimedia transmission. Orthogonal frequency division multiplexing (OFDM) has been the backbone technique in the current DVB-T systems adopted by Europe and Japan. However, since the OFDM system is very sensitive to the frequency synchronization and phase errors, which will induce the intercarrier interference (ICI), the ongoing research has been dedicated to this ICI problem in the presence of the Doppler frequency drift and the fading channels. A means to deal with the ICI problem is called the ICI self-cancellation or polynomial cancellation coding scheme. In this thesis, we establish the complete simulation environment for the physical layer of the DVB-T system and then evaluate the effectiveness of the ICI self-cancellation coding scheme compared with the existing convolutional coding scheme for different fading channels and different Doppler frequencies. According to our simulation results, we conclude that the ICI self-cancellation scheme significantly outperforms the convolutional coding scheme which is adopted by the existing DVB-T standard in the AWGN and the frequency non-selective fading channels, but both schemes have the similar performance in the frequency selective fading channels

Advanced Statistical Signal Processing Methods in Sensing, Detection, and Estimation for Communication Applications

The applications of wireless communications and digital signal processing have dramatically changed the way we live, work, and learn over decades. The requirement of higher throughput and ubiquitous connectivity for wireless communication systems has become prevalent nowadays. Signal sensing, detection and estimation have been prevalent in signal processing and communications for many years. The relevant studies deal with the processing of information-bearing signals for the purpose of information extraction. Nevertheless, new robust and efficient signal sensing, detection and estimation techniques are still in demand since there emerge more and more practical applications which rely on them. In this dissertation work, we proposed several novel signal sensing, detection and estimation schemes for wireless communications applications, such as spectrum sensing, symbol-detection/channel-estimation, and encoder identification. The associated theories and practice in robustness, computational complexity, and overall system performance evaluation are also provided

OFDM techniques for multimedia data transmission

Orthogonal Frequency Division Multiplexing (OFDM) is an efficient parallel data transmission scheme that has relatively recently become popular in both wired and wireless communication systems for the transmission of multimedia data. OFDM can be found at the core of well known systems such as digital television/radio broadcasting, ADSL internet and wireless LANs. Research into the OFDM field continually looks at different techniques to attempt to make this type of transmission more efficient. More recent works in this area have considered the benefits of using wavelet transforms in place of the Fourier transforms traditionally used in OFDM systems and other works have looked at data compression as a method of increasing throughput in these types of transmission systems. The work presented in this thesis considers the transmission of image and video data in traditional OFDM transmission and discusses the strengths and weaknesses of this method. This thesis also proposes a new type of OFDM system that combines transmission and data compression into one block. By merging these two processes into one the complexity of the system is reduced, therefore promising to increase system efficiency. The results presented in this thesis show the novel compressive OFDM method performs well in channels with a low signal-to-noise ratio. Comparisons with traditional OFDM with lossy compression show a large improvement in the quality of the data received with the new system when used in these noisy channel environments. The results also show superior results are obtained when transmitting image and video data using the new method, the high correlative properties of images are ideal for effective transmission using the new technique. The new transmission technique proposed in this thesis also gives good results when considering computation time. When compared to MATLAB simulations of a traditional DFT-based OFDM system with a separate compression block, the proposed transmission method was able to reduce the computation time by between a half to three-quarters. This decrease in computational complexity also contributes to transmission efficiency when considering the new method

The optimization of multiple antenna broadband wireless communications. A study of propagation, space-time coding and spatial envelope correlation in Multiple Input, Multiple Output radio systems

This work concentrates on the application of diversity techniques and space time block coding for future mobile wireless communications. The initial system analysis employs a space-time coded OFDM transmitter over a multipath Rayleigh channel, and a receiver which uses a selection combining diversity technique. The performance of this combined scenario is characterised in terms of the bit error rate and throughput. A novel four element QOSTBC scheme is introduced, it is created by reforming the detection matrix of the original QOSTBC scheme, for which an orthogonal channel matrix is derived. This results in a computationally less complex linear decoding scheme as compared with the original QOSTBC. Space time coding schemes for three, four and eight transmitters were also derived using a Hadamard matrix. The practical optimization of multi-antenna networks is studied for realistic indoor and mixed propagation scenarios. The starting point is a detailed analysis of the throughput and field strength distributions for a commercial dual band 802.11n MIMO radio operating indoors in a variety of line of sight and non-line of sight scenarios. The physical model of the space is based on architectural schematics, and realistic propagation data for the construction materials. The modelling is then extended and generalized to a multi-storey indoor environment, and a large mixed site for indoor and outdoor channels based on the Bradford University campus. The implications for the physical layer are also explored through the specification of antenna envelope correlation coefficients. Initially this is for an antenna module configuration with two independent antennas in close proximity. An operational method is proposed using the scattering parameters of the system and which incorporates the intrinsic power losses of the radiating elements. The method is extended to estimate the envelope correlation coefficient for any two elements in a general (N,N) MIMO antenna array. Three examples are presented to validate this technique, and very close agreement is shown to exist between this method and the full electromagnetic analysis using the far field antenna radiation patterns

A compressed sensing approach to block-iterative equalization: connections and applications to radar imaging reconstruction

The widespread of underdetermined systems has brought forth a variety of new algorithmic solutions, which capitalize on the Compressed Sensing (CS) of sparse data. While well known greedy or iterative threshold type of CS recursions take the form of an adaptive filter followed by a proximal operator, this is no different in spirit from the role of block iterative decision-feedback equalizers (BI-DFE), where structure is roughly exploited by the signal constellation slicer. By taking advantage of the intrinsic sparsity of signal modulations in a communications scenario, the concept of interblock interference (IBI) can be approached more cunningly in light of CS concepts, whereby the optimal feedback of detected symbols is devised adaptively. The new DFE takes the form of a more efficient re-estimation scheme, proposed under recursive-least-squares based adaptations. Whenever suitable, these recursions are derived under a reduced-complexity, widely-linear formulation, which further reduces the minimum-mean-square-error (MMSE) in comparison with traditional strictly-linear approaches. Besides maximizing system throughput, the new algorithms exhibit significantly higher performance when compared to existing methods. Our reasoning will also show that a properly formulated BI-DFE turns out to be a powerful CS algorithm itself. A new algorithm, referred to as CS-Block DFE (CS-BDFE) exhibits improved convergence and detection when compared to first order methods, thus outperforming the state-of-the-art Complex Approximate Message Passing (CAMP) recursions. The merits of the new recursions are illustrated under a novel 3D MIMO Radar formulation, where the CAMP algorithm is shown to fail with respect to important performance measures.A proliferação de sistemas sub-determinados trouxe a tona uma gama de novas soluções algorítmicas, baseadas no sensoriamento compressivo (CS) de dados esparsos. As recursões do tipo greedy e de limitação iterativa para CS se apresentam comumente como um filtro adaptativo seguido de um operador proximal, não muito diferente dos equalizadores de realimentação de decisão iterativos em blocos (BI-DFE), em que um decisor explora a estrutura do sinal de constelação. A partir da esparsidade intrínseca presente na modulação de sinais no contexto de comunicações, a interferência entre blocos (IBI) pode ser abordada utilizando-se o conceito de CS, onde a realimentação ótima de símbolos detectados é realizada de forma adaptativa. O novo DFE se apresenta como um esquema mais eficiente de reestimação, baseado na atualização por mínimos quadrados recursivos (RLS). Sempre que possível estas recursões são propostas via formulação linear no sentido amplo, o que reduz ainda mais o erro médio quadrático mínimo (MMSE) em comparação com abordagens tradicionais. Além de maximizar a taxa de transferência de informação, o novo algoritmo exibe um desempenho significativamente superior quando comparado aos métodos existentes. Também mostraremos que um equalizador BI-DFE formulado adequadamente se torna um poderoso algoritmo de CS. O novo algoritmo CS-BDFE apresenta convergência e detecção aprimoradas, quando comparado a métodos de primeira ordem, superando as recursões de Passagem de Mensagem Aproximada para Complexos (CAMP). Os méritos das novas recursões são ilustrados através de um modelo tridimensional para radares MIMO recentemente proposto, onde o algoritmo CAMP falha em aspectos importantes de medidas de desempenho