Smoothing techniques for decision-directed MIMO OFDM channel estimation

With the purpose of supplying the demand of faster and more reliable communication, multiple-input multiple-output (MIMO) systems in conjunction with Orthogonal Frequency Division Multiplexing (OFDM) are subject of extensive research. Successful Decoding requires an accurate channel estimate at the receiver, which is gained either by evaluation of reference symbols which requires designated resources in the transmit signal or decision-directed approaches. The latter offers a convenient way to maximize bandwidth efficiency, but it suffers from error propagation due to the dependency between the decoding of the current data symbol and the calculation of the next channel estimate. In our contribution we consider linear smoothing techniques to mitigate error propagation by the introduction of backward dependencies in the decision-based channel estimation. Designed as a post-processing step, frame repeat requests can be lowered by applying this technique if the data is insensitive to latency. The problem of high memory requirements of FIR smoothing in the context of MIMO-OFDM is addressed with an recursive approach that acquires minimal resources with virtual no performance loss. Channel estimate normalized mean square error and bit error rate (BER) performance evaluations are presented. For reference, a median filtering technique is presented that operates on the MIMO time-frequency grids of channel coefficients to reduce the peak-like outliers produced by wrong decisions due to unsuccessful decoding. Performance in terms of Bit Error Rate is compared to the proposed smoothing techniques

Single-Frequency Network Terrestrial Broadcasting with 5GNR Numerology

L'abstract è presente nell'allegato / the abstract is in the attachmen

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

Doppler compensation algorithms for DSP-based implementation of OFDM underwater acoustic communication systems

In recent years, orthogonal frequency division multiplexing (OFDM) has gained considerable attention in the development of underwater communication (UWC) systems for civilian and military applications. However, the wideband nature of the communication links necessitate robust algorithms to combat the consequences of severe channel conditions such as frequency selectivity, ambient noise, severe multipath and Doppler Effect due to velocity change between the transmitter and receiver. This velocity perturbation comprises two scenarios; the first induces constant time scale expansion/compression or zero acceleration during the transmitted packet time, and the second is time varying Doppler-shift. The latter is an increasingly important area in autonomous underwater vehicle (AUV) applications. The aim of this thesis is to design a low complexity OFDM-based receiver structure for underwater communication that tackles the inherent Doppler effect and is applicable for developing real-time systems on a digital signal processor (DSP). The proposed structure presents a paradigm in modem design from previous generations of single carrier receivers employing computationally expensive equalizers. The thesis demonstrates the issues related to designing a practical OFDM system, such as channel coding and peak-to-average power ratio (PAPR). In channel coding, the proposed algorithms employ convolutional bit-interleaved coded modulation with iterative decoding (BICM-ID) to obtain a higher degree of protection against power fading caused by the channel. A novel receiver structure that combines an adaptive Doppler-shift correction and BICM-ID for multi-carrier systems is presented. In addition, the selective mapping (SLM) technique has been utilized for PAPR. Due to their time varying and frequency selective channel nature, the proposed systems are investigated via both laboratory simulations and experiments conducted in the North Sea off the UK’s North East coast. The results of the study show that the proposed systems outperform block-based Doppler-shift compensation and are capable of tracking the Doppler-shift at acceleration up to 1m /s2.EThOS - Electronic Theses Online ServiceIraqi Government's Ministry of Higher Education and Scientific ResearchGBUnited Kingdo

Advanced receivers for distributed cooperation in mobile ad hoc networks

Mobile ad hoc networks (MANETs) are rapidly deployable wireless communications systems, operating with minimal coordination in order to avoid spectral efficiency losses caused by overhead. Cooperative transmission schemes are attractive for MANETs, but the distributed nature of such protocols comes with an increased level of interference, whose impact is further amplified by the need to push the limits of energy and spectral efficiency. Hence, the impact of interference has to be mitigated through with the use PHY layer signal processing algorithms with reasonable computational complexity. Recent advances in iterative digital receiver design techniques exploit approximate Bayesian inference and derivative message passing techniques to improve the capabilities of well-established turbo detectors. In particular, expectation propagation (EP) is a flexible technique which offers attractive complexity-performance trade-offs in situations where conventional belief propagation is limited by computational complexity. Moreover, thanks to emerging techniques in deep learning, such iterative structures are cast into deep detection networks, where learning the algorithmic hyper-parameters further improves receiver performance. In this thesis, EP-based finite-impulse response decision feedback equalizers are designed, and they achieve significant improvements, especially in high spectral efficiency applications, over more conventional turbo-equalization techniques, while having the advantage of being asymptotically predictable. A framework for designing frequency-domain EP-based receivers is proposed, in order to obtain detection architectures with low computational complexity. This framework is theoretically and numerically analysed with a focus on channel equalization, and then it is also extended to handle detection for time-varying channels and multiple-antenna systems. The design of multiple-user detectors and the impact of channel estimation are also explored to understand the capabilities and limits of this framework. Finally, a finite-length performance prediction method is presented for carrying out link abstraction for the EP-based frequency domain equalizer. The impact of accurate physical layer modelling is evaluated in the context of cooperative broadcasting in tactical MANETs, thanks to a flexible MAC-level simulato

Synchronization algorithms and architectures for wireless OFDM systems

Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation technique that has become a viable method for wireless communication systems due to the high spectral efficiency, immunity to multipath distortion, and being flexible to integrate with other techniques. However, the high-peak-to-average power ratio and sensitivity to synchronization errors are the major drawbacks for OFDM systems. The algorithms and architectures for symbol timing and frequency synchronization have been addressed in this thesis because of their critical requirements in the development and implementation of wireless OFDM systems. For the frequency synchronization, two efficient carrier frequency offset (CFO) estimation methods based on the power and phase difference measurements between the subcarriers in consecutive OFDM symbols have been presented and the power difference measurement technique is mapped onto reconfigurable hardware architecture. The performance of the considered CFO estimators is investigated in the presence of timing uncertainty conditions. The power difference measurements approach is further investigated for timing synchronization in OFDM systems with constant modulus constellation. A new symbol timing estimator has been proposed by measuring the power difference either between adjacent subcarriers or the same subcarrier in consecutive OFDM symbols. The proposed timing metric has been realized in feedforward and feedback configurations, and different implementation strategies have been considered to enhance the performance and reduce the complexity. Recently, multiple-input multiple-output (MIMO) wireless communication systems have received considerable attention. Therefore, the proposed algorithms have also been extended for timing recovery and frequency synchronization in MIMO-OFDM systems. Unlike other techniques, the proposed timing and frequency synchronization architectures are totally blind in the sense that they do not require any information about the transmitted data, the channel state or the signal-to-noise-ratio (SNR). The proposed frequency synchronization architecture has low complexity because it can be implemented efficiently using the three points parameter estimation approach. The simulation results confirmed that the proposed algorithms provide accurate estimates for the synchronization parameters using a short observation window. In addition, the proposed synchronization techniques have demonstrated robust performance over frequency selective fading channels that significantly outperform other well-established methods which will in turn benefit the overall OFDM system performance. Furthermore, an architectural exploration for mapping the proposed frequency synchronization algorithm, in particular the CFO estimation based on the power difference measurements, on reconfigurable computing architecture has been investigated. The proposed reconfigurable parallel and multiplexed-stream architectures with different implementation alternatives have been simulated, verified and compared for field programmable gate array (FPGA) implementation using the Xilinx’s DSP design flow.EThOS - Electronic Theses Online ServiceMinistry of Higher Education and Scientific Research (MOHSR) of IraqGBUnited Kingdo