Distributed space time block coding and application in cooperative cognitive relay networks

The design and analysis of various distributed space time block coding schemes for cooperative relay networks is considered in this thesis. Rayleigh frequency flat and selective fading channels are assumed to model the links in the networks, and interference suppression techniques together with an orthogonal frequency division multiplexing (OFDM) type transmission approach are employed to mitigate synchronization errors at the destination node induced by the different delays through the relay nodes. Closed-loop space time block coding is first considered in the context of decode-and-forward (regenerative) networks. In particular, quasi orthogonal and extended orthogonal coding techniques are employed for transmission from four relay nodes and parallel interference cancellation detection is exploited to mitigate synchronization errors. Availability of a direct link between the source and destination nodes is studied. Outer coding is then added to gain further improvement in end-to-end performance and amplify-and-forward (non regenerative) type networks together with distributed space time coding are considered to reduce relay node complexity. A novel detection scheme is then proposed for decode-and-forward and amplify-and-forward networks with closed-loop extended orthogonal coding and closed-loop quasi-orthogonal coding which reduce the computational complexity of the parallel interference cancellation. The near-optimum detector is presented for relay nodes with single or dual antennas. End-to-end bit error rate simulations confirm the potential of the approach and its ability to mitigate synchronization errors

Architectures and Algorithms for the Signal Processing of Advanced MIMO Radar Systems

This thesis focuses on the research, development and implementation of novel concepts, architectures, demonstrator systems and algorithms for the signal processing of advanced Multiple Input Multiple Output (MIMO) radar systems. The key concept is to address compact system, which have high resolutions and are able to perform a fast radar signal processing, three-dimensional (3D), and four-dimensional (4D) beamforming for radar image generation and target estimation. The idea is to obtain a complete sensing of range, Azimuth and elevation (additionally Doppler as the fourth dimension) from the targets in the radar captures. The radar technology investigated, aims at addressing sev- eral civil and military applications, such as surveillance and detection of targets, both air and ground based, and situational awareness, both in cars and in flying platforms, from helicopters, to Unmanned Aerial Vehicles (UAV) and air-taxis. Several major topics have been targeted. The development of complete systems and innovative FPGA, ARM and software based digital architectures for 3D imaging MIMO radars, which operate in both Time Division Multiplexing (TDM) and Frequency Divi- sion Multiplexing (FDM) modes, with Frequency Modulated Continuous Wave (FMCW) and Orthogonal Frequency Division Multiplexing (OFDM) signals, respectively. The de- velopment of real-time radar signal processing, beamforming and Direction-Of-Arrival (DOA) algorithms for target detection, with particular focus on FFT based, hardware implementable techniques. The study and implementation of advanced system concepts, parametrisation and simulation of next generation real-time digital radars (e.g. OFDM based). The design and development of novel constant envelope orthogonal waveforms for real-time 3D OFDM MIMO radar systems. The MIMO architectures presented in this thesis are a collection of system concepts, de- sign and simulations, as well as complete radar demonstrators systems, with indoor and outdoor measurements. Several of the results shown, come in the form of radar images which have been captured in field-test, in different scenarios, which aid in showing the proper functionality of the systems. The research activities for this thesis, have been carried out on the premises of Air- bus, based in Munich (Germany), as part of a Ph.D. candidate joint program between Airbus and the Polytechnic Department of Engineering and Architecture (Dipartimento Politecnico di Ingegneria e Architettura), of the University of Udine, based in Udine (Italy).Questa tesi si concentra sulla ricerca, lo sviluppo e l\u2019implementazione di nuovi concetti, architetture, sistemi dimostrativi e algoritmi per l\u2019elaborazione dei segnali in sistemi radar avanzati, basati su tecnologia Multiple Input Multiple Output (MIMO). Il con- cetto chiave `e quello di ottenere sistemi compatti, dalle elevate risoluzioni e in grado di eseguire un\u2019elaborazione del segnale radar veloce, un beam-forming tri-dimensionale (3D) e quadri-dimensionale (4D) per la generazione di immagini radar e la stima delle informazioni dei bersagli, detti target. L\u2019idea `e di ottenere una stima completa, che includa la distanza, l\u2019Azimuth e l\u2019elevazione (addizionalmente Doppler come quarta di- mensione) dai target nelle acquisizioni radar. La tecnologia radar indagata ha lo scopo di affrontare diverse applicazioni civili e militari, come la sorveglianza e la rilevazione di targets, sia a livello aereo che a terra, e la consapevolezza situazionale, sia nelle auto che nelle piattaforme di volo, dagli elicotteri, ai Unmanned Aerial Vehicels (UAV) e taxi volanti (air-taxis). Le tematiche affrontante sono molte. Lo sviluppo di sistemi completi e di architetture digitali innovative, basate su tecnologia FPGA, ARM e software, per radar 3D MIMO, che operano in modalit`a Multiplexing Time Division Multiplexing (TDM) e Multiplexing Frequency Diversion (FDM), con segnali di tipo FMCW (Frequency Modulated Contin- uous Wave) e Orthogonal Frequency Division Multiplexing (OFDM), rispettivamente. Lo sviluppo di tecniche di elaborazione del segnale radar in tempo reale, algoritmi di beam-forming e di stima della direzione di arrivo, Direction-Of-Arrival (DOA), dei seg- nali radar, per il rilevamento dei target, con particolare attenzione a processi basati su trasformate di Fourier (FFT). Lo studio e l\u2019implementazione di concetti di sistema avan- zati, parametrizzazione e simulazione di radar digitali di prossima generazione, capaci di operare in tempo reale (ad esempio basati su architetture OFDM). Progettazione e sviluppo di nuove forme d\u2019onda ortogonali ad inviluppo costante per sistemi radar 3D di tipo OFDM MIMO, operanti in tempo reale. Le attivit`a di ricerca di questa tesi sono state svolte presso la compagnia Airbus, con sede a Monaco di Baviera (Germania), nell\u2019ambito di un programma di dottorato, svoltosi in maniera congiunta tra Airbus ed il Dipartimento Politecnico di Ingegneria e Architettura dell\u2019Universit`a di Udine, con sede a Udine

Estimation of Sparse MIMO Channels with Common Support

We consider the problem of estimating sparse communication channels in the MIMO context. In small to medium bandwidth communications, as in the current standards for OFDM and CDMA communication systems (with bandwidth up to 20 MHz), such channels are individually sparse and at the same time share a common support set. Since the underlying physical channels are inherently continuous-time, we propose a parametric sparse estimation technique based on finite rate of innovation (FRI) principles. Parametric estimation is especially relevant to MIMO communications as it allows for a robust estimation and concise description of the channels. The core of the algorithm is a generalization of conventional spectral estimation methods to multiple input signals with common support. We show the application of our technique for channel estimation in OFDM (uniformly/contiguous DFT pilots) and CDMA downlink (Walsh-Hadamard coded schemes). In the presence of additive white Gaussian noise, theoretical lower bounds on the estimation of SCS channel parameters in Rayleigh fading conditions are derived. Finally, an analytical spatial channel model is derived, and simulations on this model in the OFDM setting show the symbol error rate (SER) is reduced by a factor 2 (0 dB of SNR) to 5 (high SNR) compared to standard non-parametric methods - e.g. lowpass interpolation.Comment: 12 pages / 7 figures. Submitted to IEEE Transactions on Communicatio

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe