Novel irregular LDPC codes and their application to iterative detection of MIMO systems

Low-density parity-check (LDPC) codes are among the best performing error correction codes currently known. For higher performing irregular LDPC codes, degree distributions have been found which produce codes with optimum performance in the infinite block length case. Significant performance degradation is seen at more practical short block lengths. A significant focus in the search for practical LDPC codes is to find a construction method which minimises this reduction in performance as codes approach short lengths. In this work, a novel irregular LDPC code is proposed which makes use of the SPA decoder at the design stage in order to make the best choice of edge placement with respect to iterative decoding performance in the presence of noise. This method, a modification of the progressive edge growth (PEG) algorithm for edge placement in parity-check matrix (PCM) construction is named the DOPEG algorithm. The DOPEG design algorithm is highly flexible in that the decoder optimisation stage may be applied to any modification or extension of the original PEG algorithm with relative ease. To illustrate this fact, the decoder optimisation step was applied to the IPEG modification to the PEG algorithm, which produces codes with comparatively excellent performance. This extension to the DOPEG is called the DOIPEG. A spatially multiplexed coded iteratively detected and decoded multiple-input multiple-output (MIMO) system is then considered. The MIMO system to be investigated is developed through theory and a number of results are presented which illustrate its performance characteristics. The novel DOPEG code is tested for the MIMO system under consideration and a significant performance gain is achieved

Gemeinsame Kommunikation und Positionierung basierend auf Interleave-Division Multiplexing

Interest in joint communication and positioning is steadily increasing because the combination of both techniques offers a wide range of advantages. On the one hand, synergy effects between communication and positioning like enhanced resource allocation can be exploited. On the other hand, new applications are enabled. Examples comprise a wide area of interest and include the automated localisation of emergency calls, tracking and guiding fire fighters or policemen on a mission, monitoring people with special needs in a hospital or a nursing home, asset tracking, location-based services and so forth. However, it is a challenging task to combine communication and positioning because their prerequisites are quite different. On the one hand, high data rates with little training overhead and low bit error rate are desirable for communication. On the other hand, localisation aims at precise position estimates. Much training is typically spent for that purpose. Given a single transmit signal supporting communication as well as positioning, it is very difficult to fulfil all requirements at the same time. Hence, a flexible configuration is desirable for a joint communication and positioning system with a unified signal structure in order to adjust the tradeoff between both parts to the instantaneous needs. In this thesis, a new system concept for joint communication and positioning with a unified signal structure is proposed and investigated. The system concept is based on interleave-division multiplexing (IDM) in combination with pilot layer aided channel estimation (PLACE) and multilateration via the time of arrival (TOA). On the one hand, IDM seems to be a suitable candidate for a joint communication and positioning system because of its flexible but simple transmitter structure. On the other hand, multilateration via the TOA enables precise localisation. The connection between the communication and the positioning part is accomplished via an enhanced PLACE unit. Through the incorporation of a channel parameter estimator, not only the channel coefficients of the equivalent discrete-time channel model, that are needed for data detection, but also parameters of the physical channel, that are required for positioning, can be estimated. A priori information about pulse shaping and receive filtering is exploited for that purpose. The main aim of this thesis is to show the feasibility of the proposed joint communication and positioning system. Hence, a fundamental system setup is analysed systematically. Since many applications of joint communication and positioning are located in urban or indoor environments, a very high positioning accuracy in the centimetre region is desirable. Unfortunately, positioning is most challenging in these environments due to severe multipath propagation. In order to achieve the required accuracies, the positioning part of the proposed system concept can be complemented by other localisation sources like GPS/Galileo and/or motion sensors via sensor fusion. However, the stand-alone performance of the proposed joint communication and positioning system is evaluated by means of Monte Carlo simulations in this thesis. The achieved results are compared to performance limits in terms of Cramer-Rao lower bounds. In order to improve the overall system performance and to enable sensor fusion, soft information with respect to the parameter as well as the position estimates is taken into account. The accuracy of the soft information is analysed with the help of curvature measures. Altogether, promising results are obtained.Das Interesse an gemeinsamer Kommunikation und Positionierung nimmt aufgrund vieler Vorteile stetig zu: Durch die Kombination beider Techniken können Synergieeffekte wie beispielsweise eine verbesserte Ressourcenverteilung ausgenutzt werden. Des Weiteren werden neue Anwendungen in den unterschiedlichsten Bereichen ermöglicht: Notrufe können automatisch lokalisiert werden, Feuerwehrmänner und Polizisten im Einsatz können durch eine Verfolgung ihrer Position und gegebenenfalls eine Überwachung ihrer Vitalwerte besser angeleitet und koordiniert werden, Patienten mit speziellen Bedürfnissen in Krankenhäusern können durch ein effizientes Monitoring besser versorgt werden, Ein- und Auslagerungsprozesse in Warenhäusern können erleichtert werden, positionsbezogene Dienste können realisiert werden und vieles anderes mehr. Aufgrund der verschiedenen Anforderungen von Kommunikations- und Positionierungsdiensten ist es schwierig, diese beiden Bereiche zu vereinen. Einerseits sollen große Datenraten mit geringem Trainingsaufwand als auch geringen Bitfehlerraten erreicht werden. Andererseits ist eine hohe Positionierungsgenauigkeit erwünscht, die einen großen Trainingsaufwand erfordert. In einem Systementwurf mit einer einheitlichen Signalstruktur ist es schwer, alle Anforderungen gleichzeitig zu erfüllen. Daher ist ein flexibler Systementwurf von Vorteil, um den Abtausch zwischen Kommunikation und Positionierung an die aktuellen Bedürfnisse anpassen zu können. Im Rahmen dieser Arbeit wird ein neues gemeinsames Kommunikations- und Positionierungssystem mit einer einheitlichen Signalstruktur vorgeschlagen und untersucht. Der Systementwurf basiert auf Interleave-Division Multiplexing (IDM) in Kombination mit einer Pilotlayer basierten Kanalschätzung und Multilateration mit Hilfe der Signalankunftszeit, im Folgenden Time of Arrival (TOA) genannt. Einerseits ist IDM aufgrund seiner flexiblen, jedoch einfachen Senderstruktur gut für ein gemeinsames Kommunikations- und Positionierungssystem geeignet. Andererseits ermöglicht eine Multilateration mit Hilfe der TOA hohe Positionierungsgenauigkeiten. Die Verbindung zwischen beiden Komponenten wird durch eine erweiterte Pilotlayer basierte Kanalschätzung erreicht: Durch die Verwendung eines Kanalparameterschätzers können sowohl die Kanalkoeffizienten des äquivalenten zeitdiskreten Ersatzkanalmodells, die für die Datendetektion benötigt werden, als auch Parameter des physikalischen Kanals, die für die Lokalisierung erforderlich sind, geschätzt werden. A priori Information bezüglich des Pulsformungs- und Empfangsfilters werden hierfür ausgenutzt. Das Hauptziel dieser Arbeit ist es, die Realisierbarkeit des vorgeschlagenen gemeinsamen Kommunikations- und Positionierungssystems zu zeigen. Daher wird ein grundlegender Systementwurf systematisch analysiert. Da viele Anwendungen von gemeinsamer Kommunikation und Positionierung innerhalb von Städten oder Gebäuden angesiedelt sind, ist eine sehr hohe Positionierungsgenauigkeit im Zentimeter-Bereich wünschenswert. Unglücklicherweise ist es in diesen Gebieten aufgrund von starker Mehrwegeausbreitung besonders schwer, die Position eines Objektes zu bestimmen. Allerdings kann die Positionierungskomponente durch andere Lokalisierungsquellen wie beispielsweise GPS/Galileo und/oder Bewegungssensoren mittels Sensorfusion ergänzt werden, um die erforderlichen Genauigkeiten zu erreichen. In Rahmen dieser Arbeit wird jedoch nur die eigenständige Leistungsfähigkeit des vorgeschlagenen Systementwurfs mit Hilfe von Monte Carlo Simulationen untersucht. Die Simulationsergebnisse werden mit Leistungsgrenzen in Form von Cramer-Rao Untergrenzen verglichen. Dabei wird Zuverlässigkeitsinformation bezüglich der geschätzten Parameter und der geschätzten Position berücksichtigt, um die gesamte Systemleistung zu verbessern und Sensorfusion zu ermöglichen. Die Genauigkeit der Zuverlässigkeitsinformation wird mit Hilfe von Krümmungsmaßen analysiert. Insgesamt werden vielversprechende Ergebnisse erzielt

Joint Communication and Positioning based on Channel Estimation

Mobile wireless communication systems have rapidly and globally become an integral part of everyday life and have brought forth the internet of things. With the evolution of mobile wireless communication systems, joint communication and positioning becomes increasingly important and enables a growing range of new applications. Humanity has already grown used to having access to multimedia data everywhere at every time and thereby employing all sorts of location-based services. Global navigation satellite systems can provide highly accurate positioning results whenever a line-of-sight path is available. Unfortunately, harsh physical environments are known to degrade the performance of existing systems. Therefore, ground-based systems can assist the existing position estimation gained by satellite systems. Determining positioning-relevant information from a unified signal structure designed for a ground-based joint communication and positioning system can either complement existing systems or substitute them. Such a system framework promises to enhance the existing systems by enabling a highly accurate and reliable positioning performance and increased coverage. Furthermore, the unified signal structure yields synergetic effects. In this thesis, I propose a channel estimation-based joint communication and positioning system that employs a virtual training matrix. This matrix consists of a relatively small training percentage, plus the detected communication data itself. Via a core semi- blind estimation approach, this iteratively includes the already detected data to accurately determine the positioning-relevant parameter, by mutually exchanging information between the communication part and the positioning part of the receiver. Synergy is created. I propose a generalized system framework, suitable to be used in conjunction with various communication system techniques. The most critical positioning-relevant parameter, the time-of-arrival, is part of a physical multipath parameter vector. Estimating the time-of-arrival, therefore, means solving a global, non-linear, multi-dimensional optimization problem. More precisely, it means solving the so-called inverse problem. I thoroughly assess various problem formulations and variations thereof, including several different measurements and estimation algorithms. A significant challenge, when it comes to solving the inverse problem to determine the positioning-relevant path parameters, is imposed by realistic multipath channels. Most parameter estimation algorithms have proven to perform well in moderate multipath environments. It is mathematically straightforward to optimize this performance in the sense that the number of observations has to exceed the number of parameters to be estimated. The typical parameter estimation problem, on the other hand, is based on channel estimates, and it assumes that so-called snapshot measurements are available. In the case of realistic channel models, however, the number of observations does not necessarily exceed the number of unknowns. In this thesis, I overcome this problem, proposing a method to reduce the problem dimensionality via joint model order selection and parameter estimation. Employing the approximated and estimated parameter covariance matrix inherently constrains the estimation problem’s model order selection to result in optimal parameter estimation performance and hence optimal positioning performance. To compare these results with the optimally achievable solution, I introduce a focused order-related lower bound in this thesis. Additionally, I use soft information as a weighting matrix to enhance the positioning algorithm positioning performance. For demonstrating the feasibility and the interplay of the proposed system components, I utilize a prototype system, based on multi-layer interleave division multiple access. This proposed system framework and the investigated techniques can be employed for multiple existing systems or build the basis for future joint communication and positioning systems. The assessed estimation algorithms are transferrable to all kinds of joint communication and positioning system designs. This thesis demonstrates their capability to, in principle, successfully cope with challenging estimation problems stemming from harsh physical environments

Journal of Telecommunications and Information Technology, 2001, nr 3

kwartalni

Channel estimation techniques for filter bank multicarrier based transceivers for next generation of wireless networks

A dissertation submitted to Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical and Information Engineering), August 2017The fourth generation (4G) of wireless communication system is designed based on the principles of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) where the cyclic prefix (CP) is used to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) in order to achieve higher data rates in comparison to the previous generations of wireless networks. Various filter bank multicarrier systems have been considered as potential waveforms for the fast emerging next generation (xG) of wireless networks (especially the fifth generation (5G) networks). Some examples of the considered waveforms are orthogonal frequency division multiplexing with offset quadrature amplitude modulation based filter bank, universal filtered multicarrier (UFMC), bi-orthogonal frequency division multiplexing (BFDM) and generalized frequency division multiplexing (GFDM). In perfect reconstruction (PR) or near perfect reconstruction (NPR) filter bank designs, these aforementioned FBMC waveforms adopt the use of well-designed prototype filters (which are used for designing the synthesis and analysis filter banks) so as to either replace or minimize the CP usage of the 4G networks in order to provide higher spectral efficiencies for the overall increment in data rates. The accurate designing of the FIR low-pass prototype filter in NPR filter banks results in minimal signal distortions thus, making the analysis filter bank a time-reversed version of the corresponding synthesis filter bank. However, in non-perfect reconstruction (Non-PR) the analysis filter bank is not directly a time-reversed version of the corresponding synthesis filter bank as the prototype filter impulse response for this system is formulated (in this dissertation) by the introduction of randomly generated errors. Hence, aliasing and amplitude distortions are more prominent for Non-PR. Channel estimation (CE) is used to predict the behaviour of the frequency selective channel and is usually adopted to ensure excellent reconstruction of the transmitted symbols. These techniques can be broadly classified as pilot based, semi-blind and blind channel estimation schemes. In this dissertation, two linear pilot based CE techniques namely the least square (LS) and linear minimum mean square error (LMMSE), and three adaptive channel estimation schemes namely least mean square (LMS), normalized least mean square (NLMS) and recursive least square (RLS) are presented, analyzed and documented. These are implemented while exploiting the near orthogonality properties of offset quadrature amplitude modulation (OQAM) to mitigate the effects of interference for two filter bank waveforms (i.e. OFDM/OQAM and GFDM/OQAM) for the next generation of wireless networks assuming conditions of both NPR and Non-PR in slow and fast frequency selective Rayleigh fading channel. Results obtained from the computer simulations carried out showed that the channel estimation schemes performed better in an NPR filter bank system as compared with Non-PR filter banks. The low performance of Non-PR system is due to the amplitude distortion and aliasing introduced from the random errors generated in the system that is used to design its prototype filters. It can be concluded that RLS, NLMS, LMS, LMMSE and LS channel estimation schemes offered the best normalized mean square error (NMSE) and bit error rate (BER) performances (in decreasing order) for both waveforms assuming both NPR and Non-PR filter banks. Keywords: Channel estimation, Filter bank, OFDM/OQAM, GFDM/OQAM, NPR, Non-PR, 5G, Frequency selective channel.CK201

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression