15 research outputs found

    Advanced low-complexity multiuser receivers

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    It tema centrale di questa tesi è la rivelazione multi-utente per sistemi di comunicazione wireless ad elevata efficienza spettrale. Lo scopo del lavoro è quello di proporre nuovi ricevitori multi-utente a bassa complessità con elevate prestazioni. Sono considerati sistemi satellitari basati su FDM (Frequency Division Multiplexing), in cui ogni utente adotta una modulazione CPM (Continuous Phase Modulation) concatenata serialmente con un codificatore tramite un interlacciatore e decodifica iterativa. Si considerano, inoltre, canali lineari in presenza di AWGN (additive white Gaussian noise). In particolare, si studiano sistemi FDM, in cui i canali adiacenti possono sovrapporsi in frequenza per aumentere l'efficienza spettrale, e sistemi CDMA (code division multiple access). Per gli scenari presi in esame, proponiamo schemi di rivelazione con un eccellente compromesso tra prestazioni e complessità computazionale, che permettono di implementare schemi di trasmissione con straordinaria efficienza spettrale, al prezzo di un limitato aumento di complessità rispetto ad un classico ricevitore singolo-utente che ignora l'interferenza.This thesis deals with multiuser detection (MUD) for spectrally-efficient wireless communication systems. The aim of this work is to propose new advanced low-complexity multiuser receivers with near-optimal detection performance. We consider frequency division multiplexing (FDM) satellite systems where each user employs a continuous phase modulation (CPM), serially concatenated with an outer code through an interleaver, and iterative detection/decoding. We also consider linear channels impaired by additive white Gaussian noise (AWGN), focusing on FDM systems where adjacent channels are allowed to overlap in frequency, and on code division multiple access systems (CDMA). For the considered scenarios, we propose detection schemes with an excel- lent performance/complexity tradeoff which allow us to implement transmission schemes with unprecedented spectral efficiency at a price of a limited complexity increase with respect to a classical single-user receiver which neglects the interference

    Sparse graph-based coding schemes for continuous phase modulations

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    The use of the continuous phase modulation (CPM) is interesting when the channel represents a strong non-linearity and in the case of limited spectral support; particularly for the uplink, where the satellite holds an amplifier per carrier, and for downlinks where the terminal equipment works very close to the saturation region. Numerous studies have been conducted on this issue but the proposed solutions use iterative CPM demodulation/decoding concatenated with convolutional or block error correcting codes. The use of LDPC codes has not yet been introduced. Particularly, no works, to our knowledge, have been done on the optimization of sparse graph-based codes adapted for the context described here. In this study, we propose to perform the asymptotic analysis and the design of turbo-CPM systems based on the optimization of sparse graph-based codes. Moreover, an analysis on the corresponding receiver will be done

    Turbo multiuser detection with integrated channel estimation for differentially coded CDMA systems.

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    Capacity -based parameter optimization of bandwidth constrained CPM

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    Continuous phase modulation (CPM) is an attractive modulation choice for bandwidth limited systems due to its small side lobes, fast spectral decay and the ability to be noncoherently detected. Furthermore, the constant envelope property of CPM permits highly power efficient amplification. The design of bit-interleaved coded continuous phase modulation is characterized by the code rate, modulation order, modulation index, and pulse shape. This dissertation outlines a methodology for determining the optimal values of these parameters under bandwidth and receiver complexity constraints. The cost function used to drive the optimization is the information-theoretic minimum ratio of energy-per-bit to noise-spectral density found by evaluating the constrained channel capacity. The capacity can be reliably estimated using Monte Carlo integration. A search for optimal parameters is conducted over a range of coded CPM parameters, bandwidth efficiencies, and channels. Results are presented for a system employing a trellis-based coherent detector. To constrain complexity and allow any modulation index to be considered, a soft output differential phase detector has also been developed.;Building upon the capacity results, extrinsic information transfer (EXIT) charts are used to analyze a system that iterates between demodulation and decoding. Convergence thresholds are determined for the iterative system for different outer convolutional codes, alphabet sizes, modulation indices and constellation mappings. These are used to identify the code and modulation parameters with the best energy efficiency at different spectral efficiencies for the AWGN channel. Finally, bit error rate curves are presented to corroborate the capacity and EXIT chart designs

    Synchronisation, détection et égalisation de modulation à phase continue dans des canaux sélectifs en temps et en fréquence

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    Si les drones militaires connaissent un développement important depuis une quinzaine d’année, suivi depuis quelques années par les drones civiles dont les usages ne font que se multiplier, en réalité les drones ont un siècle avec le premier vol d’un avion équipé d’un système de pilotage automatique sur une centaine de kilomètre en 1918. La question des règles d’usage des drones civiles sont en cours de développement malgré leur multiplication pour des usages allant de l’agriculture, à l’observation en passant par la livraison de colis. Ainsi, leur intégration dans l’espace aérien reste un enjeu important, ainsi que les standards de communication avec ces drones dans laquelle s’inscrit cette thèse. Cette thèse vise en effet à étudier et proposer des solutions pour les liens de communications des drones par satellite.L’intégration de ce lien de communication permet d’assurer la fiabilité des communications et particulièrement du lien de Commande et Contrôle partout dans le monde, en s’affranchissant des contraintes d’un réseau terrestre (comme les zones blanches). En raison de la rareté des ressources fréquentielles déjà allouées pour les futurs systèmes intégrant des drones, l’efficacité spectrale devient un paramètre important pour leur déploiement à grande échelle et le contexte spatiale demande l’utilisation d’un système de communication robuste aux non-linéarités. Les Modulations à Phase Continue permettent de répondre à ces problématiques. Cependant, ces dernières sont des modulations non-linéaire à mémoire entraînant une augmentation de la complexité des récepteurs. Du fait de la présence d’un canal multi-trajet (canal aéronautique par satellite), le principal objectif de cette thèse est de proposer des algorithmes d’égalisation (dans le domaine fréquentiel pour réduire leur complexité) et de synchronisation pour CPM adaptés à ce concept tout en essayant de proposer une complexité calculatoire raisonnable. Dans un premier temps, nous avons considéré uniquement des canaux sélectifs en fréquence et avons étudier les différents égaliseurs de la littérature. En étudiant leur similitudes et différences, nous avons pu développer un égaliseur dans le domaine fréquentiel qui proposant les mêmes performances a une complexité moindre. Nous proposons également des méthodes d’estimation canal et une méthode d’estimation conjointe du canal et de la fréquence porteuse. Dans un second temps nous avons montré comment étendre ces méthodes à des canaux sélectifs en temps et fréquence permettant ainsi de conserver une complexité calculatoire raisonnable

    Adaptive iterative decoding : block turbo codes and multilevel codes

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    New adaptive, iterative approaches to the decoding of block Turbo codes and multilevel codes are developed. Block Turbo codes are considered as they can readily provide high data rates, low decoding complexity and good performance. Multilevel codes are considered as they provide a moderate complexity approach to a high complexity code and can provide codes with good bandwidth efficiency. The work develops two adaptive sub-optimal soft output decoding algorithms for block Turbo codes. One is based on approximation and the other on the distance properties of the component codes. They can be used with different codes, modulation schemes, channel conditions and in different applications without modification. Both approaches provide improved performance compared to previous approaches on the additive white Gaussian noise (AWGN) channel. The approximation based adaptive algorithm is also investigated on the uncorrelated Rayleigh fiat fading channel and is shown to improve performance over previous approaches. Multilevel codes are typically decoded using a multistage decoder (MSD) for complexity reasons. Each level passes hard decisions to subsequent levels. If the approximation based adaptive algorithm is used to decode component codes in a traditional MSD it improves performance significantly. Performance can be improved further by passing reliability (extrinsic) information to all previous and subsequent levels using an iterative MSD. A new iterative multistage decoding algorithm for multilevel codes is developed by treating the extrinsic information as a Gaussian random variable. If the adaptive algorithms are used in conjunction with iterative multistage decoding on the AWGN channel, then a significant improvement in performance is obtained compared to results using a traditional MSD

    Adaptive multiple symbol decision feedback for non-coherent detection.

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    Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2006.Non-coherent detection is a simple form of signal detection and demodulation for digital communications. The main drawback of this detection method is the performance penalty incurred, since the channel state information is not known at the receiver. Multiple symbol detection (MSD) is a technique employed to close the gap between coherent and non-coherent detection schemes. Differentially encoded JW-ary phase shift keying (DM-PSK) is the classic modulation technique that is favourable for non-coherent detection. The main drawback for standard differential detection (SDD) has been the error floor incurred for frequency flat fading channels. Recently a decision feedback differential detection (DFDD) scheme, which uses the concept of MSD was proposed and offered significant performance gain over the SDD in the mobile flat fading channel, almost eliminating the error floor. This dissertation investigates multiple symbol decision feedback detection schemes, and proposes alternate adaptive strategies for non-coherent detection. An adaptive algorithm utilizing the numerically stable QR decomposition that does not require training symbols is proposed, named QR-DFDD. The QR-DFDD is modified to use a simpler QR decomposition method which incorporates sliding windows: QRSW-DFDD. This structure offers good tracking performance in flat fading conditions, while achieving near optimal DFDD performance. A bit interleaved coded decision feedback differential demodulation (DFDM) scheme, which takes advantage of the decision feedback concept and iterative decoding, was introduced by Lampe in 2001. This low complexity iterative demodulator relied on accurate channel statistics for optimal performance. In this dissertation an alternate adaptive DFDM is introduced using the recursive least squares (RLS) algorithm. The alternate iterative decoding procedure makes use of the convergence properties of the RLS algorithm that is more stable and achieves superior performance compared to the DFDM

    On Trellis-Based Truncated-Memory Detection

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    Iterative Detection for Overloaded Multiuser MIMO OFDM Systems

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    Inspired by multiuser detection (MUD) and the ‘Turbo principle’, this thesis deals with iterative interference cancellation (IIC) in overloaded multiuser multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Linear detection schemes, such as zero forcing (ZF) and minimum mean square error (MMSE) cannot be used for the overloaded system because of the rank deficiency of channel matrix, while the optimal approach, the maximum likelihood (ML) detection has high computational complexity. In this thesis, an iterative interference cancellation (IIC) multiuser detection scheme with matched filter and convolutional codes is considered. The main idea of this combination is a low complexity receiver. Parallel interference cancellation (PIC) is employed to improve the multiuser receiver performance for overloaded systems. A log-likelihood ratio (LLR) converter is proposed to further improve the reliability of the soft value converted from the output of the matched filter. Simulation results show that the bit error rate (BER) performance of this method is close to the optimal approach for a two user system. However, for the four user or more user system, it has an error floor of the BER performance. For this case, a channel selection scheme is proposed to distinguish whether the channel is good or bad by using the mutual information based on the extrinsic information transfer (EXIT) chart. The mutual information can be predicted in a look-up table which greatly reduces the complexity. For those ‘bad’ channels identified by the channel selection, we introduce two adaptive transmission methods to deal with such channels: one uses a lower code rate, and the other is multiple transmissions. The use of an IIC receiver with the interleave-division multiple access (IDMA) to further improve the BER performance without any channel selection is also investigated. It has been shown that this approach can remove the error floor. Finally, the influence of channel accuracy on the IIC is investigated. Pilot-based Wiener filter channel estimation is used to test and verify how much the IIC is influenced by the channel accuracy
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