This dissertation focuses on quantifying the effects of multi-user co-channel interference for an avionic communication system operating in a heavy-traffic aeronautical mobile environment and proposes advanced interference cancellation techniques to mitigate the interference. The dissertation consists of two parts. The first part of the work investigates the use of a visualization method to quantify and characterize the multi-user co-channel interference (multiple access interference) effects impinging on an avionic communication system. The interference is caused by complex interactions of thousands of RF signals transmitted from thousands of aircraft; each attempts to access a common communication channel, which is governed by a specific channel contention access protocol. The visualization method transforms the co-channel interference, which is specified in terms of signal-overlaps (signal collisions), from a visual representation to a matrix representation for further statistical analysis. It is found that the statistical Poisson and its cumulative distribution provide the best estimates of multi-user co-channel interference. It is shown, using Monte Carlo simulation, that the co-channel interference of a victim aircraft operating in the heavy-traffic environment could result in as high as eight signal-overlaps. This constitutes to approximately 83.4% of success rate in signal detection for the entire three thousand aircraft environment using conventional FSK receiver. One key finding shows that high-quality communications, up to 98.5% success rate, is achievable if only three overlapping signals can be decoded successfully. The interference results found in the first part set the stage for interference cancellation research in the second part. The second part of the work proposes the use of advanced interference cancellation techniques, namely sequential interference cancellation (SIC) and parallel interference cancellation (PIC), as potential solutions to mitigating the interference effects. These techniques can be implemented in radio receivers to perform multi-signal decoding functionality to remove the required interferers (three overlapping signals) so that high-quality communication, as described in the first part, can be achieved. Various performance graphs are shown for B-FSK and B-PSK for both SIC and PIC techniques. One key finding is that the system performance can be improved substantially to an additional 15% in signal reception success rate by using SIC or PIC. This means that critical information transmitted from 450 aircraft (out of approximately three thousand aircraft in the environment) is preserved and successfully decoded. Multi-signal decoding using these interference cancellation receivers comes at a small penalty of 2 - 4.5 dBs in Eb/No when sufficient signal-to-interference (SIR) ratio (7-12 dB) is provided. / Ph. D.

L’optimisation des communications par satellite devient un enjeu crucial pour fournir un accèsInternet aux zones blanches et/ou défavorisées et pour supporter des réseaux à grande échelle.Dans ce contexte, l’utilisation des techniques d’accès aléatoires sur le lien retour permetd’améliorer les performances de ces systèmes. Cependant, les techniques d’accès aléatoireclassiques comme ‘Aloha’ et ‘Slotted Aloha’ ne sont pas optimales pour la transmission dedonnées sur le lien retour. En effet, ces techniques présentent un taux élevé de pertes depaquets suite aux collisions. Par conséquent, des études récentes ont proposé de nouvellesméthodes d’accès aléatoire pour résoudre les collisions entre les paquets et ainsi, améliorerles performances. En particulier, ces méthodes se basent sur la redondance de l’informationet l’annulation successive des interférences. Dans ces systèmes, l’estimation de canal sur le lien retour est un problème difficile en raison du haut niveau de collisions de paquets. Dans une première contribution dans cette thèse, nous décrivons une technique améliorée d’estimation de canal pour les paquets en collision. Par ailleurs, nous analysons l’impact des erreurs résiduelles d’estimation de canal sur la performance des annulations successives des interférences. Même si les résultats obtenus sont encore légèrement inférieurs au cas de connaissance parfaite du canal, on observe une amélioration significative des performances par rapport aux algorithmes d’estimation de canal existants. Une autre contribution de cette thèse présente une méthode appelée ‘Multi-Replica Decoding using Correlation based Localisation’ (MARSALA). Celle-ci est une nouvelle technique de décodage pour la méthode d’accès aléatoire synchrone ‘Contention Résolution diversité Slotted Aloha’ (CRDSA), qui est basée sur les principe de réplication de paquets et d’annulation successive des interférences. Comparée aux méthodes d’accès aléatoire traditionnelles, CRDSA permet d’améliorer considérablement les performances. Toutefois, le débit offert par CRDSA peut être limité à cause des fortes collisions de paquets. L’utilisation deMARSALA par le récepteur permet d’améliorer les résultats en appliquant des techniques de corrélation temporelles pour localiser et combiner les répliques d’un paquet donné. Cette procédure aboutit à des gains en termes de débit et de taux d’erreurs paquets. Néanmoins, le gain offert par MARSALAest fortement dépendant de la synchronisation en temps et en phase des répliques d’un mêmepaquet. Dans cette thèse, nous détaillons le fonctionnement de MARSALA afin de corriger ladésynchronisation en temps et en phase entre les répliques. De plus, nous évaluons l’impactde la combinaison imparfaite des répliques sur les performances, en fournissant un modèle analytique ainsi que des résultats de simulation. En outre, plusieurs schémas d’optimisationde MARSALA sont proposés tels que le principe du ‘MaximumRatio Combining’, ou la transmissiondes paquets à des puissances différentes. Utilisées conjointement, ces différentespropositions permettent d’obtenir une amélioration très significative des performances. Enfin,nous montrons qu’en choisissant la configuration optimale pour MARSALA, le gain deperformance est considérablement amélioré. / With the need to provide the Internet access to deprived areas and to cope with constantlyenlarging satellite networks, enhancing satellite communications becomes a crucial challenge.In this context, the use of Random Access (RA) techniques combined with dedicated accesson the satellite return link, can improve the system performance. However conventionalRA techniques like Aloha and Slotted Aloha suffer from a high packet loss rate caused bydestructive packet collisions. For this reason, those techniques are not well-suited for datatransmission in satellite communications. Therefore, researchers have been studying andproposing new RA techniques that can cope with packet collisions and decrease the packet lossratio. In particular, recent RA techniques involving information redundancy and successiveinterference cancellation, have shown some promising performance gains.With such methods that can function in high load regimes and resolve packets with high collisions,channel estimation is not an evident task. As a first contribution in this dissertation, wedescribe an improved channel estimation scheme for packets in collision in new RAmethodsin satellite communications. And we analyse the impact of residual channel estimation errorson the performance of interference cancellation. The results obtained show a performancedegradation compared to the perfect channel knowledge case, but provide a performanceenhancement compared to existing channel estimation algorithms. Another contribution of this thesis is presenting a method called Multi-Replica Decoding using Correlation based Localisation (MARSALA). MARSALA is a new decoding technique for a recent synchronous RAmethod called Contention Resolution Diversity Slotted Aloha (CRDSA). Based on packets replication and successive interference cancellation, CRDSA enables to significantly enhance the performance of legacy RA techniques. However, if CRDSA is unable to resolve additional packets due to high levels of collision, MARSALA is applied. At the receiver side, MARSALA takes advantage of correlation procedures to localise the replicas of a given packet, then combines the replicas in order to obtain a better Signal to Noise plus Interference Ratio. Nevertheless, the performance ofMARSALA is highly dependent on replicas synchronisation in timing and phase, otherwise replicas combination would not be constructive. In this dissertation, we describe an overall framework ofMARSALA including replicas timing and phase estimation and compensation, then channel estimation for theresulting signal. This dissertation also provides an analytical model for the performancedegradation of MARSALA due to imperfect replicas combination and channel estimation.In addition, several enhancement schemes forMARSALA are proposed likeMaximum RatioCombining, packets power unbalance, and various coding schemes. Finally, we show thatby choosing the optimal design configuration for MARSALA, the performance gain can besignificantly enhanced.

Τα ασύρματα συστήματα πολλαπλών κεραιών MIMO αποτελούν ένα από τα βασικά μέτωπα ανάπτυξης των τηλεπικοινωνιών. Ωστόσο η εξαιρετικά τυχαία φύση τους καθώς και η αλληλεπίδραση μεταξύ των πολλαπλών ροών δεδομένων επιβάλει την χρήση σύγχρονων τεχνικών ισοστάθμισης. Η προσαρμοστική ισοστάθμιση στο δέκτη ενός τηλεπικοινωνιακού συστήματος χρησιμοποιείται για την αντιμετώπιση της δυναμικής φύσης του ασύρματου καναλιού και την ανίχνευση των αλλαγών στα χαρακτηριστικά του. Επίσης, μη γραμμικές τεχνικές ισοστάθμισης ανατροφοδότησης συμβόλων είναι απαραίτητες για την απομάκρυνση της διασυμβολικής παρεμβολής που παρουσιάζεται στα συγκεκριμένα συστήματα. Η παρούσα εργασία ασχολείται με μεθόδους προσαρμοστικής ισοστάθμισης στο δέκτη ενός τηλεπικοινωνιακού συστήματος. Διακρίνουμε τις εξής περιπτώσεις προσαρμοστικών αλγορίθμων για την ελαχιστοποίηση του σφάλματος, του αλγορίθμου Αναδρομικών Ελαχίστων Τετραγώνων (RLS), του επαναληπτικού αλγορίθμου Συζυγών Κλίσεων (CG) και του επαναληπτικού αλγορίθμου τροποποιημένων Συζυγών Κλίσεων (MCG). Όπως διαπιστώνουμε, όταν οι παραπάνω αλγόριθμοι χρησιμοποιηθούν με γραμμικές τεχνικές ισοστάθμισης έχουμε πολύ αργή σύγκλιση και γενικά υψηλό όριο σφάλματος. Συμπεραίνουμε λοιπόν ότι, προκειμένου να έχουμε γρήγορη σύγκλιση των προσαρμοστικών αλγορίθμων και αντιμετώπιση της διασυμβολικής παρεμβολής για τα συστήματα MIMO, είναι απαραίτητη η χρήση μη γραμμικών τεχνικών ισοστάθμισης. Αρχικά χρησιμοποιούμε την μέθοδο της γενικευμένης ανατροφοδότησης συμβόλων GDFE ενώ στη συνέχεια μελετάμε μία σύγχρονη τεχνική ανατροφοδότησης συμβόλων που χρησιμοποιεί ένα κριτήριο διάταξης για την ακύρωση των συμβόλων (OSIC ή V-BLAST). Όπως διαπιστώνεται και από τις εξομοιώσεις η συγκεκριμένη τεχνική επιτυγχάνει το χαμηλότερο όριο σφάλματος, αλλά με αυξημένο υπολογιστικό κόστος. Επίσης, διαπιστώνουμε ότι η εφαρμογή της τεχνικής αυτής με χρήση του τροποποιημένου αλγορίθμου Συζυγών Κλίσεων δεν είναι εφικτή. Στα πλαίσια αυτής της εργασίας, περιγράφουμε μια συγκεκριμένη υλοποίηση της τεχνικής διατεταγμένης ακύρωσης που κάνει χρήση του αλγορίθμου Αναδρομικών Ελαχίστων Τετραγώνων με μειωμένη πολυπλοκότητα. Στη συνέχεια γενικεύουμε την εφαρμογή της για την περίπτωση των αλγορίθμων Συζυγών Κλίσεων, και διαπιστώνουμε ότι ο τροποποιημένος αλγόριθμος Συζυγών Κλίσεων δεν μπορεί να χρησιμοποιηθεί ούτε σε αυτήν την περίπτωση. Για την υλοποίηση ενός συστήματος OSIC με χρήση του αλγορίθμου Συζυγών Κλίσεων είναι απαραίτητη η χρήση ενός αλγορίθμου που δεν έχει χρονική εξάρτηση σύγκλισης, όπως είναι ο βασικός αλγόριθμος Συζυγών Κλίσεων. / Wireless systems with multiple antenna configurations has recently emerged as one of the most significant technical breaktroughs in modern communications. However, because of the extremly random nature of the wireless channels, we have to use modern equalization methods in order to defeat the signal degradation. Adaptive equalization at the receiver of the telecommunication system can be used to compete this dynamic nature of the wireless channel and track the changes of its characteristics. Furthermore, nonlinear decision feedback methods are nessesary for the cancellation of the intersymbol interference which occurs with these systems. This work involves with adaptive equalization methods at the receiver of the telecommunication system. We use the following adaptive algorithms so as to minimize the error : the Recursive Least Squares algorithm (RLS), the iterative Conjugate Gradient algorithm (CG) and the iterative Modified Conjugate Gradient algorithm (MCG). When these algorithms are used with linear methods, they give very slow converge and high final error. So, it is neccessary to use nonlinear equalization methods in order to succeed fast converge rate and deal with the increazed intersymbol interference for MIMO systems. Firstly we use the generalized decision feedback method (GDFE), and then the modern method of ordered successive cancellation method (OSIC or V-BLAST). Based on the emulations we conclude that the last method succeed the lower error, but with high computational cost. Furthermore, we can't use OSIC method with Modified Conjugate Gradient algorithm. In this work, we describe a specific implementation of the OSIC method which uses RLS algorithm with low computational complexity. So we generalize its usage with the Conjugate Gradient algorithms. Finaly, we conclude that we can't also use MCG with OSIC method with low computational complexity. In order to construct an OSIC system based on Conjugate Gradient algorithm, the algorithm must not operate on time basis, like basic Conjugate Gradient algorithm does.

Wireless communications rely, among other things, on theunderstanding of the properties of the radio propagationchannel, the antennas and their interplay. Adequate measurementsare required to verify theoretical models and togain knowledge of the channel behavior and antenna performance.As a result of this master thesis we built a 3D fieldscanner measurement system to predict multipath propagationand to measure antenna characteristics. The 3Dscanner allows measuring a signal at the point of interestalong a line, on a surface or within a volume in space. In orderto evaluate the system, we have performed narrowbandchannel sounding measurements of the spatial distributionof waves impinging at an imaginary spherical sector. Datawas used to estimate the Angle-of-Arrivals (AoA) and amplitudeof the waves. An estimation method is presented tosolve the resulting inverse problem by means of regularizationwith truncated singular value decomposition. The regularizedsolution was then further improved with the helpof a successive interference cancellation algorithm. Beforeapplying the method to measurement data, it was testedon synthetic data to evaluate its performance as a functionof the noise level and the number of impinging waves. Inorder to minimize estimation errors it was also required tofind the phase center of the horn antenna used in the channelmeasurements. The task was accomplished by directmeasurements and by the regularization method, both resultsbeing in good agreement.

The search for the closest lattice point arises in many communication problems, and is known to be NP-hard. The Maximum Likelihood (ML) Detector is the optimal detector which yields an optimal solution to this problem, but at the expense of high computational complexity. Existing near-optimal methods used to solve the problem are based on the Sphere Decoder (SD), which searches for lattice points confined in a hyper-sphere around the received point. The SD has emerged as a powerful means of finding the solution to the ML detection problem for MIMO systems. However the bottleneck lies in the determination of the initial radius. This thesis is concerned with the detection of transmitted wireless signals in Multiple-Input Multiple-Output (MIMO) digital communication systems as efficiently and effectively as possible. The main objective of this thesis is to design efficient ML detection algorithms for MIMO systems based on the depth-first search (DFS) algorithms whilst taking into account complexity and bit error rate performance requirements for advanced digital communication systems. The increased capacity and improved link reliability of MIMO systems without sacrificing bandwidth efficiency and transmit power will serve as the key motivation behind the study of MIMO detection schemes. The fundamental principles behind MIMO systems are explored in Chapter 2. A generic framework for linear and non-linear tree search based detection schemes is then presented Chapter 3. This paves way for different methods of improving the achievable performance-complexity trade-off for all SD-based detection algorithms. The suboptimal detection schemes, in particular the Minimum Mean Squared Error-Successive Interference Cancellation (MMSE-SIC), will also serve as pre-processing as well as comparison techniques whilst channel capacity approaching Low Density Parity Check (LDPC) codes will be employed to evaluate the performance of the proposed SD. Numerical and simulation results show that non-linear detection schemes yield better performance compared to linear detection schemes, however, at the expense of a slight increase in complexity. The first contribution in this thesis is the design of a near ML-achieving SD algorithm for MIMO digital communication systems that reduces the number of search operations within the sphere-constrained search space at reduced detection complexity in Chapter 4. In this design, the distance between the ML estimate and the received signal is used to control the lower and upper bound radii of the proposed SD to prevent NP-complete problems. The detection method is based on the DFS algorithm and the Successive Interference Cancellation (SIC). The SIC ensures that the effects of dominant signals are effectively removed. Simulation results presented in this thesis show that by employing pre-processing detection schemes, the complexity of the proposed SD can be significantly reduced, though at marginal performance penalty. The second contribution is the determination of the initial sphere radius in Chapter 5. The new initial radius proposed in this thesis is based on the variable parameter α which is commonly based on experience and is chosen to ensure that at least a lattice point exists inside the sphere with high probability. Using the variable parameter α, a new noise covariance matrix which incorporates the number of transmit antennas, the energy of the transmitted symbols and the channel matrix is defined. The new covariance matrix is then incorporated into the EMMSE model to generate an improved EMMSE estimate. The EMMSE radius is finally found by computing the distance between the sphere centre and the improved EMMSE estimate. This distance can be fine-tuned by varying the variable parameter α. The beauty of the proposed method is that it reduces the complexity of the preprocessing step of the EMMSE to that of the Zero-Forcing (ZF) detector without significant performance degradation of the SD, particularly at low Signal-to-Noise Ratios (SNR). More specifically, it will be shown through simulation results that using the EMMSE preprocessing step will substantially improve performance whenever the complexity of the tree search is fixed or upper bounded. The final contribution is the design of the LRAD-MMSE-SIC based SD detection scheme which introduces a trade-off between performance and increased computational complexity in Chapter 6. The Lenstra-Lenstra-Lovasz (LLL) algorithm will be utilised to orthogonalise the channel matrix H to a new near orthogonal channel matrix H ̅.The increased computational complexity introduced by the LLL algorithm will be significantly decreased by employing sorted QR decomposition of the transformed channel H ̅ into a unitary matrix and an upper triangular matrix which retains the property of the channel matrix. The SIC algorithm will ensure that the interference due to dominant signals will be minimised while the LDPC will effectively stop the propagation of errors within the entire system. Through simulations, it will be demonstrated that the proposed detector still approaches the ML performance while requiring much lower complexity compared to the conventional SD.

[pt] Na primeira parte desta tese, são desenvolvidos dois esquemas de detecção por listas para sistemas MIMO multiusuário. As técnicas propostas usam uma única transformação de redução de reticulado (LR) para modificar a matriz de canal entre os usuários e a estação base (BS). Após a transformação LR, um candidato confiável do sinal transmitido é obtido usando um detector de cancelamento sucessivo de interferências (SIC). No detector em múltiplos ramos com redução de reticulado e cancelamento sucessivo de interferências (MB-LR-SIC) proposto, um número fixo de diferentes ordenamentos para o detector SIC gera uma lista de possíveis candidatos para a informação transmitida. O melhor candidato é escolhido usando o critério maximum likelihood (ML). No detector por listas de tamanho variável (VLD) proposto, um algoritmo que decide se o candidato atual tem uma boa qualidade ou se é necessário continuar procurando por um candidato melhor nos ordenamentos restantes é utilizado. Os resultados numéricos mostram que os esquemas propostos têm um desempenho quase ótimo com uma complexidade computacional bem abaixo do detector ML. Um esquema de detecção e decodificação iterativa (IDD) baseado no algoritmo VLD é também desenvolvido, produzindo um desempenho próximo a um sistema mono usuário (SU) livre de interferências. Na segunda parte desta tese, uma técnica de detecção desacoplada de sinais (DSD) para sistemas MIMO massivo é proposta. Esta técnica permite que o sinal composto recebido na BS seja separado em sinais independentes, correspondentes a diferentes classes de usuários, viabilizando assim o uso dos procedimentos de detecção propostos na primeira parte desta tese em sistemas MIMO massivos. Um modelo de sinais para sistemas MIMO massivo com antenas centralizadas e/ou antenas distribuídas operando em redes heterogêneas de quinta geração é proposto. Uma análise baseada na soma das taxas e um estudo de custo computacional para DSD são apresentados. Os resultados numéricos ilustram o excelente compromisso desempenho versus complexidade obtido com a técnica DSD quando comparada com o esquema de detecção conjunta tradicional. / [en] In the first part of this thesis, we introduce two list detection schemes for the uplink scenario of multiuser multiple-input multiple-output (MUMIMO) systems. The proposed techniques employ a single lattice reduction (LR) transformation to modify the channel matrix between the users and the base station (BS). After the LR transformation, a reliable candidate for the transmitted signal vector, provided by successive interference cancellation (SIC) detection is obtained. In the proposed multi-branch lattice reduction SIC (MB-LR-SIC) detector, a fixed number of different orderings, generates a list of SIC detection candidates. The best candidate is chosen according to the maximum likelihood (ML) selection criterion. For the proposed variable list detection (VLD) scheme, an algorithm to decide if the current candidate has good quality or if it is necessary to further explore different orderings to improve the detection performance is employed. Simulation results indicate that the proposed schemes have a near-optimal performance while keeping its computational complexity well below that of the ML detector. An iterative detection and decoding (IDD) scheme based on the VLD algorithm is also developed, producing an excellent performance that approaches the single user (SU) scenario. In the second part of this thesis, a decoupled signal detection (DSD) technique which allows the separation of uplink signals, for each user class, at the base station (BS) for massive MIMO systems is proposed. The proposed DSD allows to implement the detection procedures proposed in the first part of this thesis in massive MIMO scenarios. A mathematical signal model for massive MIMO systems with centralized and distributed antennas in the future fifth generation (5G) heterogeneous cellular networks is also developed. A sum-rate analysis and a study of computational cost for DSD are also presented. Simulation results show excellent performance of the proposed DSD algorithm when combined with linear and SIC-based detectors.