Interference and jamming severely disrupt our ability to communicate by decreasing the effective signal-to-noise ratio and by making parameter estimation difficult at the receiver. The objective of this research work is to design robust wireless systems and algorithms to suppress the adverse effects of non-intentional co-channel interference (CCI) or intentional jamming. In particular, we develop chip-combining schemes with timing, channel, and noise-power estimation techniques, all of which mitigate CCI or jamming. We also exploit the spatial diversity and iterative receiver techniques for this purpose. Most of the existing timing estimation algorithms are robust against either large frequency offsets or CCI, but not against both at the same time. Hence, we develop a new frame boundary estimation method that is robust in the presence of severe co-channel interference and large carrier-frequency offsets. To solve the high peak-to-average-power ratio problem of a multicarrier code division multiple access (MC-CDMA) system and enhance its robustness against fading and jamming, we propose a constant-envelope MC-CDMA system employing cyclic delay diversity (CDD) as transmit diversity. We analyze the diversity order, coding gain, and bit-error rate upper bound. We also propose a blind, accurate, and computationally efficient signal-to-noise ratio estimator for the proposed system. We propose a configurable robust anti-jam receiver that estimates the frequency- or time-domain jammer state information (JSI) and uses it for chip combining in the corresponding domain. A soft-JSI-based chip-combining technique is proposed that outperforms conventional hard-JSI-based chip combining. We also derive a chip combiner that provides sufficient statistics to the decoder. Channel estimation is necessary for coherent signal detection and JSI estimation. Conversely, knowledge of the jamming signal power and JSI of different subcarriers can improve the accuracy of the channel estimates. Hence, we propose joint iterative estimation of the multiple-input multiple-output (MIMO) channel coefficients, jamming power, and JSI for a coded MC-CDMA MIMO system operating under jamming and a time-varying frequency-selective fading channel. Finally, we reduce the computational complexity of the JSI-based anti-jam receivers by introducing an expectation-maximization-based joint channel and noise-covariance estimator that does not need either the subcarrier JSI or the individual powers of the AWGN and jamming signal.

Orientador: Prof. Dr. Murilo Bellezoni Loiola / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia da Informação, 2017.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In this master thesis it is proposed a MIMO communication scheme with four transmit antennas and unitary transmission rate. The performance and robustness of the scheme are evaluated and compared with other good proposals recently presented in the literature. The proposed scheme uses a preprocessor based on phase feedback. The preprocessor allows the proposed scheme to obtain full diversity and also coding gain. The pre-processing considers a codebook design, whose size is dependent on the number of feedback bits. Error probability analysis is provided, where the upper and lower bounds for different numbers of feedback bits and antennas are presented, considering two different types of constellations, QAM and PSK. For robustness analysis, channels estimators were used. For the channel estimators model it was added the effects of spatial correlation, enabling the evaluation the losses caused by the spatial correlation among the antennas, and the Doppler effect, for evaluating the loss performance due to the relative mobilitys between trnamitter and receiver. / Nesta dissertação propõe-se um esquema de comunicação MIMO para quatro antenas transmissoras com taxa de transmissão unitária. O desempenho e a robustez do esquema proposto são avaliados e comparados com outras boas propostas recentemente apresentadas na literatura. O esquema proposto utiliza um pré-processador baseado na realimentação de fase provinda do receptor. O pré-processamento permite que o esquema proposto alcance um grau de diversidade completo bem como um ganho de codificação. A pré-codificação considera o uso de um codebook, cujo comprimento depende do número de bits de realimentação disponível. Faz-se uma análise de desempenho da probabilidade de erro, mostrando os limitantes superior e inferior do esquema para diferentes quantidades de bits de realimentação, diferentes números de antenas e para as constelações do tipo PSK e QAM. Para a análise de robustez, considerou-se o emprego de estimadores de canais clássicos. No modelo utilizado para os estimadores de canais foram acrescentados os efeitos da correlação espacial, para se verificar as perdas decorrentes da correlação espacial entre as antenas, e do efeito Doppler, para se avaliar a perda de desempenho decorrente da mobilidade relativa entre transmissor e receptor.

La mise en œuvre de systèmes basés OFDMA nécessite une synchronisation de la fréquence très fine en raison de l'extrême sensibilité de l'OFDMA aux décalages en fréquence porteuse (CFO). La synchronisation en fréquence devient plus difficile dans les systèmes OFDMA en liaison montante. Nos objectifs comprennent l'étude et l'analyse des problèmes résultant de décalages de fréquence et la proposition de solutions pour lutter contre ces problèmes. Nous examinons d'abord les interférences résultant de décalages de fréquence porteuse présents dans l'oscillateur du terminal utilisateur. Nous démontrons que l'on doit prendre en compte le préfixe cyclique tout en analysant les interférences résultant du CFO. Ensuite, nous montrons qu'il existe une contradiction entre la diversité de fréquence de canal et la robustesse contre le CFO. Nous proposons un compromis sous la forme d'une taille de bloc de seuil, afin de permettre un bon compromis entre la diversité des canaux et de robustesse pour les CFO pour le cas où aucune connaissances du canal n'est disponible. Quand le canal est connu, nous proposons une allocation optimale par bloc grâce à laquelle la robustesse aux CFO et à la diversité de fréquence de canal peut être réalisée en utilisant une petite taille de bloc petit pour des CFO de petite valeur. Nous proposons également une valeur CFO critique, en dessous de laquelle l'allocation optimal par bloc est très performant.Ensuite, nous proposons des solutions pour deux problèmes importants rencontrés dans un système OFDMA en liaison montante.Premièrement, nous proposons une méthode efficace pour l'estimation conjointe des réponses impulsionnelles des canaux et fréquences porteuses basée sur l'approximation polynomiale.Notre méthode d'estimation conjointe est plus simple que les méthodes existantes, sans aucune dégradation de performance. Ensuite, nous proposons une méthode de compensation de CFO basée sur l'annulation des interférences successives (SIC). La méthode d'annulation proposée réduit la complexité de mise en oeuvre quand le nombre de porteuses est important. / One of the most prominent issues in the design and implementation of OFDMA based systems is the need for a very fine frequency synchronization due to the fact that OFDMA, like OFDM, is extremely sensitive to carrier frequency offsets (CFO). The task of frequency synchronization becomes more challenging in the uplink OFDMA-based systems where one OFDMA symbol is generated by the contribution of many different users. Our goals include the study and analysis of problems resulting from frequency mismatches provide solution to combat these problems. We first look at the interference resulting from CFOs, resulting from user terminal oscillator mismatch. We demonstrate that one must take into account the cyclic prefix while analyzing interference resulting from CFO. A new analytical expression of the ICI that takes into account the effect of CFO on the cyclic prefix is proposed. Then we focus our attention on analysis of the trade-off between channel frequency diversity and robustness against CFO and show that there exists a contradiction between the two. We propose a trade-off in the form of a Threshold blocksize, to allow a good compromise between the channel diversity and robustness for CFO for the case when no CSI is available. For system where CSI is available, we propose an optimal block carrier allocation scheme through which both robustness to CFO and channel frequency diversity can be achieved with small blocksize for small CFO. We also propose a Critical CFO value, above which the performance of the optimal block carrier allocation loses interest.Next we propose solutions for two important issues encountered in an uplink OFDMA system. First, we propose an efficient method for joint estimation of channel impulse responses and carrier frequency at the receiver based on polynomial approximation. Our proposed joint estimation method is simpler than the existing methods without any performance degradation. Next we propose a CFO compensation method based on successive interference cancellation. The proposed cancellation method reduces the implementation complexity faced in case of large DFT matrices.

No description available.

Channel estimation is a fundamental task for exploiting the advantages of massive Multiple-Input Multiple-Output (MIMO) systems in fifth generation (5G) wireless technology. Channel estimates require solving sparse linear inverse problems that is usually performed with the Least Squares method, which brings low complexity but high mean squared error values. Thus other methods are usually needed to obtain better results, on top of Least Squares. Approximate Message Passing (AMP) is an efficient method for solving sparse linear inverse problems and recently a deep neural network approach to quickly solving such problems has been proposed, called Learned Approximate Message Passing (LAMP) [1], which estimates AMP with a fixed number iterations and learnable parameters. We formalize the channel estimation problem as a dictionary-based sparse linear inverse problem and investigate the applicability of LAMP to the task. We build upon the work of Borgerding et al. [1], providing a new loss function to minimize for our dictionary-based problem, we investigate empirically LAMP’s capabilities in various conditions: varying the dataset size, number of subcarriers, depth of network, and signal-to-noise ratio (SNR). We also propose a new network called Adaptive-LAMP which differs from LAMP for the introduction of a small neural network in each layer for estimating certain parameters instead of learning them. Experiments show that LAMP performs significantly better than AMP in terms of NMSE at low signal-to-noise ratio (SNR) levels and worse at high SNR levels. Interestingly, both proposed networks perform well at discovering active paths in cellular networks, paving the way for new approaches to the Channel Estimation problem. / Kanalbedömning är en grundläggande uppgift för att utnyttja fördelarna med massiva MIMO-system (Multiple-Input Multiple-Output) i femte generationens (5G) trådlösa teknik. Kanalskattningar kräver att man löser glesa linjära inversa problem som vanligtvis utförs med Least Squares-metoden, som ger låg komplexitet men höga medelvärden för det kvadratiska felet. Därför behövs vanligtvis andra metoder för att få bättre resultat, utöver Least Squares. Approximate Message Passing (AMP) är en effektiv metod för att lösa sparsamma linjära inversa problem, och nyligen har det föreslagits ett djupt neuralt nätverk för att snabbt lösa sådana problem, kallat Learned Approximate Message Passing (LAMP) [1], som uppskattar AMP med ett fast antal iterationer och inlärningsbara parametrar. Vi formaliserar kanalskattningsproblemet som ett ordboksbaserat sparse linjärt inversproblem och undersöker LAMP:s tillämplighet på uppgiften. Vi bygger på Borgerding et al. [1], som tillhandahåller en ny förlustfunktion att minimera för vårt ordboksbaserade problem, och vi undersöker empiriskt LAMP:s kapacitet under olika förhållanden: vi varierar datasetets storlek, antalet underbärare, nätverkets djup och signal-brusförhållandet (SNR). Vi föreslår också ett nytt nätverk kallat Adaptive-LAMP som skiljer sig från LAMP genom att det införs ett litet neuralt nätverk i varje lager för att uppskatta vissa parametrar i stället för att lära sig dem. Experiment visar att LAMP presterar betydligt bättre än AMP när det gäller NMSE vid låga signal-brusförhållande (SNR) och sämre vid höga SNR-nivåer. Intressant nog presterar båda de föreslagna nätverken bra när det gäller att upptäcka aktiva vägar i cellulära nätverk, vilket banar väg för nya metoder för kanalskattningsproblemet.

La coopération des émetteurs est considérée comme une approche prometteuse pour limiter les interférences dans les réseaux sans fil ayant une réutilisation des ressources spectrales très agressive. La coopération des émetteurs permet l'optimisation conjointe de certains paramètres de transmission. Bien que la coopération des émetteurs existe sous différentes formes, une hypothèse commune est le besoin pour les émetteurs entrant en coopération (i) d’acquérir et de partager des informations concernant le canal de propagation ainsi que (ii) d’effectuer une coopération fondée sur les informations diffusées à l'étape précédente. La conception coordonnée des matrices de précodage et, d’une manière encore plus marquée, la transmission conjointe à différents émetteurs sont des exemples importants de méthodes de coopérations présentant ces propriétés. L’acquisition et l'échange de l’information de canal étant strictement limités, il se pose deux questions importantes: (i) Quelle information doit être renvoyée ou échangée de manière à permettre la coopération la plus efficace? (ii) Quelles méthodes permettent de réaliser les gains de la coopération dans ce contexte de partage limité et imparfait d’information? Dans cette thèse, nous abordons les deux questions précédentes. Dans un premier temps, nous considérons que chaque émetteur acquiert une estimée de canal imparfaite. Dans un second temps, nous étudions la conception de techniques de coopération efficaces dans une configuration d’information de canal imparfaitement partagée entre les émetteurs. Enfin, les futures directions de recherche découlant de ces travaux sont présentées et discutées. / Transmitter cooperation is considered a promising tool for dealing with interference in wireless networks with an aggressive reuse policy of spectral resources. Although transmitter cooperation comes in many flavors, a recurrent assumption behind proposed methods lies in the need for cooperating devices to (i) acquire, share information pertaining to the propagation channel toward the multiple receivers and (ii) perform cooperation based on the disseminated information in the previous step. This holds true for instance for coordinated beamforming methods and, to an even greater extent, for network-MIMO (Joint Processing coordinated multi-point (JP CoMP) in the long term evolution (LTE) terminology). As feedback and exchange of channel state information (CSI) come at a price in terms of signaling overhead, there arise two important questions: (i) What information should be fed back or exchanged such that the CSI acquired at each transmitter is most informative to perform cooperation? (ii) Which techniques can reap the benefits of cooperation while living with an imperfect channel representation that varies from transmitter to transmitter ? In this thesis, we address both aforementioned questions. We consider first each transmitter acquires an initial imperfect CSI based on limited receivers feedback. For the design of efficient cooperation techniques that copes with the imperfect and non-identical CSI configuration at each transmitter, we investigate specifically a regularized zero forcing (RZF) precoder design in large system scenario. Finally, interesting and challenging research directions and open problems are discussed.

With the recent advancements of wireless networks to satisfy new requirements, the investigation of novel transmission schemes to improve the link level performance is of major importance. A very common technique utilized in nowadays systems is the Orthogonal frequency division multiplexing (OFDM) waveform, which has been adopted by several standards, including WiFi, LTE, and more recently 5G, due to its simple equalization process. Despite its success, this dissertation shows that OFDM is a sub-optimal scheme under frequency-selective channel (FSC), when channel state information (CSI) is available at the receiver only. Based on the coded modulation capacity approach, this work demonstrates that the data symbols should experience the same channel gain in order to achieve the best performance, leading to the equal gain criterion (EGC). However, this comes at a cost in terms of losing orthogonality among data symbols. The result is valid for linear modulation matrices under the assumptions of CSI at only at the receiver with perfect feedback equalization. In order to attain the EGC for doubly-dispersive channels, the block multiplexing (BM) waveform is proposed in this thesis, where the data symbols are spread in frequency and time. For instance, the recently conceived orthogonal time frequency space (OTFS) is shown to be a particular case of BM with the classical single-carrier (SC). Regarding the equalization for the robust waveforms, it is shown that the minimum mean squared error with parallel interference cancellation (MMSE-PIC) employed together with convolutional encoder and soft decoder can completely remove the inter-symbol interference (ISI), where a low-complexity implementation is designed. In addition, a waveform with decreased complexity based on the sparse Walsh-Hadamard (SWH) is proposed for two reasons, i) sparse spreading requires a transform with lower size, ii) the Walsh-Hadamard transform is implemented with 1s and −1s, which requires less complexity than fast Fourier transform (FFT) based waveforms. Furthermore, the problem of estimating the time varying channel is considered, where a unique word (UW) or (pilot block) based approach is studied. In this regard, another main contribution of this dissertation is to develop an optimization framework, where the combination of channel estimation plus Doppler spread error is minimized. In particular, the composite error minimization is achieved by properly setting the FFT size of the system, for a fixed data length. Lastly, cyclic prefix (CP)-free system is considered such that the transmission time is decreased, and therefore provides a better channel estimation. Naturally, the CP-free system has undesirable interference, which is resolved by an iterative CP-Restoration algorithm. In this case, we extend the EGC to equal reliability criterion (ERC), i.e., the data symbols should be equally reliable and not only have equal gain. As a consequence, the BM with orthogonal chirp division multiplexing (OCDM) waveform has the best performance due to equal time and frequency spreading. In conclusion, the coded modulation capacity approach of this dissertation provides new insights and solutions to improve the performance of wireless systems.

The increasing demand for mobile data has placed significant strain on radio access networks (RANs), leading to a continuous need for increased network capacity. In keeping with that, a significant advancement in modern RANs is the ability to utilize several receivers and transmitters, to allow for beamforming. One way to increase the capacity of the network is therefore to optimize the resource allocation by preprocessing the transmitted signals, which involves several costly matrix multiplications (MMs). The aim of the project was to investigate the potential of accelerating Ericsson's RAN simulations by using AI based approximate matrix multiplication (AMM) algorithms. The main focus was on the multiply additionless (MADDNESS) algorithm, a product quantization technique that has achieved speedups of up to 100 times compared to exact MM, and 10 times faster than previous AMM methods. A complex matrix handling version of MADDNESS was implemented in Java and Python respectively, and its speed and accuracy were evaluated against Ericsson's current MM implementation. The proposed implementation did not beat the benchmark with respect to speed, instead resulting in a 4-10 times slowdown in runtime. However, this may largely be due to the fact that the used languages do not allow for complete control over memory resource allocation. As such, the implementations at hand do not incorporate all the crucial features of the algorithm. Particularly, the handicapped version does not fully leverage the vectorization potential, which is one of the key contributors to the speed of the algorithm. Consequently, further improvements are necessary before employing the techniques in an end-to-end implementation. / Den växande efterfrågan på mobildata har ökat belastningen på dagens radionätverk (RAN) och har medfört ett behov av att utvidga dess kapacitet. En betydande innovation inom RAN är beamforming, vilket är förmågan att fokusera digitala signaler mot mottagaren och på så vis öka singalstyrkan. En metod för att öka kapaciteten i ett nätverk är att optimera både kvaliteten av och resursallokeringen mellan nätverkets digitala kanaler, vilket medför tidskrävande matrismultiplikationer. Syftet med denna studie var att utforska om AI-baserade approximativa matrismultiplikationsalgoritmer har potentialen att accelerera Ericssons digitala tvilling-simuleringar. Studien fokuserade i huvudsak på produktkvantiseringsalgoritmen MADDNESS som påvisat potentialen att accelerera exakta matrismultiplikationer med en faktor 100, samt en faktor 10 snabbare än jämförbara approximativa metoder. En modifierad version av MADDNESS, som behandlar komplexa matriser, implementerades i Java samt Python, varefter precisionen och hastigheten utvärderades. Den föreslagna implementationen resulterade i en försämring med avseende på hastigheten med en faktor 4-10 jämfört med Ericssons nuvarande algoritmer. Den föreslagna implementationen saknar effektiv minnesallokering och misslyckas följaktligen att till fullo ta tillvara på vektoriseringspotentialen i MADDNESS. Detta indikerar att det är nödvändigt för ytterligare förbättringar innan algoritmen är användbar i den givna simuleringsmiljön.

The onset of quantum computing threatens commonly used schemes for information secrecy across wireless communication channels, particularly key-based data-level encryption. This calls for secrecy schemes that can provide everlasting secrecy resistant to increased computational power of an adversary. One novel physical layer scheme proposes that an intended receiver capable of performing analog cancellation of a known key-based interference would hold a significant advantage in recovering small underlying messages versus an eavesdropper performing cancellation after analog-to-digital conversion. This advantage holds even in the event that an eavesdropper can recover and use the original key in their digital cancellation. Inspired by this scheme, a flexible software-defined radio receiver design capable of maintaining analog cancellation ratios consistently over 40 dB, reaching up to and over 50 dB, is implemented in this thesis. Maintaining this analog cancellation requires very precise time-frequency synchronization along with accurate modeling and simulation of the channel effects on the interference. The key sources of synchronization error preventing this test bed from achieving and maintaining perfect interference cancellation, sub-sample period timing errors and limited radio frequency stability, are explored for possible improvements. To further prove robustness of the implemented secrecy scheme, the testbed is shown to operate with both phase-shift keying and frequency-modulated waveforms. Differences in the synchronization algorithm used for the two waveforms are highlighted. Interference cancellation performance is measured for increasing interference bandwidth and shown to decrease with such. The implications this testbed has on security approaches based on intentional interference employed to confuse eavesdroppers is approached from the framework proposed in the motivating everlasting secrecy scheme. Using analog cancellation levels from the hardware testbed, it is calculated that secrecy rates up to 2.3 bits/symbol are gained by receivers (intended or not) performing interference cancellation in analog rather than on a digital signal processor. Inspired by the positive gains in secrecy over systems not performing analog cancellation prior to signal reception, a novel secrecy scheme that focuses on the advantage an analog canceller holds in receiver amplifier compression is proposed here. The adversary amplifier is assumed to perform linear cancellation after the interference has passed through their nonlinear amplifier. This is accomplished by deriving the distribution of the interference residual after undergoing an inverse tangent transfer function and perfect linear cancellation. Parameters of this scheme are fit for the radios and cancellation ratios observed in the testbed, resulting in a secrecy gain of 0.95 bits/symbol. The model shows that larger message powers can still be kept secure for the achieved levels of cancellation, thus providing an even greater secrecy gain with increased message transmission power.