Em sistemas MIMO multiusuÃrio, o transmissor pode selecionar um subconjunto de antenas e/ou usuÃrios que tÃm bons canais para maximizar o rendimento do sistema usando vÃrios critÃrios de seleÃÃo. AlÃm disso, os prÃ-codificadores podem proporcionar dimensÃes livres de interferÃncia. O alinhamento de interferÃncia (IA) à baseado no conceito de prÃ-codificaÃÃo e oferece diferentes compromissos entre complexidade e desempenho. A idÃia bÃsica do Alinhamento InterferÃncia consiste em prÃ-codificar os sinais transmitidos de maneira que os mesmos sejam alinhados no receptor, em que eles constituem interferÃncia, enquanto que ao mesmo tempo os separa do sinal desejado. No entanto, a InformaÃÃo do Estado do Canal (CSI) tem sido uma preocupaÃÃo para os pesquisadores porque ela tem um impacto no desempenho de algoritmos de IA. Assim, nos propomos a analisar o desempenho da seleÃÃo de antena e diversidade multiusuÃrio em conjunto, a fim de permitir o IA oportunista usando vÃrios critÃrios com relaÃÃo à perturbaÃÃo da CSI. AnÃlises e simulaÃÃes verificam o comportamento do esquema proposto. / In multiuser MIMO systems, the transmitter can select a subset of antennas and/or users which have good channel conditions to maximize the system throughput using various selection criteria. Furthermore, precoding can provide free interference dimensions. The Interference Alignment (IA) is based on the concept of precoding and it offers different trade-offs between complexity and performance. The basic idea of Interference Alignment consists in precoding the transmitted signals such that they are aligned at the receiver where they constitute interference, while at the same time disjointed from the desired signal. However, the Channel State Information (CSI) has been a concern because it impacts the performance of IA algorithms. Hence, we propose to analyze the performance of antenna selection and multiuser diversity together in order to allow opportunistic IA using several criteria over the disturbance of CSI. Analyses and simulations verify the behavior of the proposed scheme.

Enabling multiple base stations to utilize the spatial dimension in a coordinated manner has been shown to be a fruitful technique for improving the spectral efficiency in wireless interference networks. This thesis considers multicell systems where base stations and mobile stations are equipped with multiple antennas. The base stations coordinate their spatial precoding, but individually serve their mobile stations with data. For such coordinated precoding systems, interference alignment (IA) is a useful theoretical tool, due to its ability to serve the maximum number of interference-free data streams. Three topics related to interference alignment and coordinated precoding are studied. First, the feasibility of IA over a joint space-frequency signal space is studied. A necessary condition for space-frequency IA feasibility is derived, and the possible gain over space-only IA is analyzed. An upper bound on the degree of freedom gain is shown to increase in the number of subcarriers, but decrease in the number of antennas. Numerical studies, using synthetically generated channels and real-world channels obtained from indoors and outdoors channel measurements, are used for sum rate performance evaluation. The results show that although a degree of freedom gain is noticeable due to the space-frequency precoding, the sum rate of the system is mainly improved due to a power gain. Second, distributed channel state information (CSI) acquisition techniques are proposed, which provide estimates of the information necessary to perform distributed coordinated precoding. The methods are based on pilot-assisted channel estimation in the uplink and downlink, and correspond to different tradeoffs between feedback and signaling, backhaul use, and computational complexity. Naively applying the existing WMMSE algorithm for distributed coordinated precoding together with the estimated CSI however results in poor performance. A robustification of the algorithm is therefore proposed, relying on the well known diagonal loading technique. An inherent property of the WMMSE solutions is derived and, when enforced onto solutions with imperfect CSI, results in diagonally loaded receive filters. Numerical simulations show the effectiveness of the proposed robustification. Further, the proposed robustified and distributed WMMSE algorithm performs well compared to existing state-of-the-art robust WMMSE algorithms. In contrast to our approach, the existing methods however rely on centralized CSI acquisition. Third, coordinated precoding systems with hardware impairments are studied. Assuming that impairment compensation techniques have been applied, a model is used to describe the aggregate effect of the residual hardware impairments. An iterative resource allocation method accounting for the residual hardware impairments is derived, based on an existing resource allocation framework. Numerical simulations show that the proposed method outperforms all benchmarks. In particular, the gain over impairments-aware time-division multiple access is substantial. / Genom att låta flera radiobasstationer samarbeta är det möjligt att förbättra spektraleffektiviteten i trådlösa interferensnätverk. Fokus i denna licentiatavhandling ligger på multicellnätverk där både radiobasstationer och mobilenheter har flera antenner. Radiobasstationerna väljer sina spatiella förkodare gemensamt, men skickar data individuellt till sina respektive mobilenheter. För sådana system med koordinerad förkodning ('coordinated precoding') är interferensupprätning ('interference alignment') ett användbart teoretiskt verktyg, eftersom det möjliggör överföring av maximalt antal dataströmmar i nätverket. I avhandlingen studeras tre aspekter av interferensupprätning och koordinerad förkodning. Först undersöks interferensupprätning när signalrummet består av en kombination av rymd- och frekvensdimensioner. Ett nödvändigt villkor härleds för existensen av rymd/frekvens-interferensupprätning, och prestandavinsten analyseras i jämförelse med system där enbart rymddimensionerna används för interferensupprätning. Det föreslagna systemet utvärderas med hjälp av numeriska simuleringar och uppmätta inomhus- och utomhuskanaler. Resultaten visar att rymd/frekvens-interferensupprätning ger upphov till ett ökat antal frihetsgrader, men att summadatatakten främst förbättras tack vare en upplevd effektförstärkning. Därefter undersöks tekniker för skattning av den nödvändiga kanalkännedom som krävs för att genomföra koordinerad förkodning. Det finns flera sätt att erhålla den nödvändiga informationen, t.ex. genom olika kombinationer av kanalskattning, feedback, signalering och användning av backhaulnätverk. Speciellt söks distribuerade metoder, eftersom dessa är fördelaktiga vid praktisk implementering. Tre metoder för skattning av kanalkännedom föreslås. Dessa motsvarar olika avvägningar mellan kanalskattning och signalering, och en av metoderna är helt distribuerad. När den skattade informationen används med en existerande algoritm för koordinerad förkodning blir prestandan undermålig. Därför föreslås två förändringar av algoritmen, vilka leder till mer robusta prestanda. Förändringarna bygger på den välkända diagonal loading-tekniken. Utvärdering av det föreslagna systemet, som består av distribuerad erhållning av kanalkännedom samt den förbättrade algoritmen för koordinerad förkodning, genomförs med numerisk simulering. Resulterande prestanda är i nivå med ett tidigare föreslaget system, som dock kräver centraliserad tillgång till kanalskattningarna, till skillnad från vår nya lösning. Slutligen studeras ett system med koordinerad förkodning och icke-perfekt radiohårdvara. En modell för distortionsbruset orsakad av bristerna i radiohårdvaran används, och en iterativ resurstilldelningsteknik föreslås baserad på ett existerande ramverk. Den föreslagna algoritmen kan implementeras distribuerat över mobilenheterna, men kan i allmänhet inte implementeras distribuerat över radiobasstationerna. Den föreslagna algoritmen utvärderas med numeriska simuleringar, och resultaten visar att prestanda är bättre än alla referensmetoder. Detta visar betydelsen av att hantera bristerna i radiohårdvaran i resurstilldelningen. Sammantaget visar avhandlingen på möjligheterna att öka spektraleffektiviteten i framtida multicellnätverk med hjälp av koordinerad förkodning. / <p>QC 20140512</p>

Next-generation wireless communication systems will need to contend with many active mobile devices, each of which will require a very high data rate. To cope with this growing demand, network deployments are becoming denser, leading to higher interference between active users. Conventional architectures aim to mitigate this interference through careful design of signaling and scheduling protocols. Unfortunately, these methods become less effective as the device density increases. One promising option is to enable cellular basestations (i.e., cell towers) to jointly process their received signals for decoding users’ data packets as well as to jointly encode their data packets to the users. This joint processing architecture is often enabled by a cloud radio access network that links the basestations to a central processing unit via dedicated connections. One of the main contributions of this thesis is a novel end-to-end communications architecture for cloud radio access networks as well as a detailed comparison to prior approaches, both via theoretical bounds and numerical simulations. Recent work has that the following high-level approach has numerous advantages: each basestation quantizes its observed signal and sends it to the central processing unit for decoding, which in turn generates signals for the basestations to transmit, and sends them quantized versions. This thesis follows an integer-forcing approach that uses the fact that, if codewords are drawn from a linear codebook, then their integer-linear combinations are themselves codewords. Overall, this architecture requires integer-forcing channel coding from the users to the central processing unit and back, which handles interference between the users’ codewords, as well as integer-forcing source coding from the basestations to the central processing unit and back, which handles correlations between the basestations’ analog signals. Prior work on integer-forcing has proposed and analyzed channel coding strategies as well as a source coding strategy for the basestations to the central processing unit, and this thesis proposes a source coding strategy for the other direction. Iterative algorithms are developed to optimize the parameters of the proposed architecture, which involve real-valued beamforming and equalization matrices and integer-valued coefficient matrices in a quadratic objective. Beyond the cloud radio setting, it is argued that the integer-forcing approach is a promising framework for interference alignment between multiple transmitter-receiver pairs. In this scenario, the goal is to align the interfering data streams so that, from the perspective of each receiver, there seems to be only a signal receiver. Integer-forcing interference alignment accomplishes this objective by having each receiver recover two linear combinations that can then be solved for the desired signal and the sum of the interference. Finally, this thesis investigates the impact of channel coherence on the integer-forcing strategy via numerical simulations.

This thesis focuses on the design of linear precoding schemes for downlink multiple-input multiple-output (MIMO) networks. These schemes are designed to be amenable to implementation in wireless networks that allow rate-limited feedback of channel state information (CSI). In the first half of this thesis, memoryless quantization codebooks are designed and incremental vector quantization techniques are developed for the representation of CSI in MIMO point-to-point links and isolated (single-cell) downlink networks. The second half of the thesis seeks to design linear precoding schemes for the multi-cell downlink networks that can achieve improved performance without requiring significantly more communication resources for CSI feedback than those required in the case of an isolated single-cell. For the quantization problem, smooth optimization algorithms are developed for the design of codebooks that possess attractive features that facilitate their implementation in practice in the addition to having good quantization properties. As one example, the proposed approach is used to design rank-2 codebooks that have a nested structure and elements from a phase-shift keying (PSK) alphabet. The designed codebooks have larger minimum distances than some existing codebooks, and provide tangible performance gains. To take advantage of temporal correlation that may exist in the wireless channel, an incremental approach to the Grassmannian quantization problem is proposed. This approach leverages existing codebooks for memoryless quantization schemes and employs a quantized form of geodesic interpolation. Two schemes that implement the principles of the proposed approach are presented. A distinguishing feature of the proposed approach is that the direction of the geodesic interpolation is specified implicitly using a point in a conventional codebook. As a result, the approach has an inherent ability to recover autonomously from errors in the feedback path. In addition to the development of the Grassmannian quantization techniques and codebooks, this thesis studies linear precoder design for the downlink MIMO networks in the cases of small networks of arbitrary topology and unbounded networks that have typical architectures. In particular, a linear precoding scheme for the isolated 2-cell network that achieves the optimal spatial degrees of freedom of the network is proposed. The implementation of a limited feedback model for the proposed linear precoding scheme is developed as well. Based on insight from that model, other linear precoding schemes that can be implemented in larger networks, but with finite size, are developed. For unbounded networks of typical architecture, such as the hexagonal arrangement of cells, linear precoding schemes that exploit the partial connectivity of the network are presented under a class of precoding schemes that is referred to as spatial reuse precoding. These precoding schemes provide substantial gains in the achievable rates of users in the network, and require only local feedback. / Thesis / Doctor of Philosophy (PhD)

This thesis deals with the design of efficient transmission schemes forwireless interference networks, when certain channel state information(CSI) is available at the terminals.In wireless interference networks multiple source-destination pairsshare the same transmission medium for the communications. The signalreception at each destination is affected by the interference from unintendedsources. This may lead to a competitive situation that each sourcetries to compensate the negative effect of interference at its desired destinationby increasing its transmission power, while it in fact increasesthe interference to the other destinations. Ignoring this dependency maycause a significant waste of available radio resource. Since the transmissiondesign for each user is interrelated to the other users’ strategies, anefficient radio resource allocation should be jointly performed consideringall the source-destination pairs. This may require a certain amount ofCSI to be exchanged, e.g. through feedback channels, among differentterminals. In this thesis, we investigate such joint transmission designand resource allocation in wireless interference networks.We first consider the smallest interference network with two sourcedestinationpairs. Each source intends to communicate with its dedicateddestination with a fixed transmission rate. All terminals have the perfectglobal CSI. The power control seeks feasible solutions that properly assigntransmission power to each source in order to guarantee the successfulcommunications of both source-destination pairs. To avoid interference,the transmissions of the two sources can be orthogonalized. They canalso be activated non-orthogonally. In this case, each destination maydirectly decode its desired signals by treating the interference signals asnoise. It may also perform decoding of its desired signals after decodingand subtracting the interference signals sent from the unintendedsources. The non-orthogonal transmission can more efficiently utilize the  available channel such that the power control problem has solutions withsmaller transmission power in comparison with the orthogonal transmission.However, due to the randomness of fading effects, feasible powercontrol solutions may not always exist. We quantify the probability thatthe power control problem has feasible solutions, under a Rayleigh fadingenvironment. A hybrid transmission strategy that combines the orthogonaland non-orthogonal transmissions is then employed to use the smallesttransmission power to guarantee the communications in the consideredtwo-user interference network.The network model is further extended to the general K-user interferencenetwork, which is far more complicated than the two-user case. Thecommunication is conducted in a time-varying fading environment. Thefeedback channel’s capacity is limited so that each terminal can obtainonly quantized global CSI. Conventional interference management techniquestend to orthogonalize the transmissions of the sources. However,we permit them to transmit non-orthogonally and apply an interferencealignment scheme to tackle inter-user interference. Ideally, the interferencealignment concept coordinates the transmissions of the sources insuch a way that at each destination the interference signals from differentunintended sources are aligned together in the same sub-space which isdistinguishable from the sub-space for its desired signals. Hence, eachdestination can cancel the interference signals before performing decoding.Nevertheless, due to the imperfect channel knowledge, the interferencecannot be completely eliminated and thus causes difficulties to theinformation recovery process. We study efficient resource allocation intwo different classes of systems. In the first class, each source desires tosend information to its destination with a fixed data rate. The powercontrol problem tends to find the smallest transmission powers to guaranteesuccessful communications between all the source-destination pairs.In another class of systems where the transmission power of each sourceis fixed, a rate adaptation problem seeks the maximum sum throughputthat the network can support. In both cases, the combination of interferencealignment and efficient resource allocation provides substantialperformance enhancement over the conventional orthogonal transmissionscheme.When the fading environment is time-invariant, interference alignmentcan still be realized if each terminal is equipped with multiple antennas.With perfect global CSI at all terminals, the interference signalscan be aligned in the spatial dimension. If each terminal has only localCSI, which refers to the knowledge of channels directly related to  the terminal itself, an iterative algorithm can be applied to calculate thenecessary transmitter-side beamformers and receiver-side filters to properlyalign and cancel interference, respectively. Again, due to the lack ofperfect global CSI, it is difficult to completely eliminate the interferenceat each destination. We study the power control problem in this caseto calculate the minimum required power that guarantees each source tosuccessfully communicate with its destination with a fixed transmissionrate. In particular, since only local CSI is available at each terminal, wepropose an iterative algorithm that solves the joint power control andinterference alignment design in a distributed fashion. Our results showthat a substantial performance gain in terms of required transmissionpower over the orthogonalizing the transmissions of different sources canbe obtained. / <p>QC 20120912</p>

Interference is a fundamental problem in wireless networks. An effective solution to this problem usually calls for a cross-layer approach. Although there exist a large volume of works on interference management techniques in the literature, most of them are limited to signal processing at the physical (PHY) layer or information-theoretic exploitation. Studies of advanced interference techniques from a cross-layer optimization perspective remain limited, especially involving multi-hop wireless networks. This dissertation aims at filling this gap by offering a comprehensive investigation of three interference techniques: interference cancellation (IC), interference alignment (IA), and interference neutralization (IN). This dissertation consists of three parts: the first part studies IC in distributed multi-hop multiple-input multiple-output (MIMO) networks; the second part studies IA in multi-hop networks, cellular networks, and underwater acoustic (UWA) networks; and the third part focuses on IN in multi-hop single-antenna networks. While each part makes a step towards advancing an interference technique, they collectively constitute a body of work on interference management in the networking research community. Results in this dissertation not only advance network-level understanding of the three interference management techniques, but also offer insights and guidance on how these techniques may be incorporated in upper-layer protocol design. In the first part, we study IC in multi-hop MIMO networks where resource allocation is achieved through neighboring node coordination and local information exchange. Based on a well-established degree-of-freedom (DoF) MIMO model, we develop a distributed DoF scheduling algorithm with the objective of maximizing network-level throughput while guaranteeing solution feasibility at the PHY layer. The proposed algorithm accomplishes a number of beneficial features, including polynomial-time complexity, amenability to local implementation, a guarantee of feasibility at the PHY layer, and competitive throughput performance. Our results offer a definitive ``yes'' answer to the question --- Can the node-ordering DoF model be deployed in a distributed multi-hop MIMO network? In particular, we show that the essence of the DoF model --- a global node ordering, can be implicitly achieved via local operations, albeit it is invisible to individual node. In the second part, we investigate IA in various complex wireless networks from a networking perspective. Specifically, we study IA in three different domains: spatial domain, spectral domain, and temporal domain. In the spatial domain, we study IA for multi-hop MIMO networks. We derive a set of simple constraints to characterize the IA capability at the PHY layer. We prove that as long as the set of simple constraints are satisfied, there exists a feasible IA scheme (i.e., precoding and decoding vectors) at the PHY layer so that the data streams on each link can be transported free of interference. Therefore, instead of dealing with the complex design of precoding and decoding vectors, our IA constraints only require simple algebraic addition/subtraction operations. Such simplicity allows us to study network-level IA problems without being distracted by the tedious details in signal design at the PHY layer. Based on these IA constraints, we develop an optimization framework for unicast and multicast communications. In the spectral domain, we study IA in OFDM-based cellular networks. Different from spatial IA, spectral IA is achieved by mapping data streams onto a set of frequency bands/subcarriers (rather than a set of antenna elements). For the uplink, we derive a set of simple IA constraints to characterize a feasible DoF region for a cellular network. We show how to construct precoding and decoding vectors at the PHY layer so that each data stream can be transported free of interference. Based on the set of IA constraints, we study a user throughput maximization problem and show the throughput improvement over two other schemes via numerical results. For the downlink, we find that we can exploit the uplink IA constraints to the downlink case simply by reversing the roles of user and base station. Further, the downlink user throughput maximization problem has the exactly same formulation as the uplink problem and thus can be solved in the exactly same way. In the temporal domain, we study IA for UWA networks. A fundamental issue in UWA networks is large propagation delays due to slow signal speed in water medium. But temporal IA has the potential to turn the adverse effect of large propagation delays into something beneficial. We propose a temporal IA scheme based on propagation delays, nicknamed PD-IA, for multi-hop UWA networks. We first derive a set of PD-IA constraints to guarantee PD-IA feasibility at the PHY layer. Then we develop a distributed PD-IA scheduling algorithm, called Shark-IA, to maximally overlap interference in a multi-hop UWA network. We show that PD-IA can turn the adverse propagation delays to throughput improvement in multi-hop UWA networks. In the third part, we study IN for multi-hop single-antenna networks with full cooperation among the nodes. The fundamental problem here is node selection for IN in a multi-hop network environment. We first establish an IN reference model to characterize the IN capability at the PHY layer. Based on this reference model, we develop a set of constraints that can be used to quickly determine whether a subset of links can be active simultaneously. By identifying each eligible neutralization node as a neut, we study IN in a multi-hop network with a set of sessions and derive the necessary constraints to characterize neut selection, IN, and scheduling. These constraints allow us to study IN problems from a networking perspective but without the need of getting into signal design issues at the PHY layer. By applying our IN model and constraints to study a throughput maximization problem, we show that the use of IN can generally increase network throughput. In particular, throughput gain is most significant when there is a sufficient number of neuts that can be used for IN. In summary, this dissertation offers a comprehensive investigation of three interference management techniques (IC, IA, and IN) from a networking perspective. Theoretical and algorithmic contributions of this dissertation encompass characterization of interference exploitation capabilities at the PHY layer, derivation of tractable interference models, development of feasibility proof for each interference model, formulation of throughput maximization problems, design of distributed IC and PD-IA scheduling algorithms, and development of near-optimal solutions with a performance guarantee. The results in this dissertation offer network-level understanding of the three interference management techniques and lay the groundwork for future research on interference management in wireless networks. / Ph. D.

Dans cette thèse, notre objectif est d'optimiser les stratégies de transmission et de réception dans un réseau où il y a peu ou pas de gestion centrale des ressources du tout, et o'u les nœuds ont une connaissance limitée du canal avec seulement un lien restreint entre eux. En particulier, les ́émetteurs ont la plupart du temps des informations locales seulement sur le canal, et nous considérons qu'il n'y a pas de partage des données 'a transmettre aux utilisateurs, ce qui empêche la transmission conjointe en système virtuel MIMO. L'utilisation commune des ressources du système (par exemple en transmettant en même temps et dans la même bande de fréquence) conduit 'a la génération d'interférence au niveau des différents récepteurs, ce qui rend la gestion des interférences essentielle. En considérant l'optimisation du précodeur dans le cadre de la théorie des jeux, des stratégies extrêmes, égoïste ou altruiste, peuvent être ́définies. Un émetteur égoïste agit en prenant compte de son propre intérêt et recherche la maximisation de son propre rapport signal sur bruit plus interférence (SINR) sans considération des interférences générées aux autres récepteurs. Un émetteur altruiste, par contre, utilise toutes ses ressources afin d'annuler les interférences qu'il crée aux autres récepteurs. Il est intuitif qu'aucune de ces deux stratégies extrêmes n'est optimale pour maximiser le débit total du réseau. Un travail récent sur le design du vecteur de précodage dans un canal d'interférence MISO (MISO-IC) sans décodage des interférences au récepteur (SUD) a mis en évidence qu'il est possible, en balançant les approches égoïste et altruiste, d'atteindre un point d'opération se situant sur la frontière Pareto optimale de la région de débit, qui est la frontière limitant la région des débits atteignables par l'utilisation de précodage linéaire. En gardant 'a l'esprit ce résultat, nous étudions l'optimisation distribuée des vecteurs de précodage pour le MISO-IC-SUD dans le chapitre 2. Nous développons un algorithme qui est initialisé 'a l'équilibre de Nash (point d'opération égoïste) et se déplace 'a chaque itération vers la solution du zéro-forcing (point d'opération altruiste) 'a pas fixe. L'algorithme s'arrête si un des émetteurs observe une baisse de son débit, imitant ainsi le procédé de négociation. L'algorithme propos ́e atteint un point d'opération proche de la frontière Pareto optimale, et chaque utilisateur obtient un débit supérieur 'a celui qu'il aurait eu 'a l'équilibre de Nash. Nous démontrons ainsi que les joueurs (les paires ́émetteur-récepteur) peuvent atteindre des débits supérieurs dans le MISO-IC-SUD en coopérant et en balançant égoïsme et altruisme. Le problème du design des vecteurs de précodage pour le MISO-IC-SUD est étendu au cas du MIMO-IC-SUD au chapitre 3. En supposant une connaissance locale, nous modélisons ce problème en un jeu bayésien prenant en compte le fait que le canal ne soit pas complètement connu, et o'u les joueurs maximisent l'espérance de leur fonction d'utilité 'a partir des statistiques du canal. Nous trouvons le point d'équilibre de ce jeu bayésien et étudions la maximisation de la somme des débits dans un MIMO-IC-SUD. Nous observons que la maximisation du débit total peut aussi être interprétée dans ce scénario comme un équilibre entre les approches égoïstes et altruistes. Avec cette analyse, un algorithme dans lequel les vecteurs de transmission et de réception sont obtenus par une optimisation alternée aux émetteurs et aux récepteurs est développé. L'algorithme converge vers une solution qui aligne les interférences lorsque le SNR devient large, ce qui implique que le débit total augmente indéfiniment avec le SNR (avec une pente égale aux nombre de degrés de liberté). Dans le régime 'a faible SNR, notre approche fonctionne mieux que les algorithmes conventionnels visant 'a aligner les interférences, ce qui est une conséquence de l'équilibre entre égoïsme et altruisme. En particulier, l'algorithme propos ́e atteint des performances presque optimales dans des réseaux asymétriques pour lesquels certains récepteurs sont soumis 'a du bruit de fond incontrôlé. Dans le chapitre 4, nous considérons enfin des récepteurs ayant la capacité de décoder les interférences (IDC) dans un MISO-IC. Ce degré de liberté additionnel permet aux récepteurs de décoder les interférences et de les soustraire au signal reçu, ce qui permet ainsi d'obtenir une communication sans interférence. En revanche, les choix des récepteurs dépendent des vecteurs de précodage aux émetteurs. Pour chaque choix de vecteur de précodage, nous obtenons un nouveau SISO-IC avec une nouvelle région de capacité correspondante. Ainsi, nous devons choisir pour chaque réalisation d'un canal MISO le vecteur de précodage et la puissance de transmission de manière 'a atteindre un débit maximal après avoir considéré toutes les possibilités pour les actions des récepteurs (décodage des interférences ou traitement des interférences comme du bruit). Il y a trois paramètres influant le design: la structure du récepteur, le vecteur de précodage, et la puissance de transmission. Ces trois paramètres sont interdépendants et l'obtention du triplet optimal est un problème qui a ́et ́e démontré comme étant NP-complet. Quoi qu'il en soit, nous avons simplifié cette analyse en reformulant la région des débits atteignables d'un MISO-IC-IDC comme l'union des régions pour les différentes structures. Ensuite nous avons caractérisé les limites de ces régions de débit atteignable et obtenu ainsi la frontière Pareto optimale du problème initial. Les vecteurs de précodage Pareto optimaux sont obtenus par une combinaison linéaire de deux vecteurs du canal avec des poids dépendant seulement de deux scalaires réels entre zéro et un. Nous utilisons ensuite cette caractérisation de la frontière Pareto optimale pour obtenir une caractérisation du point o'u le débit total maximum est atteint. Cet ensemble de solutions potentielles est un sous-ensemble strict de la frontière Pareto optimale, ce qui réduit ainsi considérablement l'espace de recherche du problème NP-complet initial.

Support of many different services, approximately 1000x increase of current data rates, ultra-reliability, low latency and energy/cost efficiency are among the demands from upcoming 5G standard. In order to meet them, researchers investigate various potential technologies involving different network layers and discuss their trade-offs for possible 5G scenarios. Waveform design is a critical part of these efforts and various alternatives have been heavily discussed over the last few years. Besides that, wireless technology is expected to be deployed in many critical applications including the ones involving with daily life activities, health-care and vehicular traffic. Therefore, security of wireless systems is also crucial for a reliable and confidential deployment. In order to achieve these goals in future wireless systems, physical layer (PHY) algorithms play a vital role not only in waveform design but also for improving security. In this dissertation, we draft the ongoing activities in PHY in terms of waveform design and security for providing spectrally efficient and reliable services considering various scenarios, and present our algorithms in this direction. Regarding the waveform design, orthogonal frequency division multiplexing (OFDM) is mostly considered as the base scheme since it is the dominant technology in many existing standards and is also considered for 5G new radio. We specifically propose two approaches for the improvement of OFDM in terms of out-of-band emission and peak to average power ratio. We also present how the requirements of different 5G RAN scenarios reflect on waveform parameters and explore the motivations behind designing advanced frames that include multiple waveforms with different parameters, referred to as numerologies by the 3GPP community, as well as the problems that arise with such coexistence. On the security aspect, we firstly consider broadband communication scenarios and propose practical security approaches that suppress the cyclic features of OFDM and single carrier-frequency domain equalization based waveforms and remove their vulnerability to the eavesdropping attacks. Additionally, an authentication mechanism in PHY is presented for wireless implantable medical devices. Thus, we address the security issues for two critical wireless communication scenarios in PHY to contribute a confidential and reliable deployment of wireless technologies in the near future.

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Spectrum sharing is known as a key solution to accommodate the increasing number of users and the growing demand for throughput in wireless networks. While spectrum sharing improves the data rate in sparse networks, it suffers from interference of concurrent links in dense networks. In fact, interference is the primary barrier to enhance the overall throughput of the network, especially in the medium and high signal-to-noise ratios (SNR’s). Managing interference to overcome this barrier has emerged as a crucial step in developing efficient wireless networks. This thesis deals with optimum and sub-optimum interference management-cancelation in non-cooperative networks. Several techniques for interference management including novel strategies such as interference alignment and structural coding are investigated. These methods are applied to obtain optimum and sub-optimum coding strategies in such networks. It is shown that a single strategy is not able to achieve the maximum throughput in all possible scenarios and in fact a careful design is required to fully exploit all available resources in each realization of the system. This thesis begins with a complete investigation of the capacity region of the two-user Gaussian interference channel. This channel models the basic interaction between two users sharing the same spectrum for data communication. New outer bounds outperforming known bounds are derived using Genie-aided techniques. It is proved that these outer bounds meet the known inner bounds in some special cases, revealing the sum capacity of this channel over a certain range of parameters which has not been known in the past. A novel coding scheme applicable in networks with single antenna nodes is proposed next. This scheme converts a single antenna system to an equivalent Multiple Input Multiple Output (MIMO) system with fractional dimensions. Interference can be aligned along these dimensions and higher multiplexing gains can be achieved. Tools from the field of Diophantine approximation in number theory are used to show that the proposed coding scheme in fact mimics the traditional schemes used in MIMO systems where each data stream is sent along a direction and alignment happens when several streams are received along the same direction. Two types of constellation are proposed for the encoding part, namely the single layer constellation and the multi-layer constellation. Using single layer constellations, the coding scheme is applied to the two-user $X$ channel. It is proved that the total Degrees-of-Freedom (DOF), i.e. $\frac{4}{3}$, of the channel is achievable almost surely. This is the first example in which it is shown that a time invariant single antenna system does not fall short of achieving this known upper bound on the DOF. Using multi-layer constellations, the coding scheme is applied to the symmetric three-user GIC. Achievable DOFs are derived for all channel gains. It is observed that the DOF is everywhere discontinuous (as a function of the channel gain). In particular, it is proved that for the irrational channel gains the achievable DOF meets the upper bound of $\frac{3}{2}$. For the rational gains, the achievable DOF has a gap to the known upper bounds. By allowing carry over from multiple layers, however, it is shown that higher DOFs can be achieved for the latter. The $K$-user single-antenna Gaussian Interference Channel (GIC) is considered, where the channel coefficients are NOT necessarily time-variant or frequency selective. It is proved that the total DOF of this channel is $\frac{K}{2}$ almost surely, i.e. each user enjoys half of its maximum DOF. Indeed, we prove that the static time-invariant interference channels are rich enough to allow simultaneous interference alignment at all receivers. To derive this result, we show that single-antenna interference channels can be treated as \emph{pseudo multiple-antenna systems} with infinitely-many antennas. Such machinery enables us to prove that the real or complex $M \times M$ MIMO GIC achieves its total DOF, i.e., $\frac{MK}{2}$, $M \geq 1$. The pseudo multiple-antenna systems are developed based on a recent result in the field of Diophantine approximation which states that the convergence part of the Khintchine-Groshev theorem holds for points on non-degenerate manifolds. As a byproduct of the scheme, the total DOFs of the $K\times M$ $X$ channel and the uplink of cellular systems are derived. Interference alignment requires perfect knowledge of channel state information at all nodes. This requirement is sometimes infeasible and users invoke random coding to communicate with their corresponding receivers. Alternative interference management needs to be implemented and this problem is addressed in the last part of the thesis. A coding scheme for a single user communicating in a shared medium is proposed. Moreover, polynomial time algorithms are proposed to obtain best achievable rates in the system. Successive rate allocation for a $K$-user interference channel is performed using polynomial time algorithms.