Hardware impairments (HWIs) impose a huge challenge on modern wireless commu- nication systems owing to the characteristics like compactness, least complexity, cost ef- fectiveness and high energy efficiency. Numerous techniques are implemented to minimize the detrimental effects of these HWIs ,however, the residual HWIs may still appear as an additive distortion, multiplicative interference, or an aggregate of both. Numerous studies have commenced efforts to model one or the other forms of hardware impairments in the ra- dio frequency (RF) transceivers. Many presented the widely linear model for in-phase and quadrature imbalance (IQI) but failed to recognize the impropriety induced in the system because of the self-interfering signals. Therefore, we have presented not only a rigorous ag- gregate impairment model along with its complete impropriety statistical characterization but also the appropriate performance analysis to quantify their degradation effects. Lat- est advances have endorsed the superiority of incorporating more generalized impropriety phenomenon as opposed to conventional propriety. In this backdrop, we propose the improper Gaussian signaling (IGS) to mitigate the drastic impact of HWIs and improve the system performance in terms of achievable rate and outage probability. Recent contributions have advocated the employment of IGS over traditional proper Gaussian signaling (PGS) in various interference limited scenarios even in the absence of any improper noise/interference. It is pertaining to the additional degree of freedom (DoF) offered by IGS, which can be optimized to reap maximum benefits. This reduced-entropy signaling is the preferred choice to pose minimal interference to a legitimate network yielding another mechanism to tackle undesired interference. Evidently, the incorporation of both inherent and induced impropriety characteristics is critical for effective utilization. Most of the recent research revolves around the theoretical analysis and advantages of improper signaling with minimal focus on its practical realization. We bridge this gap by adopting and optimizing asymmetric signaling (AS) which is the finite discrete implemen- tation of the improper signaling. We propose the design of both structural and stochastic shaping to realize AS. Structural shaping involves geometric shaping (GS) of the symbol constellation using some rotation and translation matrices. Whereas, stochastic shaping as- signs non-uniform prior probabilities to the symbols. Furthermore, hybrid shaping (HS) is also proposed to reap the gains of both geometric and probabilistic shaping. AS is proven superior to the conventional M-ary symmetric signaling in all of its forms. To this end, probabilistic shaping (PS) demonstrates the best trade-off between the performance en- hancement and added complexity. This research motivates further investigation for the utilization of impropriety concepts in the upcoming generations of wireless communications. It opens new paradigms in inter- ference management and another dimension in the signal space. Besides communications, the impropriety characterization has also revealed numerous applications in the fields of medicine, acoustics, geology, oceanography, economics, bioinformatics, forensics, image processing, computer vision, and power grids.

Next generation of wireless communication mostly relies on multiple-input multipleoutput (MIMO) configuration and full-duplex relaying to improve data-rates, spectrale efficiency, spatial-multiplexing, quality-of-service and energy-efficiency etc. However, multiple radio frequency (RF) transceivers in MIMO system and multi-hops in relay networks, accumulate transceiver impairments, rendering an unacceptable system performance. Majority of the technical contributions either assume ideal hardware or inappropriately model hardware impairments which often induce misleading results especially for high data-rate communication systems. We propose statistical mathematical modeling of various hardware impairment (HWI) to characterize their deteriorating effects on the information signal. In addition, we model the aggregate HWI as improper Gaussian signaling (IGS), to fully characterize their asymmetric properties and the self-interfering signal attribute under I/Q imbalance. The proposed model encourages to adopt asymmetric transmission scheme, as opposed to traditional symmetric signaling. First, we present statistical baseband equivalent mathematical models for general MIMO system and two special scenarios of receive and transmit diversity systems under HWI. Then, we express their achievable rate under PGS and IGS transmit schemes. Moreover, we tune the IGS statistical characteristics to maximize the achievable rate. We also present optimal beam-forming/pre-coding and receive combiner vector for multiple-input single-output (MISO) and single-input multiple output (SIMO) systems, which lead to SDNR maximization. Moreover, we propose an adaptive scheme to switch between maximal IGS (MIGS) and PGS transmission based on the described conditions to reduce computational overhead. Subsequently, two case studies are presented. 1) Outage analysis has been carried out for SIMO, under transceiver distortion noise, for two diversity combining schemes 2) The benefits of employing IGS is investigated in full duplex relaying (FDR) suffering from two types of interference, the residual self-interference (RSI) and I/Q distortions. We further optimize the pseudo-variance to compensate the interference impact and improve end-to-end achievable rate. Finally, we validate the analytic expressions through simulation results, to quantify the performance degradation in the absence of ideal transceivers and the gain reaped from adopting IGS scheme compared with PGS 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>

Wireless communications are important in our highly connected world. The amount of data being transferred in cellular networks is steadily growing, and consequently more capacity is needed. This thesis considers the problem of downlink capacity improvement from the perspective of multicell coordination. By employing multiple antennas at the transmitters and receivers of a multicell network, the inherent spatial selectivity of the users can be exploited in order to increase the capacity through linear precoding and receive filtering. For the coordination between cells, distributed algorithms are often sought due to their low implementation complexity and robustness. In this context, the thesis considers two problem domains: base station clustering and coordinated precoding. Base station clustering corresponds to grouping the cell base stations into disjoint clusters in order to reduce the coordination overhead. This is needed in intermediate-sized to large networks, where the overhead otherwise would be overwhelmingly high. Two solution methods for the clustering problem are proposed: an optimal centralized method, as well as a heuristic distributed method. The optimal method applies to a family of throughput models and exploits the structure of the model to find bounds that can be used to focus the search for the optimal clustering into promising territories. The distributed method instead uses notions from coalitional game theory, where the base stations are modelled as rational and intelligent players in a game. By letting the players make individual deviations that benefit them in the game, i.e.\@ switching clusters, a distributed coalition formation algorithm is obtained. Coordinated precoding is the act of finding the linear precoders and receive filters that maximize the network performance, given a base station clustering. Four specific challenges are studied in this problem domain. First, coordinated precoding under intercluster interference is considered. The channels of the intercluster links are not explicitly estimated due to overhead reasons, and these links thus lead to intercluster interference. By exploiting the known statistics of the intercluster channels, a robust and distributed coordinated precoding algorithm is developed. Second, coordinated precoding under imperfect channel state information is considered. Relying on the channel reciprocity under time-division duplex operation, a distributed estimation framework is proposed. Given the estimated channels, a robust and distributed coordinated precoding algorithm is then derived. Third, coordinated precoding under imperfect radio hardware is considered. By modelling the radio frequency distortion noises, a distributed coordinated precoding method that accounts for the imperfections is proposed. Fourth, joint coordinated precoding and discrete rate selection is considered. By bounding and linearizing an originally intractable optimization problem, a heuristic algorithm is derived which selects the transmit rate from a finite set and simultaneously forms the linear precoders and receive filters. / Trådlös kommunikation är ett viktigt verktyg i dagens ständigt uppkopplade värld. Datamängden som överförs i mobilnätverk ökar stadigt och därmed behovet av mer kapacitet. För att öka kapaciteten i nedlänken så utvecklar denna avhandling nya metoder för koordinering av multicellnätverk. Med flerantenniga sändare och mottagare så kan den spatiala selektiviteten hos mottagarna utnyttjas för att separera dem, vilket ger en ökad kapacitet. För denna koordinering är distribuerade algoritmer ofta att föredra eftersom de är robusta och har låg implementeringskomplexitet. I detta sammanhang undersöker denna avhandling två problemområden: basstationsgruppering och samordnad förkodning. Basstationsgruppering innebär att basstationerna delas in i disjunkta grupper, vilket minskar overheadkostnaden för samordningen. Detta är framför allt nödvändigt i medelstora till stora nätverk, eftersom overheadkostnaden för koordineringen av dessa annars skulle bli för stor. Två lösningar för basstationsgruppering presenteras: dels en optimal och centraliserad metod samt dels en heuristisk och distribuerad metod. Den optimala och centraliserade metoden kan hantera en familj av modeller för den totala datatakten och utnyttjar strukturen i modellen för att fokusera sökandet efter den optimala grupperingen mot lovande områden. Den heuristiska och distribuerade metoden bygger på spelteori för koalitioner och modellerar basstationerna som rationella och intelligenta spelare i ett spel. En distribuerad algoritm för koalitionsformering härleds genom att låta spelarna göra individuella förflyttningar, dvs. byta grupp, när det gynnar dem under spelets regler. Vid samordnad förkodning använder de flerantenniga sändarna och mottagarna linjära förkodare och mottagningsfilter för att maximera nätverkets prestanda. Inom detta problemområde undersöks fyra olika specifika problem. Först undersöks problemet när det finns störningar mellan basstationsgrupperna. För att hålla nere mängden overhead så skattas inte kanalerna mellan grupperna, vilket ger upphov till störningar hos mottagarna. Genom att utnyttja den kända statistiska informationen för dessa okända kanaler kan en robust och distribuerade samordningsmetod för förkodningen utvecklas. Därnäst undersöks problemet då kanalkännedomen är bristfällig i allmänhet. Reciprociteten som uppstår vid tidsdelningsduplexning utnyttjas och flera distribuerade skattningsmetoder härleds. Givet den skattade kanalkännedomen föreslås en robust metod för samordnad förkodning. Därnäst undersöks problemet med samordnad förkodning då radiohårdvaran är bristfällig. En modell för det distortionsbrus som skapas av den bristfälliga hårdvaran används för att föreslå en robust distribuerad metod för samordnad förkodning för detta scenario. Slutligen undersöks valet av diskret datatakt med simultan samordnad förkodning. En heuristisk algoritm utvecklas som löser ett begränsat optimeringsproblem. Algoritmen väljer sänddatatakten från en ändlig mängd och bestämmer simultant de linjära förkodarna och mottagningsfiltrena. / <p>QC 20160407</p>

With the increasing maturity of unmanned aerial vehicles (UAVs), also known as drones, wireless ecosystem is experiencing an unprecedented paradigm shift. These aerial platforms are specifically appealing for a variety of applications due to their rapid and flexible deployment, cost-effectiveness, and high chance of forming line-of-sight (LoS) links to the ground nodes. As with any new technology, the benefits of incorporating UAVs in existing cellular networks cannot be characterized without completely exploring the underlying trade space. This requires a detailed system-level analysis of drone cellular networks by taking the unique features of UAVs into account, which is the main objective of this dissertation. We first focus on a static setup and characterize the performance of a three-dimensional (3D) two-hop cellular network in which terrestrial base stations (BSs) coexist with UAVs to serve a set of ground user equipment (UE). In particular, a UE connects either directly to its serving terrestrial BS by an access link or connects first to its serving UAV which is then wirelessly backhauled to a terrestrial BS (joint access and backhaul). We consider realistic antenna radiation patterns for both BSs and UAVs using practical models developed by the third generation partnership project (3GPP). We assume a probabilistic channel model for the air-to-ground transmission, which incorporates both LoS and non-LoS links. Assuming the max-power association policy, we study the performance of the network in both amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols. Using tools from stochastic geometry, we analyze the joint distribution of distance and zenith angle of the closest (and serving) UAV to the origin in a 3D setting. Further, we identify and extensively study key mathematical constructs as the building blocks of characterizing the received signal-to-interference-plus-noise ratio (SINR) distribution. Using these results, we obtain exact mathematical expressions for the coverage probability in both AF and DF relaying protocols. Furthermore, considering the fact that backhaul links could be quite weak because of the downtilted antennas at the BSs, we propose and analyze the addition of a directional uptilted antenna at the BS that is solely used for backhaul purposes. The superiority of having directional antennas with wirelessly backhauled UAVs is further demonstrated via extensive simulations. Second, we turn our attention to a mobile setup and characterize the performance of several canonical mobility models in a drone cellular network in which UAV base stations serve UEs on the ground. In particular, we consider the following four mobility models: (i) straight line (SL), (ii) random stop (RS), (iii) random walk (RW), and (iv) random waypoint (RWP), among which the SL mobility model is inspired by the simulation models used by the 3GPP for the placement and trajectory of UAVs, while the other three are well-known canonical models (or their variants) that offer a useful balance between realism and tractability. Assuming the nearest-neighbor association policy, we consider two service models for the UEs: (i) UE independent model (UIM), and (ii) UE dependent model (UDM). While the serving UAV follows the same mobility model as the other UAVs in the UIM, it is assumed to fly towards the UE of interest in the UDM and hover above its location after reaching there. We then present a unified approach to characterize the point process of UAVs for all the mobility and service models. Using this, we provide exact mathematical expressions for the average received rate and the session rate as seen by the typical UE. Further, using tools from the calculus of variations, we concretely demonstrate that the simple SL mobility model provides a lower bound on the performance of other general mobility models (including the ones in which UAVs follow curved trajectories) as long as the movement of each UAV in these models is independent and identically distributed (i.i.d.). Continuing our analysis on mobile setups, we analyze the handover probability in a drone cellular network, where the initial positions of the UAVs serving the ground UEs are modeled by a homogeneous Poisson point process (PPP). Inspired by the mobility model considered in the 3GPP studies, we assume that all the UAVs follow the SL mobility model, i.e., move along straight lines in random directions. We further consider two different scenarios for the UAV speeds: (i) same speed model (SSM), and (ii) different speed model (DSM). Assuming nearest-neighbor association policy, we characterize the handover probability of this network for both mobility scenarios. For the SSM, we compute the exact handover probability by establishing equivalence with a single-tier terrestrial cellular network, in which the BSs are static while the UEs are mobile. We then derive a lower bound for the handover probability in the DSM by characterizing the evolution of the spatial distribution of the UAVs over time. After performing these system-level analyses on UAV networks, we focus our attention on the air-to-ground wireless channel and attempt to understand its unique features. For that, we first study the impact of UAV wobbling on the coherence time of the wireless channel between UAVs and a ground UE, using a Rician multi-path channel model. We consider two different scenarios for the number of UAVs: (i) single UAV scenario (SUS), and (ii) multiple UAV scenario (MUS). For each scenario, we model UAV wobbling by two random processes, i.e., the Wiener and sinusoidal processes, and characterize the channel autocorrelation function (ACF) which is then used to derive the coherence time of the channel. For the MUS, we further show that the UAV-UE channels for different UAVs are uncorrelated from each other. One key observation that is revealed from our analysis is that even for small UAV wobbling, the coherence time of the channel may degrade quickly, which may make it difficult to track the channel and establish a reliable communication link. Finally, we develop an impairments-aware air-to-ground unified channel model that incorporates the effect of both wobbling and hardware impairments, where the former is caused by random physical fluctuations of UAVs, and the latter by intrinsic radio frequency (RF) nonidealities at both the transmitter and receiver, such as phase noise, in-phase/quadrature (I/Q) imbalance, and power amplifier (PA) nonlinearity. The impact of UAV wobbling is modeled by two stochastic processes, i.e., the canonical Wiener process and the more realistic sinusoidal process. On the other hand, the aggregate impact of all hardware impairments is modeled as two multiplicative and additive distortion noise processes, which is a well-accepted model. For the sake of generality, we consider both wide-sense stationary (WSS) and nonstationary processes for the distortion noises. We then rigorously characterize the ACF of the wireless channel, using which we provide a comprehensive analysis of four key channel-related metrics: (i) power delay profile (PDP), (ii) coherence time, (iii) coherence bandwidth, and (iv) power spectral density (PSD) of the distortion-plus-noise process. Furthermore, we evaluate these metrics with reasonable UAV wobbling and hardware impairment models to obtain useful insights. Similar to our observation above, this work again demonstrates that the coherence time severely degrades at high frequencies even for small UAV wobbling, which renders air-to-ground channel estimation very difficult at these frequencies. / Doctor of Philosophy / With the increasing maturity of unmanned aerial vehicles (UAVs), also known as drones, wireless ecosystem is changing dramatically. Owing to their ease of deployment and high chance of forming direct line-of-sight (LoS) links with the other UAVs and ground users, they are very appealing for numerous wireless applications. As with any new technology, exploring the full extent of the benefits of UAVs requires careful exploration of the underlying trade space. Therefore, in this dissertation, our main focus is on the analysis of such aerial networks, their interplay with the current terrestrial networks, and the unique features of UAVs that make them different from conventional ground nodes. One important aspect of aerial communication systems is their integration into our current cellular networks. Clearly, the addition of these new aerial components has the potential of benefiting both the ground users (such as mobile users watching a concert who need cellular connectivity to share the moments) and the cellular base station (BS). Therefore, careful analysis of these ``aerial-terrestrial" networks is of utmost importance. In the first phase of this dissertation, we perform this analysis by interpreting the network as a combination of one-hop (from the BS to the user) and two-hop (from the BS to the UAV and then from the UAV to the UE) links. Since the locations of BSs, UAVs, and users are irregular in general, we use tools from stochastic geometry to carry out our analysis, which is a field of mathematics that studies random shapes and patterns. Also, because existing terrestrial BSs are primarily designed to serve the ``ground", we propose the addition of a separate set of antennas at the BS site that is solely used to serve the ``air", i.e., to communicate with the UAVs, and demonstrate the benefits of this additional infrastructure in detail. One of our assumptions in the first phase of this dissertation was that the considered network was static, i.e., the UAVs were hovering in the air and the BSs/users were also not moving. In the second phase, on the other hand, we explore the benefits and challenges of a mobile network of UAVs and characterize the performance of several canonical mobility models in a drone cellular network. In particular, one of the models that we studied extensively is the so-called straight line (SL) mobility model, which was inspired by the simulation models used by the third generation partnership project (3GPP) for the placement and trajectory of UAVs. Since the locations of UAVs could be assumed random in general, we use tools from stochastic geometry and present a unified approach to characterize the point process of UAVs, using which we obtained exact mathematical expressions for the average received rate (i.e., throughput) as seen by the users. Continuing our analysis on mobile setups and using the SL mobility model, we also analyze the handover probability in a drone cellular network, which is defined as the event when the serving UAV of a user changes. By establishing equivalence between our aerial setup with a terrestrial cellular network, we compute the exact handover probability in drone cellular networks. In the final phase of this dissertation, we focus our attention on the air-to-ground wireless channel and attempt to understand its unique features. For that, we propose an impairments-aware unified channel model for an air-to-ground wireless communication system and extensively analyze the link between a hovering UAV in the air and a static user on the ground. In particular, we consider two different types of impairments: (i) UAV wobbling, and (ii) hardware impairments, where the former is caused by random physical fluctuations, and the latter by intrinsic radio frequency (RF) nonidealities at both the transmitter and receiver. Using appropriate models for each type of impairment, we rigorously characterize the autocorrelation function (ACF) of the wireless channel, using which we provide a comprehensive analysis of key channel-related metrics, such as coherence time and coherence bandwidth. One key observation that is revealed from our analysis is that even for small UAV wobbling and low hardware impairment levels, the coherence time of the channel may degrade quickly at high frequencies, which could make it difficult to track the channel and establish a reliable communication link at these frequencies.