While the channel capacity of an isolated noise-limited wireless link is well-understood, the same is not true for the interference-limited wireless links that coexist in the same area and occupy the same frequency band(s). The performance of these wireless systems is coupled to each other due to the mutual interference. One such wireless scenario is modeled as a network of simultaneously communicating node pairs and is generally referred to as an interference channel (IC). The problem of characterizing the capacity of an IC is one of the most interesting and long-standing open problems in information theory. A popular way of characterizing the capacity of an IC is to maximize the achievable sum-rate by treating interference as Gaussian noise, which is considered optimal in low-interference scenarios. While the sum-rate of the single-band SISO IC is relatively well understood, it is not so when the users have multiple-bands and multiple-antennas for transmission. Therefore, the study of the optimal sum-rate of the multi-band MIMO IC is the main goal of this thesis. The sum-rate maximization problem for these ICs is formulated and is shown to be quite similar to the one already known for single-band MIMO ICs. This problem is reduced to the problem of finding the optimal fraction of power to be transmitted over each spatial channel in each frequency band. The underlying optimization problem, being non-linear and non-convex, is difficult to solve analytically or by employing local optimization techniques. Therefore, we develop a global optimization algorithm by extending the Reformulation and Linearization Technique (RLT) based Branch and Bound (BB) strategy to find the provably optimal solution to this problem. We further show that the spatial and spectral channels are surprisingly similar in a multi-band multi-antenna IC from a sum-rate maximization perspective. This result is especially interesting because of the dissimilarity in the way the spatial and frequency channels affect the perceived interference. As a part of this study, we also develop some rules-of-thumb regarding the optimal power allocation strategies in multi-band MIMO ICs in various interference regimes. Due to the recent popularity of Interference Alignment (IA) as a means of approaching capacity in an IC (in high-interference regime), we also compare the sum-rates achievable by our technique to the ones achievable by IA. The results indicate that the proposed power control technique performs better than IA in the low and intermediate interference regimes. Interestingly, the performance of the power control technique improves further relative to IA with an increase in the number of orthogonal spatial or frequency channels. / Master of Science

This thesis is targeted at precoding methods and resource allocation for the downlink of fixed multi-user multi-antenna broadband wireless systems. We explore different utilizations of precoders in transmission over frequency-selective channels. We first consider the weighted sum-rate (WSR) maximization problem for multi-carrier systems using linear precoding and propose a low complexity algorithm which exhibits near-optimal performance. Moreover, we offer a novel rate allocation method that utilizes the signalto- noise-ratio (SNR) gap to capacity concept to choose the rates to allocate to each data stream. We then study a single-carrier transmission scheme that overcomes known impairments associated with multi-carrier systems. The proposed scheme utilizes timereversal space-time block coding (TR-STBC) to orthogonalize the downlink receivers and performs the required pre-equalization using Tomlinson-Harashima precoding (THP).We finally discuss the strengths and weaknesses of the proposed method.

This thesis is targeted at precoding methods and resource allocation for the downlink of fixed multi-user multi-antenna broadband wireless systems. We explore different utilizations of precoders in transmission over frequency-selective channels. We first consider the weighted sum-rate (WSR) maximization problem for multi-carrier systems using linear precoding and propose a low complexity algorithm which exhibits near-optimal performance. Moreover, we offer a novel rate allocation method that utilizes the signalto- noise-ratio (SNR) gap to capacity concept to choose the rates to allocate to each data stream. We then study a single-carrier transmission scheme that overcomes known impairments associated with multi-carrier systems. The proposed scheme utilizes timereversal space-time block coding (TR-STBC) to orthogonalize the downlink receivers and performs the required pre-equalization using Tomlinson-Harashima precoding (THP).We finally discuss the strengths and weaknesses of the proposed method.

Abstract The application of optimization techniques for resource management in wireless communication networks is considered in this thesis. It is understood that a wide variety of resource management problems of recent interest, including power/rate control, link scheduling, cross-layer control, network utility maximization, beamformer design of multiple-input multiple-output networks, and many others are directly or indirectly reliant on the general weighted sum-rate maximization (WSRMax) problem. Thus, in this dissertation a greater emphasis is placed on the WSRMax problem, which is known to be NP-hard. A general method, based on the branch and bound technique, is developed, which solves globally the nonconvex WSRMax problem with an optimality certificate. Efficient analytic bounding techniques are derived as well. More broadly, the proposed method is not restricted to WSRMax. It can also be used to maximize any system performance metric, which is Lipschitz continuous and increasing on signal-to-interference-plus-noise ratio. The method can be used to find the optimum performance of any network design method, which relies on WSRMax, and therefore it is also useful for evaluating the performance loss encountered by any heuristic algorithm. The considered link-interference model is general enough to accommodate a wide range of network topologies with various node capabilities, such as singlepacket transmission, multipacket transmission, simultaneous transmission and reception, and many others. Since global methods become slow in large-scale problems, fast local optimization methods for the WSRMax problem are also developed. First, a general multicommodity, multichannel wireless multihop network where all receivers perform singleuser detection is considered. Algorithms based on homotopy methods and complementary geometric programming are developed for WSRMax. They are able to exploit efficiently the available multichannel diversity. The proposed algorithm, based on homotopy methods, handles efficiently the self interference problem that arises when a node transmits and receives simultaneously in the same frequency band. This is very important, since the use of supplementary combinatorial constraints to prevent simultaneous transmissions and receptions of any node is circumvented. In addition, the algorithm together with the considered interference model, provide a mechanism for evaluating the gains when the network nodes employ self interference cancelation techniques with different degrees of accuracy. Next, a similar multicommodity wireless multihop network is considered, but all receivers perform multiuser detection. Solutions for the WSRMax problem are obtained by imposing additional constraints, such as that only one node can transmit to others at a time or that only one node can receive from others at a time. The WSRMax problem of downlink OFDMA systems is also considered. A fast algorithm based on primal decomposition techniques is developed to jointly optimize the multiuser subcarrier assignment and power allocation to maximize the weighted sum-rate (WSR). Numerical results show that the proposed algorithm converges faster than Lagrange relaxation based methods. Finally, a distributed algorithm for WSRMax is derived in multiple-input single-output multicell downlink systems. The proposed method is based on classical primal decomposition methods and subgradient methods. It does not rely on zero forcing beamforming or high signal-to-interference-plus-noise ratio approximation like many other distributed variants. The algorithm essentially involves coordinating many local subproblems (one for each base station) to resolve the inter-cell interference such that the WSR is maximized. The numerical results show that significant gains can be achieved by only a small amount of message passing between the coordinating base stations, though the global optimality of the solution cannot be guaranteed. / Tiivistelmä Tässä työssä tutkitaan optimointimenetelmien käyttöä resurssienhallintaan langattomissa tiedonsiirtoverkoissa. Monet ajankohtaiset resurssienhallintaongelmat, kuten esimerkiksi tehonsäätö, datanopeuden säätö, radiolinkkien ajastus, protokollakerrosten välinen optimointi, verkon hyötyfunktion maksimointi ja keilanmuodostus moniantenniverkoissa, liittyvät joko suoraan tai epäsuorasti painotetun summadatanopeuden maksimointiongelmaan (weighted sum-rate maximization, WSRMax). Tästä syystä tämä työ keskittyy erityisesti WSRMax-ongelmaan, joka on tunnetusti NP-kova. Työssä kehitetään yleinen branch and bound -tekniikkaan perustuva menetelmä, joka ratkaisee epäkonveksin WSRMax-ongelman globaalisti ja tuottaa todistuksen ratkaisun optimaalisuudesta. Työssä johdetaan myös tehokkaita analyyttisiä suorituskykyrajojen laskentatekniikoita. Ehdotetun menetelmän käyttö ei rajoitu vain WSRMax-ongelmaan, vaan sitä voidaan soveltaa minkä tahansa suorituskykymetriikan maksimointiin, kunhan se on Lipschitz-jatkuva ja kasvava signaali-häiriö-plus-kohinasuhteen funktiona. Menetelmää voidaan käyttää minkä tahansa WSRMax-ongelmaan perustuvan verkkosuunnittelumenetelmän optimaalisen suorituskyvyn määrittämiseen, ja siksi sitä voidaan hyödyntää myös minkä tahansa heuristisen algoritmin aiheuttaman suorituskykytappion arvioimiseen. Tutkittava linkki-häiriömalli on riittävän yleinen monien erilaisten verkkotopologioiden ja verkkosolmujen kyvykkyyksien mallintamiseen, kuten esimerkiksi yhden tai useamman datapaketin siirtoon sekä yhtäaikaiseen lähetykseen ja vastaanottoon. Koska globaalit menetelmät ovat hitaita suurien ongelmien ratkaisussa, työssä kehitetään WSRMax-ongelmalle myös nopeita paikallisia optimointimenetelmiä. Ensiksi käsitellään yleistä useaa eri yhteyspalvelua tukevaa monikanavaista langatonta monihyppyverkkoa, jossa kaikki vastaanottimet suorittavat yhden käyttäjän ilmaisun, ja kehitetään algoritmeja, joiden perustana ovat homotopiamenetelmät ja komplementaarinen geometrinen optimointi. Ne hyödyntävät tehokkaasti saatavilla olevan monikanavadiversiteetin. Esitetty homotopiamenetelmiin perustuva algoritmi käsittelee tehokkaasti itsehäiriöongelman, joka syntyy, kun laite lähettää ja vastaanottaa samanaikaisesti samalla taajuuskaistalla. Tämä on tärkeää, koska näin voidaan välttää lisäehtojen käyttö yhtäaikaisen lähetyksen ja vastaanoton estämiseksi. Lisäksi algoritmi yhdessä tutkittavan häiriömallin kanssa auttaa arvioimaan, paljonko etua saadaan, kun laitteet käyttävät itsehäiriön poistomenetelmiä erilaisilla tarkkuuksilla. Seuraavaksi tutkitaan vastaavaa langatonta monihyppyverkkoa, jossa kaikki vastaanottimet suorittavat monen käyttäjän ilmaisun. Ratkaisuja WSRMax-ongelmalle saadaan asettamalla lisäehtoja, kuten että vain yksi lähetin kerrallaan voi lähettää tai että vain yksi vastaanotin kerrallaan voi vastaanottaa. Edelleen tutkitaan WSRMax-ongelmaa laskevalla siirtotiellä OFDMA-järjestelmässä, ja johdetaan primaalihajotelmaan perustuva nopea algoritmi, joka yhteisoptimoi monen käyttäjän alikantoaalto- ja tehoallokaation maksimoiden painotetun summadatanopeuden. Numeeriset tulokset osoittavat, että esitetty algoritmi suppenee nopeammin kuin Lagrangen relaksaatioon perustuvat menetelmät. Lopuksi johdetaan hajautettu algoritmi WSRMax-ongelmalle monisoluisissa moniantennilähetystä käyttävissä järjestelmissä laskevaa siirtotietä varten. Esitetty menetelmä perustuu klassisiin primaalihajotelma- ja aligradienttimenetelmiin. Se ei turvaudu nollaanpakotus-keilanmuodostukseen tai korkean signaali-häiriö-plus-kohinasuhteen approksimaatioon, kuten monet muut hajautetut muunnelmat. Algoritmi koordinoi monta paikallista aliongelmaa (yhden kutakin tukiasemaa kohti) ratkaistakseen solujen välisen häiriön siten, että WSR maksimoituu. Numeeriset tulokset osoittavat, että merkittävää etua saadaan jo vähäisellä yhdessä toimivien tukiasemien välisellä viestinvaihdolla, vaikka globaalisti optimaalista ratkaisua ei voidakaan taata.

This dissertation addresses multi-layer optimization aspects of multiple input multiple output (MIMO) and deep learning-based communication systems. The initial focus is on the rate optimization for multi-user MIMO (MU-MIMO) configurations; specifically, multiple access channel (MAC) and interference channel (IC). First, the ergodic sum rates of MIMO MAC and IC configurations are determined by jointly integrating the error and overhead effects due to channel estimation (training) and feedback into the rate optimization. Then, we investigated methods that will increase the achievable rate for parallel Gaussian IC (PGIC) which is a special case of MIMO IC where there is no interference between multiple antenna elements. We derive a generalized iterative waterfilling algorithm for power allocation that maximizes the ergodic achievable rate. We verified the sum rate improvement with our proposed scheme through extensive simulation tests. Next, we introduce a novel physical layer scheme for single user MIMO spatial multiplexing systems based on unsupervised deep learning using an autoencoder. Both transmitter and receiver are designed as feedforward neural networks (FNN) and constellation diagrams are optimized to minimize the symbol error rate (SER) based on the channel characteristics. We first evaluate the SER in the presence of a constant Rayleigh-fading channel as a performance upper bound. Then, we quantize the Gaussian distribution and train the autoencoder with multiple quantized channel matrices. The channel is provided as an input to both the transmitter and the receiver. The performance exceeds that of conventional communication systems both when the autoencoder is trained and tested with single and multiple channels and the performance gain is sustained after accounting for the channel estimation error. Moreover, we evaluate the performance with increasing number of quantization points and when there is a difference between training and test channels. We show that the performance loss is minimal when training is performed with sufficiently large number of quantization points and number of channels. Finally, we develop a distributed and decentralized MU-MIMO link selection and activation protocol that enables MU-MIMO operation in wireless networks. We verified the performance gains with the proposed protocol in terms of average network throughput. / Doctor of Philosophy / Multiple Input Multiple Output (MIMO) wireless systems include multiple antennas both at the transmitter and receiver and they are widely used today in cellular and wireless local area network systems to increase robustness, reliability and data rate. Multi-user MIMO (MU-MIMO) configurations include multiple access channel (MAC) where multiple transmitters communicate simultaneously with a single receiver; interference channel (IC) where multiple transmitters communicate simultaneously with their intended receivers; and broadcast channel (BC) where a single transmitter communicates simultaneously with multiple receivers. Channel state information (CSI) is required at the transmitter to precode the signal and mitigate interference effects. This requires CSI to be estimated at the receiver and transmitted back to the transmitter in a feedback loop. Errors occur during both channel estimation and feedback processes. We initially analyze the achievable rate of MAC and IC configurations when both channel estimation and feedback errors are taken into account in the capacity formulations. We treat the errors associated with channel estimation and feedback as additional noise. Next, we develop methods to maximize the achievable rate for IC by using interference cancellation techniques at the receivers when the interference is very strong. We consider parallel Gaussian IC (PGIC) which is a special case of MIMO IC where there is no interference between multiple antenna elements. We develop a power allocation scheme which maximizes the ergodic achievable rate of the communication systems. We verify the performance improvement with our proposed scheme through simulation tests. Standard optimization techniques are used to determine the fundamental limits of MIMO communications systems. However, there is still a gap between current operational systems and these limits due to complexity of these solutions and limitations in their assumptions. Next, we introduce a novel physical layer scheme for MIMO systems based on machine learning; specifically, unsupervised deep learning using an autoencoder. An autoencoder consists of an encoder and a decoder that compresses and decompresses data, respectively. We designed both the encoder and the decoder as feedforward neural networks (FNNs). In our case, encoder performs transmitter functionalities such as modulation and error correction coding and decoder performs receiver functionalities such as demodulation and decoding as part of the communication system. Channel is included as an additional layer between the encoder and decoder. By incorporating the channel effects in the design process of the autoencoder and jointly optimizing the transmitter and receiver, we demonstrate the performance gains over conventional MIMO communication schemes. Finally, we develop a distributed and decentralized MU-MIMO link selection and activation protocol that enables MU-MIMO operation in wireless networks. We verified the performance gains with the proposed protocol in terms of average network throughput.

Abstract This thesis concentrates on the design and evaluation of spatial user multiplexing methods via linear transmit-receive processing for wireless cellular multi-user multiple-input multiple-output (MIMO) communication systems operating in the time-division duplexing (TDD) mode. The main focus is on the acquisition of effective channel state information (CSI) that facilitates decentralized processing so that the network nodes – base stations (BS) and user terminals (UT), each employing an arbitrary number of antenna elements – are able to locally participate in the network adaptation. The proposed methods rely on the uplink-downlink channel reciprocity and spatially precoded over-the-air pilot signaling. Considering (single-cell) multi-user MIMO systems, coordinated zero-forcing transmit-receive processing schemes for the uplink (UL) are proposed. The BS computes the transmission parameters in a centralized manner and employs downlink (DL) pilot signals to convey the information of the beamformers to be used by the UTs. When coexisting with the DL zero-forcing, the precoded DL demodulation pilots can be reused for UL beam allocation, and the precoded UL demodulation pilots are reused in turn for partial channel sounding (CS). As a result, only the precoded pilot symbols are needed in both UL and DL. Moreover, a concept for reducing the number of the required orthogonal UL CS pilot resources is presented. Based on their DL channel knowledge, the multi-antenna UTs form fewer pilot beams by spatial precoding than conventionally needed when transmitting antenna-specific pilots. In the context of DL zero-forcing, when taking into account the CSI estimation error at the BS, the overhead reduction turns out to improve robustness and increase the average system capacity. Considering multi-cell multi-user MIMO systems, decentralized coordinated DL beamforming strategies based on weighted sum rate (WSR) maximization are proposed. An optimization framework where the WSR maximization is carried out via weighted sum mean-squared-error minimization is utilized, and the approach is generalized by employing antenna-specific transmit power constraints. The iterative processing consists of optimization steps that are run locally by the BSs. In one novel strategy, the coordinating cells update their transmit precoders and receivers one cell at a time, which guarantees monotonic convergence of the network-wide problem. The strategy employs separate uplink CS and busy burst pilot signaling to reveal the effective channels of the UTs to the neighboring BSs. In another novel strategy, the monotonic convergence is sacrificed to devise a faster scheme where the BSs are allowed to optimize their variables in parallel based on just the CS responses and additional low-rate backhaul information exchange. The numerical results demonstrate that WSR maximization has the desirable property that spatial user scheduling is carried out implicitly. Finally, methods for UL CS overhead reduction are presented, and the effect of CSI uncertainty is addressed. / Tiivistelmä Tämä väitöskirja keskittyy lineaarisella lähetys- ja vastaanottoprosessoinnilla toteutettavien tilajakomonikäyttömenetelmien suunnitteluun ja arviointiin langattomissa moniantennisissa solukkoverkoissa, jotka hyödyntävät aikajakodupleksointia (TDD). Erityisesti tarkastellaan efektiivisen kanavatiedon hankintaa, joka mahdollistaa hajautetun prosessoinnin siten että verkkoelementit – tukiasemat ja terminaalit, jotka kukin hyödyntävät useaa antennielementtiä – voivat osallistua paikallisesti verkon adaptaatioon. Esitetyt menetelmät perustuvat ylä- ja alalinkin kanavien resiprookkisuuteen ja tilatasossa esikoodattuun opetus- eli pilottisignalointiin ilmarajapinnan yli. Yksisoluisille monikäyttäjä- ja moniantennijärjestelmille esitetään ylälinkin koordinoituja nollaanpakottavia lähetys- ja vastaanottomenetelmiä. Tukiasema laskee lähetysparametrit keskitetysti ja käyttää pilottisignaaleja kertomaan millaista lähetyskeilanmuodostusta terminaalien tulee käyttää. Alalinkin nollaanpakotuksen yhteydessä esikoodattuja demodulaatiopilotteja voidaan uudelleenkäyttää ylälinkin lähetyskeilojen allokointiin, ja esikoodattuja ylälinkin demodulaatiopilotteja uudelleenkäytetään puolestaan osittaiseen kanavan luotaukseen (sounding). Näin ollen molempiin suuntiin tarvitaan vain esikoodatut pilotit. Lisäksi työssä esitetään menetelmä ylälinkin luotauspilottiresurssitarpeen vähentämiseksi. Kanavatietoon perustuen moniantenniset terminaalit muodostavat tilatasossa esikoodattuja pilottilähetyskeiloja, joita tarvitaan vähemmän kuin perinteisiä antennikohtaisia pilotteja. Kun otetaan huomioon kanavanestimointivirhe tukiasemassa, resurssiensäästömenetelmä parantaa häiriösietoisuutta ja nostaa järjestelmän keskimääräistä kapasiteettia alalinkin nollaanpakotuksen yhteydessä. Monisoluisille monikäyttäjä- ja moniantennijärjestelmille esitetään hajautettuja koordinoituja alalinkin keilanmuodostusstrategioita, jotka perustuvat painotetun summadatanopeuden (WSR) maksimointiin. Valitussa optimointikehyksessä WSR:n maksimointi toteutetaan painotetun summaneliövirheen minimoinnin kautta, ja työssä menettelytapa yleistetään antennikohtaisten lähetystehorajoitusten tapaukseen. Iteratiivinen prosessointi koostuu optimointiaskelista, jotka tukiasemat paikallisesti suorittavat. Yhdessä esitetyssä strategiassa yhteistoiminnalliset solut päivittävät lähettimensä ja vastaanottimensa yksi solu kerrallaan, mikä takaa verkonlaajuisen ongelmanratkaisun monotonisen konvergenssin. Tämä strategia käyttää erillisiä ylälinkin luotaussignaaleja sekä varattu-signaaleja ilmaistakseen terminaalien efektiiviset kanavat naapuritukiasemille. Toisessa strategiassa monotoninen konvergenssi uhrataan ja kehitetään nopeammin adaptoituva menetelmä, jossa tukiasemat saavat optimoida muuttujansa rinnakkain, perustuen vain luotaussignaaleihin ja tukiasemien väliseen informaationvaihtoon. Numeeriset tulokset osoittavat, että WSR:n maksimointi toteuttaa aktiivisten käyttäjien valinnan tilatasossa implisiittisesti. Lopuksi esitetään menetelmiä luotauspilottiresurssitarpeen vähentämiseksi ja käsitellään kanavatiedon epävarmuuden vaikutusta.

In the upcoming era of communication systems, there is an anticipated shift towards using lower-grade hardware components to optimize size, cost, and power consumption. This shift is particularly beneficial for multiple-input multiple-output (MIMO) systems and internet-of-things devices, which require numerous components and extended battery lifes. However, using lower-grade components introduces impairments, including various non-linear and time-varying distortions affecting communication signals. Traditionally, these distortions have been treated as additional noise due to the lack of a rigorous theory. This thesis explores new perspective on how distortion structure can be exploited to optimize communication performance. We investigate the problem of distortion-aware beamforming in various scenarios.  In the first part of this thesis, we focus on systems with limited fronthaul capacity. We propose an optimized linear precoding for advanced antenna systems (AAS) operating at a 5G base station (BS) within the constraints of a limited fronthaul capacity, modeled by a quantizer. The proposed novel precoding minimizes the mean-squared error (MSE) at the receiver side using a sphere decoding (SD) approach.  After analyzing MSE minimization, a new linear precoding design is proposed to maximize the sum rate of the same system in the second part of this thesis. The latter problem is solved by a novel iterative algorithm inspired by the classical weighted minimum mean square error (WMMSE) approach. Additionally, a heuristic quantization-aware precoding method with lower computational complexity is presented, showing that it outperforms the quantization-unaware baseline. This baseline is an optimized infinite-resolution precoding which is then quantized. This study reveals that it is possible to double the sum rate at high SNR by selecting weights and precoding matrices that are quantization-aware.  In the third part and final part of this thesis, we focus on the signaling problem in mobile millimeter-wave (mmWave) communication. The challenge of mmWave systems is the rapid fading variations and extensive pilot signaling. We explore the frequency of updating the combining matrix in a wideband mmWave point-to-point MIMO under user equipment (UE) mobility. The concept of beam coherence time is introduced to quantify the frequency at which the UE must update its downlink receive combining matrix. The study demonstrates that the beam coherence time can be even hundreds of times larger than the channel coherence time of small-scale fading. Simulations validate that the proposed lower bound on this defined concept guarantees no more than 50 \% loss of received signal gain (SG). / I den kommande eran av kommunikationssystem finns det en förväntad förändringmot att använda hårdvarukomponenter av lägre kvalitet för att optimera storlek, kostnad och strömförbrukning. Denna förändring är särskilt fördelaktig för MIMO-system(multiple-input multiple-output) och internet-of-things-enheter, som kräver många komponenter och förlängd batteritid. Användning av komponenter av lägre kvalitet medfördock försämringar, inklusive olika icke-linjära och tidsvarierande förvrängningar sompåverkar kommunikationssignaler. Traditionellt har dessa förvrängningar behandlatssom extra brus på grund av avsaknaden av en rigorös teori. Denna avhandling utforskarett nytt perspektiv på hur distorsionsstruktur kan utnyttjas för att optimera kommunikationsprestanda. Vi undersöker problemet med distorsionsmedveten strålformning iolika scenarier. I den första delen av detta examensarbete fokuserar vi på system med begränsadfronthaulkapacitet. Vi föreslår en optimerad linjär förkodning för avancerade antennsystem (AAS) som arbetar vid en 5G-basstation (BS) inom begränsningarna av en begränsad fronthaulkapacitet, modellerad av en kvantiserare. Den föreslagna nya förkodningen minimerar medelkvadratfelet (MSE) på mottagarsidan med användning av ensfäravkodningsmetod (SD). Efter att ha analyserat MSE-minimering, föreslås en ny linjär förkodningsdesignför att maximera summahastigheten för samma system i den andra delen av dennaavhandling. Det senare problemet löses av en ny iterativ algoritm inspirerad av denklassiska vägda minsta medelkvadratfel (WMMSE)-metoden. Dessutom presenterasen heuristisk kvantiseringsmedveten förkodningsmetod med lägre beräkningskomplexitet, som visar att den överträffar den kvantiseringsomedvetna baslinjen. Denna baslinje är en optimerad förkodning med oändlig upplösning som sedan kvantiseras. Dennastudie avslöjar att det är möjligt att fördubbla summahastigheten vid hög SNR genomatt välja vikter och förkodningsmatriser som är kvantiseringsmedvetna. I den tredje delen och sista delen av denna avhandling fokuserar vi på signaleringsproblemet i mobil millimetervågskommunikation (mmWave). Utmaningen medmmWave-system är de snabba blekningsvariationerna och omfattande pilotsignalering.Vi utforskar frekvensen av att uppdatera den kombinerande matrisen i en bredbandsmmWave punkt-till-punkt MIMO under användarutrustning (UE) mobilitet. Konceptet med strålkoherenstid introduceras för att kvantifiera frekvensen vid vilken UE:nmåste uppdatera sin nedlänksmottagningskombinationsmatris. Studien visar att strålkoherenstiden kan vara till och med hundratals gånger större än kanalkoherenstiden försmåskalig fädning. Simuleringar bekräftar att den föreslagna nedre gränsen för dettadefinierade koncept inte garanterar mer än 50 % förlust av mottagen signalförstärkning(SG) / <p>QC 20240219</p>

Ces dernières années, le développement des réseaux de communication indoor et outdoor et l'augmentation du nombre d'applications conduisent à un besoin toujours croissant de transmission de données à haut débit. Parmi les nombreuses technologies concurrentes, les communications par courant porteur en ligne (CPL) ont leur place en raison des infrastructures déjà disponibles. La motivation principale de cette thèse est d'augmenter le débit et la robustesse des systèmes CPL à porteuses multiples afin qu'ils puissent être utilisés efficacement dans les réseaux domestiques et pour la domotique. Le thème de ce travail de recherche est d'explorer différentes approches de modulation et de codage de canal en liaison avec plusieurs schémas d'allocation et d'optimisation des ressources. L'objectif est ici d'améliorer les capacités des CPL et d'être concurrent face aux autres solutions de communication à haut débit et de faire face efficacement aux inconvénients inhérents au réseau d'alimentation. Un certain nombre de stratégies d'allocation des ressources et d'optimisation sont étudiées pour améliorer les performances globales des systèmes CPL. La performance d'un système de communication est généralement mesurée en termes de débit, de marge de bruit et de taux d'erreur binaire (TEB) de la liaison. La maximisation de débit (RM) est étudiée pour les systèmes OFDM (en anglais orthogonal frequency division multiplexing) et LP-OFDM (en anglais linear precoded OFDM) sous la contrainte de densité spectrale de puissance (DSP). Deux contraintes différentes de taux d'erreur ont été appliquées au problème RM. La première contrainte est la contrainte de TEB crête où toutes les sous-porteuses ou séquences de précodage doivent respecter le TEB cible. Avec la deuxième contrainte, contrainte de TEB moyen, différentes sous-porteuses ou séquences de précodage sont affectées par des valeurs différentes de TEB et une contrainte de TEB moyen est imposée sur le symbole complet OFDM ou LP-OFDM. Les algorithmes d'allocation sont également proposés en prenant en compte les gains de codage de canal dans le processus d'allocation des ressources. En outre, un nouveau schéma de minimisation de TEB moyen est introduit qui minimise le TEB moyen de systèmes pour un débit donné et un masque imposé de DSP. Pour l'allocation des ressources dans un système à porteuses multiples, il est généralement supposé que l'état du canal (CSI) est parfaitement connu par l'émetteur. En réalité, les informations de CSI disponibles au point d'émission sont imparfaites. Aussi, nous avons également étudié des schémas d'allocation des ressources dans le cas de systèmes OFDM et LP-OFDM en prenant compte, et de manière efficace, les impacts des estimations bruitées. Plusieurs chaînes de communication sont aussi développées pour les systèmes OFDM et LP-OFDM.

The thesis focuses on the privacy of communication that can be ensured by means of the physical layer, i.e., by appropriately chosen coding and resource allocation schemes. The fundamentals of physical-layer security have been already formulated in the 1970s by Wyner (1975), Csiszár and Körner (1978). But only nowadays we have the technical progress such that these ideas can find their way in current and future communication systems, which has driven the growing interest in this area of research in the last years. We analyze two physical-layer approaches that can ensure the secret transmission of private information in wireless systems in presence of an eavesdropper. One is the direct transmission of the information to the intended receiver, where the transmitter has to simultaneously ensure the reliability and the secrecy of the information. The other is a two-phase approach, where two legitimated users first agree on a common and secret key, which they use afterwards to encrypt the information before it is transmitted. In this case, the secrecy and the reliability of the transmission are managed separately in the two phases. The secrecy of the transmitted messages mainly depends on reliable information or reasonable and justifiable assumptions about the channel to the potential eavesdropper. Perfect state information about the channel to a passive eavesdropper is not a rational assumption. Thus, we introduce a deterministic model for the uncertainty about this channel, which yields a set of possible eavesdropper channels. We consider the optimization of worst-case rates in systems with multi-antenna Gaussian channels for both approaches. We study which transmit strategy can yield a maximum rate if we assume that the eavesdropper can always observe the corresponding worst-case channel that reduces the achievable rate for the secret transmission to a minimum. For both approaches, we show that the resulting max-min problem over the matrices that describe the multi-antenna system can be reduced to an equivalent problem over the eigenvalues of these matrices. We characterize the optimal resource allocation under a sum power constraint over all antennas and derive waterfilling solutions for the corresponding worst-case channel to the eavesdropper for a constraint on the sum of all channel gains. We show that all rates converge to finite limits for high signal-to-noise ratios (SNR), if we do not restrict the number of antennas for the eavesdropper. These limits are characterized by the quotients of the eigenvalues resulting from the Gramian matrices of both channels. For the low-SNR regime, we observe a rate increase that depends only on the differences of these eigenvalues for the direct-transmission approach. For the key generation approach, there exists no dependence from the eavesdropper channel in this regime. The comparison of both approaches shows that the superiority of an approach over the other mainly depends on the SNR and the quality of the eavesdropper channel. The direct-transmission approach is advantageous for low SNR and comparably bad eavesdropper channels, whereas the key generation approach benefits more from high SNR and comparably good eavesdropper channels. All results are discussed in combination with numerous illustrations. / Der Fokus dieser Arbeit liegt auf der Abhörsicherheit der Datenübertragung, die auf der Übertragungsschicht, also durch geeignete Codierung und Ressourcenverteilung, erreicht werden kann. Die Grundlagen der Sicherheit auf der Übertragungsschicht wurden bereits in den 1970er Jahren von Wyner (1975), Csiszár und Körner (1978) formuliert. Jedoch ermöglicht erst der heutige technische Fortschritt, dass diese Ideen in zukünftigen Kommunikationssystemen Einzug finden können. Dies hat in den letzten Jahren zu einem gestiegenen Interesse an diesem Forschungsgebiet geführt. In der Arbeit werden zwei Ansätze zur abhörsicheren Datenübertragung in Funksystemen analysiert. Dies ist zum einen die direkte Übertragung der Information zum gewünschten Empfänger, wobei der Sender gleichzeitig die Zuverlässigkeit und die Abhörsicherheit der Übertragung sicherstellen muss. Zum anderen wird ein zweistufiger Ansatz betrachtet: Die beiden Kommunikationspartner handeln zunächst einen gemeinsamen sicheren Schlüssel aus, der anschließend zur Verschlüsselung der Datenübertragung verwendet wird. Bei diesem Ansatz werden die Abhörsicherheit und die Zuverlässigkeit der Information getrennt voneinander realisiert. Die Sicherheit der Nachrichten hängt maßgeblich davon ab, inwieweit zuverlässige Informationen oder verlässliche Annahmen über den Funkkanal zum Abhörer verfügbar sind. Die Annahme perfekter Kanalkenntnis ist für einen passiven Abhörer jedoch kaum zu rechtfertigen. Daher wird hier ein deterministisches Modell für die Unsicherheit über den Kanal zum Abhörer eingeführt, was zu einer Menge möglicher Abhörkanäle führt. Die Optimierung der sogenannten Worst-Case-Rate in einem Mehrantennensystem mit Gaußschem Rauschen wird für beide Ansätze betrachtet. Es wird analysiert, mit welcher Sendestrategie die maximale Rate erreicht werden kann, wenn gleichzeitig angenommen wird, dass der Abhörer den zugehörigen Worst-Case-Kanal besitzt, welcher die Rate der abhörsicheren Kommunikation jeweils auf ein Minimum reduziert. Für beide Ansätze wird gezeigt, dass aus dem resultierenden Max-Min-Problem über die Matrizen des Mehrantennensystems ein äquivalentes Problem über die Eigenwerte der Matrizen abgeleitet werden kann. Die optimale Ressourcenverteilung für eine Summenleistungsbeschränkung über alle Sendeantennen wird charakterisiert. Für den jeweiligen Worst-Case-Kanal zum Abhörer, dessen Kanalgewinne einer Summenbeschränkung unterliegen, werden Waterfilling-Lösungen hergeleitet. Es wird gezeigt, dass für hohen Signal-Rausch-Abstand (engl. signal-to-noise ratio, SNR) alle Raten gegen endliche Grenzwerte konvergieren, wenn die Antennenzahl des Abhörers nicht beschränkt ist. Die Grenzwerte werden durch die Quotienten der Eigenwerte der Gram-Matrizen beider Kanäle bestimmt. Für den Ratenanstieg der direkten Übertragung ist bei niedrigem SNR nur die Differenz dieser Eigenwerte maßgeblich, wohingegen für den Verschlüsselungsansatz in dem Fall keine Abhängigkeit vom Kanal des Abhörers besteht. Ein Vergleich zeigt, dass das aktuelle SNR und die Qualität des Abhörkanals den einen oder anderen Ansatz begünstigen. Die direkte Übertragung ist bei niedrigem SNR und verhältnismäßig schlechten Abhörkanälen überlegen, wohingegen der Verschlüsselungsansatz von hohem SNR und vergleichsweise guten Abhörkanälen profitiert. Die Ergebnisse der Arbeit werden umfassend diskutiert und illustriert.

The thesis focuses on the privacy of communication that can be ensured by means of the physical layer, i.e., by appropriately chosen coding and resource allocation schemes. The fundamentals of physical-layer security have been already formulated in the 1970s by Wyner (1975), Csiszár and Körner (1978). But only nowadays we have the technical progress such that these ideas can find their way in current and future communication systems, which has driven the growing interest in this area of research in the last years. We analyze two physical-layer approaches that can ensure the secret transmission of private information in wireless systems in presence of an eavesdropper. One is the direct transmission of the information to the intended receiver, where the transmitter has to simultaneously ensure the reliability and the secrecy of the information. The other is a two-phase approach, where two legitimated users first agree on a common and secret key, which they use afterwards to encrypt the information before it is transmitted. In this case, the secrecy and the reliability of the transmission are managed separately in the two phases. The secrecy of the transmitted messages mainly depends on reliable information or reasonable and justifiable assumptions about the channel to the potential eavesdropper. Perfect state information about the channel to a passive eavesdropper is not a rational assumption. Thus, we introduce a deterministic model for the uncertainty about this channel, which yields a set of possible eavesdropper channels. We consider the optimization of worst-case rates in systems with multi-antenna Gaussian channels for both approaches. We study which transmit strategy can yield a maximum rate if we assume that the eavesdropper can always observe the corresponding worst-case channel that reduces the achievable rate for the secret transmission to a minimum. For both approaches, we show that the resulting max-min problem over the matrices that describe the multi-antenna system can be reduced to an equivalent problem over the eigenvalues of these matrices. We characterize the optimal resource allocation under a sum power constraint over all antennas and derive waterfilling solutions for the corresponding worst-case channel to the eavesdropper for a constraint on the sum of all channel gains. We show that all rates converge to finite limits for high signal-to-noise ratios (SNR), if we do not restrict the number of antennas for the eavesdropper. These limits are characterized by the quotients of the eigenvalues resulting from the Gramian matrices of both channels. For the low-SNR regime, we observe a rate increase that depends only on the differences of these eigenvalues for the direct-transmission approach. For the key generation approach, there exists no dependence from the eavesdropper channel in this regime. The comparison of both approaches shows that the superiority of an approach over the other mainly depends on the SNR and the quality of the eavesdropper channel. The direct-transmission approach is advantageous for low SNR and comparably bad eavesdropper channels, whereas the key generation approach benefits more from high SNR and comparably good eavesdropper channels. All results are discussed in combination with numerous illustrations. / Der Fokus dieser Arbeit liegt auf der Abhörsicherheit der Datenübertragung, die auf der Übertragungsschicht, also durch geeignete Codierung und Ressourcenverteilung, erreicht werden kann. Die Grundlagen der Sicherheit auf der Übertragungsschicht wurden bereits in den 1970er Jahren von Wyner (1975), Csiszár und Körner (1978) formuliert. Jedoch ermöglicht erst der heutige technische Fortschritt, dass diese Ideen in zukünftigen Kommunikationssystemen Einzug finden können. Dies hat in den letzten Jahren zu einem gestiegenen Interesse an diesem Forschungsgebiet geführt. In der Arbeit werden zwei Ansätze zur abhörsicheren Datenübertragung in Funksystemen analysiert. Dies ist zum einen die direkte Übertragung der Information zum gewünschten Empfänger, wobei der Sender gleichzeitig die Zuverlässigkeit und die Abhörsicherheit der Übertragung sicherstellen muss. Zum anderen wird ein zweistufiger Ansatz betrachtet: Die beiden Kommunikationspartner handeln zunächst einen gemeinsamen sicheren Schlüssel aus, der anschließend zur Verschlüsselung der Datenübertragung verwendet wird. Bei diesem Ansatz werden die Abhörsicherheit und die Zuverlässigkeit der Information getrennt voneinander realisiert. Die Sicherheit der Nachrichten hängt maßgeblich davon ab, inwieweit zuverlässige Informationen oder verlässliche Annahmen über den Funkkanal zum Abhörer verfügbar sind. Die Annahme perfekter Kanalkenntnis ist für einen passiven Abhörer jedoch kaum zu rechtfertigen. Daher wird hier ein deterministisches Modell für die Unsicherheit über den Kanal zum Abhörer eingeführt, was zu einer Menge möglicher Abhörkanäle führt. Die Optimierung der sogenannten Worst-Case-Rate in einem Mehrantennensystem mit Gaußschem Rauschen wird für beide Ansätze betrachtet. Es wird analysiert, mit welcher Sendestrategie die maximale Rate erreicht werden kann, wenn gleichzeitig angenommen wird, dass der Abhörer den zugehörigen Worst-Case-Kanal besitzt, welcher die Rate der abhörsicheren Kommunikation jeweils auf ein Minimum reduziert. Für beide Ansätze wird gezeigt, dass aus dem resultierenden Max-Min-Problem über die Matrizen des Mehrantennensystems ein äquivalentes Problem über die Eigenwerte der Matrizen abgeleitet werden kann. Die optimale Ressourcenverteilung für eine Summenleistungsbeschränkung über alle Sendeantennen wird charakterisiert. Für den jeweiligen Worst-Case-Kanal zum Abhörer, dessen Kanalgewinne einer Summenbeschränkung unterliegen, werden Waterfilling-Lösungen hergeleitet. Es wird gezeigt, dass für hohen Signal-Rausch-Abstand (engl. signal-to-noise ratio, SNR) alle Raten gegen endliche Grenzwerte konvergieren, wenn die Antennenzahl des Abhörers nicht beschränkt ist. Die Grenzwerte werden durch die Quotienten der Eigenwerte der Gram-Matrizen beider Kanäle bestimmt. Für den Ratenanstieg der direkten Übertragung ist bei niedrigem SNR nur die Differenz dieser Eigenwerte maßgeblich, wohingegen für den Verschlüsselungsansatz in dem Fall keine Abhängigkeit vom Kanal des Abhörers besteht. Ein Vergleich zeigt, dass das aktuelle SNR und die Qualität des Abhörkanals den einen oder anderen Ansatz begünstigen. Die direkte Übertragung ist bei niedrigem SNR und verhältnismäßig schlechten Abhörkanälen überlegen, wohingegen der Verschlüsselungsansatz von hohem SNR und vergleichsweise guten Abhörkanälen profitiert. Die Ergebnisse der Arbeit werden umfassend diskutiert und illustriert.