Interference dominated wireless communications systems are considered. Joint detection methods are applied to combat the negative effects of the temporal and spatial interference. However, practical joint detectors are not commonly used due to their high complexity. Therefore, there is a constant need to deliver reduced complexity solutions that approach substantial fraction of the channel capacity. In the first part of this thesis it is shown that simple transmission technique employing repetition coding and interleaving combined with interference cancellation is an asymptotically optimal processing strategy when high interference is experienced, for instance due to the relatively high ratio of the number of signals to the number of orthogonal dimensions. Surprisingly, strong, capacity achieving codes exhibit inferior performance and are not well suited for iterative interference cancellation due to their sharp threshold characteristics. Motivated by this observation partitioned modulation is introduced and applied to a multiuser spread spectrum system, which inherently encompasses a repetition coding mechanism. The detection of the resulting signals employs a parallel interference cancellation approach, where the repetition code exchanges information iteratively with the canceller. Precise signal-to-noise ratio evolution of the proposed receiver as a function of demodulation iterations is given. It is shown, that for equal received power system, partitioned demodulator outperforms linear minimum mean squared error processor at a fraction of complexity. This receiver processing for a wide range of parameters delivers estimates that coincide with the optimal processing based on exhaustive search. For unequal received signal powers these advantages are even more visible and for a particular exponential power allocation the proposed system reaches the capacity of the channel. The analytical investigations are verified using computer simulations. In the second part of this dissertation, multi-user MIMO systems compliant with 3GPP LTE standard are considered. Turbo near-far resistant interference cancellation receiver is proposed. It jointly removes multi-user, multi-antenna and inter-symbol interference and outperforms traditional demodulation/decoding method adopted in the LTE standard. Semi-analytical method of predicting the performance of this joint receiver for any system setup is outlined. This approach makes it possible to tune up the performance of the system without running extensive bit-error-rate simulations. / Communications

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CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Devido ao rÃpido crescimento e os agressivos requisitos de vazÃo nas atuais redes sem fio, como os sistemas celulares de 4 a GeraÃÃo, a interferÃncia se tornou um problema que nÃo pode mais ser negligenciado. Neste contexto, o Alinhamento de InterferÃncia (IA) tem surgido como uma tÃcnica promissora que possibilita transmissÃes livres de interferÃncia com elevada eficiÃncia espectral. No entanto, trabalhos recentes tÃm focado principalmente nos ganhos teÃricos que esta tÃcnica pode prover, enquanto esta dissertaÃÃo visa dar um passo na direÃÃo de esclarecer alguns dos problemas prÃticos de implementaÃÃo da tÃcnica em redes celulares, bem como comparÃ-la com outras tÃcnicas bem estabelecidas. Uma rede composta por trÃs cÃlulas foi escolhida como cenÃrio inicial de avaliaÃÃo, para o qual diversos fatores realistas foram considerados de modo a realizar diferentes anÃlises. A primeira anÃlise foi baseada em imperfeiÃÃes de canal, cujos resultados mostraram que o IA à mais robusto aos erros de estimaÃÃo de canal que o BD (do inglÃs, Block Diagonalization), enquanto as duas abordagens sÃo igualmente afetadas pela correlaÃÃo entre as antenas. O impacto de uma interferÃncia externa nÃo-coordenada, que foi modelada por diferentes matrizes de covariÃncia de modo a emular vÃrios cenÃrios, tambÃm foi avaliado. Os resultados mostraram que as modificaÃÃes feitas nos algoritmos de IA podem melhorar bastante seus desempenho, com uma vantagem para o algoritmo que suprime um Ãnico fluxo de dados, quando sÃo comparadas as taxas de erro de bit alcanÃadas por cada um. Para combinar os fatores das anÃlises anteriores, as variaÃÃes temporais de canal foram consideradas. Neste conjunto de simulaÃÃes, alÃm da presenÃa da interferÃncia externa, os prÃ-codificadores sÃo calculados atravÃs de medidas atrasadas de canal, levando a resultados que corroboraram com as anÃlises anteriores. Um fato recorrente percebido em todas as anÃlises anteriores à o dilema entre aplicar os algoritmos baseados em BD, para que se consiga alcanÃar maiores capacidades, ou enviar a informaÃÃo atravÃs de um enlace mais confiÃvel utilizando o IA. Uma maneira de esclarecer este dilema à efetivamente realizar simulaÃÃes a nÃvel sistÃmico, para isto foi aplicado um simulador sistÃmico composto por um grande nÃmero de setores. Como resultado, todas as anÃlises realizadas neste simulador mostraram que a tÃcnica de IA atinge desempenhos intermediÃrios entre a nÃo cooperaÃÃo e os algoritmos baseados na prÃ-codificaÃÃo conjunta. Uma das principais contribuiÃÃes deste trabalho foi mostrar alguns cenÃrios em que a tÃcnica do IA pode ser aplicada. Por exemplo, quando as estimaÃÃes dos canais nÃo sÃo tÃo confiÃveis à melhor aplicar o IA do que os esquemas baseados no processamento conjunto. TambÃm mostrou-se que as modificaÃÃes nos algoritmos de IA, que levam em consideraÃÃo a interferÃncia externa, podem melhorar consideravelmente o desempenho dos algoritmos. Finalmente, o IA se mostrou uma tÃcnica adequada para ser aplicada em cenÃrios em que a interferÃncia à alta e nÃo à possÃvel ter um alto grau de cooperaÃÃo entre os setores vizinhos. / Due to the rapid growth and the aggressive throughput requirements of current wireless networks, such as the 4th Generation (4G) cellular systems, the interference has become an issue that cannot be neglected anymore. In this context, the Interference Alignment (IA) arises as a promising technique that enables transmissions free of interference with high-spectral efficiency. However, while recent works have focused mainly on the theoretical gains that the technique could provide, this dissertation aims to go a step further and clarify some of the practical issues on the implementation of this technique in a cellular network, as well as compare it to other well-established techniques. As an initial evaluation scenario, a 3-cell network was considered, for which several realistic factors were taken into account in order to perform different analyses. The first analysis was based on channel imperfections, for which the results showed that IA is more robust than Block Diagonalization (BD) regarding the Channel State Information (CSI) errors, but both are similarly affected by the correlation among transmit antennas. The impact of uncoordinated interference was also evaluated, by modeling this interference with different covariance matrices in order to mimic several scenarios. The results showed that modifications on the IA algorithms can boost their performance, with an advantage to the approach that suppresses one stream, when the Bit Error Rate (BER) is compared. To combine both factors, the temporal channel variations were taken into account. At these set of simulations, besides the presence of an external interference, the precoders were calculated using a delayed CSI, leading to results that corroborate with the previous analyses. A recurring fact on the herein considered analyses was the dilemma of weather to apply the Joint Processing (JP)-based algorithms in order to achieve higher sum capacities or to send the information through a more reliable link by using IA. A reasonable step towards solving this dilemma is to actually perform the packet transmissions, which was accomplished by employing a system-level simulator composed by a large number of Transmission Points (TPs). As a result, all analyses conducted with this simulator showed that the IA technique can provide an intermediate performance between the non-cooperation and the full cooperation scheme. Concluding, one of the main contributions of this work has been to show some scenarios/cases where the IA technique can be applied. For instance, when the CSI is not reliable it can be better to use IA than a JP-based scheme. Also, the modifications on the algorithms to take into account the external interference can boost their performance. Finally, the IA technique finds itself in-between the conventional transmissions and Coordinated Multi-Point (CoMP). IA achieves an intermediate performance, while requiring a certain degree of cooperation among the neighboring sectors, but demanding less infrastructure than the JP-based schemes.

<p>Multi-input multi-output (MIMO) systems are expected to playa crucial role in future wireless communications and a significant increase of interest in all aspects of MIMO system design has been seen in the past decade. The primary interest of this thesis is in the receiver part of the MIMO system. In this area, continuous interest has been shown in developing blind-adaptive decoding algorithms. While blind decoding algorithms improve data throughput by enabling the system de:signer to replace training symbols with data, they also tend to perform robustly against any environment disturbances, compared to their training-based counterparts. On the other hand, considering the fact that the wireless end user environment is becoming increasingly mobile, adaptive algorithms have the ability to improve the performance of a system regardless of whether it is a blind system or a training-based one. The primary difficulty faced by blind and adaptive algorithms is that they generally are computationally intense. In this thesis, we develop semi-blind and blind decoding algorithms that are adaptive in nature as well as computationally efficient for multi-antenna systems.</p> <p>First, we consider the problem of channel tracking for MIMO communication systems where the MIMO channel is time-varying. We consider a class of MIMO systems where orthogonal space-time block codes (OSTBCs) are used as the underlying space-time coding schemes. For a general MIMO system with any number of transmitting and receiving antenna combinations, a two-step MIMO channel tracking algorithm is proposed. As the first step, Kalman filtering is used to obtain an initial channel estimate for the current block based on the channel estimates obtained for previous blocks. Then, in the second step, the so-obtained initial channel estimate is refined using a decision-directed iterative method. We show that, due to specific properties of orthogonal space-time block codes, both the Kalman filter and the decision-directed algorithm can be significantly simplified. Then, we extend the above receiver for MIMO-OFDM systems and propose a computationally efficient semi-blind receiver for MIMO systems in frequency-selective channels. Further, for the proposed receivers, we have derived theoretical performance analysis in terms of probability of error. Assuming the knowledge of the transmitted symbols for the first block, we have derived the instantaneous signal to interference and noise ratio (SINR) for consecutive transmission blocks in the absence of training, by exploiting Kalman filtering to track the channel in a decision-directed mode. Later, we extend the the theoretical performance limit comparisons for time-domain vs. frequency-domain channel tracking for MIMO-OFDM systems. Further, we study the advantage of adaptive channel tracking algorithms in comptype pilot aided channel estimation schemes in practical MIMO-OFDM systems.</p> <p>After that, an efficient sequential Monte-Carlo (SMC) algorithm is developed for blind detection in MIMO systems where OSTBCs are used as the underlying space-time coding scheme. The proposed algorithm employs Rao-Blackwellization strategy to marginalize out the (unwanted) channel coefficients and uses optimal importance function to generate samples to propagate the posterior distribution. The algorithm is blind in the sense that, unlike the earlier ones, the transmission of training symbols is not required by this scheme. The marginalization involves the computation of (hundreds of) Kalman filters running in parallel resulting in intense computer requirement. We show that, the marginalization step can be significantly simplified for the speci1ied problem under no additional assumptions - resulting in huge computational savings. Further, we extend this result to frequency selective channels and propose a novel and efficient SMC receiver for MIMO-OFDM systems.</p> <p>Finally, a novel adaptive algorithm is presented for directional MIMO systems. Specifically, the problem of direction of arrivall (DOA) tracking of an unknown time-varying number of mobile sources is considered. The challenging part of the problem is the unknown, time-varying number of sources that demand a combination of source enumeration techniques and sequential state estimation methods to track the time-varying number of DOAs. In this thesis, we transform the problem into a novel state-space model, and, by employing probability hypothesis density (PHD) filtering technique, propose a simple algorithm that is able to track the number of sources as well as the corresponding directions of arrivals. In addition to the fact that the proposed algorithm is simple and easier to implement, simulation results show that, the PHD implementation yields superior performance over competing schemes in tracking rapidly varying number of targets.</p> / Doctor of Philosophy (PhD)

This dissertation addresses some of the most important issues in delay-sensitive communication over wireless systems and networks. Traditionally, the design of communication networks adopts a layered framework where each layer serves as a “black box” abstraction for higher layers. However, in the context of wireless networks with delay-sensitive applications such as Voice over Internet Protocol (VoIP), on-line gaming, and video conferencing, this layered architecture does not offer a complete picture. For example, an information theoretic perspective on the physical layer typically ignores the bursty nature of practical sources and often overlooks the role of delay in service quality. The purpose of this dissertation is to take on a cross-disciplinary approach to derive new fundamental limits on the performance, in terms of capacity and delay, of wireless systems and to apply these limits to the design of practical wireless systems that support delay-sensitive applications. To realize this goal, we consider a number of objectives. 1. Develop an integrated methodology for the analysis of wireless systems that support delay-sensitive applications based, in part, on large deviation theory. 2. Use this methodology to identify fundamental performance limits and to design systems which allocate resources efficiently under stringent service requirements. 3. Analyze the performance of wireless communication networks that takes advantage of novel paradigms such as user cooperation, and multi-antenna systems. Based on the proposed framework, we find that delay constraints significantly influence how system resources should be allocated. Channel correlation has a major impact on the performance of wireless communication systems. Sophisticated power control based on the joint space of channel and buffer states are essential for delaysensitive communications.

Abstract The use of multiple antennas is a fundamental requirement in future wireless networks as it helps to increase the reliability and spectral efficiency of mobile radio links. In this thesis, we study convex optimization based radio resource allocation methods for the downlink of multi-antenna systems. First, the problem of admission control in the downlink of a multicell multiple-input single-output (MISO) system has been considered. The objective is to maximize the number of admitted users subject to a signal-to-interference-plus-noise ratio (SINR) constraint at each admitted user and a transmit power constraint at each base station (BS). We have cast the admission control problem as an ℓ0 minimization problem; it is known to be combinatorial, NP-hard. Centralized and distributed algorithms to solve this problem have been proposed. To develop the centralized algorithm, we have used sequential convex programming (SCP). The distributed algorithm has been derived by using the consensus-based alternating direction method of multipliers in conjunction with SCP. We have shown numerically that the proposed admission control algorithms achieve a near-to-optimal performance. Next, we have extended the admission control problem to provide fairness, where long-term fairness among the users has been guaranteed. We have focused on proportional and max-min fairness, and proposed dynamic control algorithms via Lyapunov optimization. Results show that these proposed algorithms guarantee fairness. Then, the problem of admission control for the downlink of a MISO heterogeneous networks (hetnet) has been considered, and the proposed centralized and distributed algorithms have been adapted to find a solution. Numerically, we have illustrated that the centralized algorithm achieves a near-to-optimal performance, and the distributed algorithm’s performance is closer to the optimal value. Finally, an algorithm to obtain the set of all achievable power-rate tuples for a multiple-input multiple-output hetnet has been provided. The setup consists of a single macrocell and a set of femtocells. The interference power to the macro users from the femto BSs has been kept below a threshold. To find the set of all achievable power-rate tuples, a two-dimensional vector optimization problem is formulated, where we have considered maximizing the sum-rate while minimizing the sum-power, subject to maximum power and interference threshold constraints. This problem is known to be NP-hard. A solution method is provided by using the relationship between the weighted sum-rate maximization and weighted-sum-mean-squared-error minimization problems. The proposed algorithm was used to evaluate the impact of imposing interference threshold constraints and the co-channel deployments in a hetnet. / Tiivistelmä Monen antennin käyttö on perusvaatimus tulevissa langattomissa verkoissa, koska se auttaa lisäämään matkaviestinyhteyksien luotettavuutta ja spektritehokkuutta. Tässä väitöskirjassa tutkitaan konveksiin optimointiin perustuvia radioresurssien allokointimenetelmiä moniantennijärjestelmien alalinkin suunnassa. Ensiksi on käsitelty pääsynvalvonnan ongelmaa alalinkin suuntaan monen solun moni-tulo yksi-lähtö (MISO) -verkoissa. Tavoitteena on maksimoida hyväksyttyjen käyttäjien määrä, kun hyväksytyille käyttäjille on asetettu signaali-häiriö-kohinasuhteen (SINR) rajoitus, ja tukiasemille lähetystehon rajoitus. Pääsynvalvonnan ongelma on muotoiltu ℓ0-minimointiongelmana, jonka tiedetään olevan kombinatorinen, NP-vaikea ongelma. Ongelman ratkaisemiseksi on ehdotettu keskitettyjä ja hajautettuja algoritmeja. Keskitetty optimointialgoritmi perustuu sekventiaaliseen konveksiin optimointiin. Hajautettu algoritmi pohjautuu konsensusoptimointimenetelmään ja sekventiaaliseen konveksiin optimointiin. Ehdotettujen pääsynvalvonta-algoritmien on numeerisesti osoitettu saavuttavan lähes optimaalinen suorituskyky. Lisäksi pääsynvalvontaongelma on laajennettu takaamaan pitkän aikavälin oikeudenmukaisuus käyttäjien välillä. Työssä käytetään erilaisia määritelmiä oikeudenmukaisuuden takaamiseen, ja ehdotetaan dynaamisia algoritmeja pohjautuen Lyapunov-optimointiin. Tulokset osoittavat, että ehdotetuilla algoritmeilla taataan käyttäjien välinen oikeudenmukaisuus. Tämän jälkeen käsitellään heterogeenisen langattoman MISO-verkon pääsynvalvonnan ongelmaa. Edellä ehdotettuja keskitettyjä ja hajautettuja algoritmeja on muokattu tämän ongelman ratkaisemiseksi. Työssä osoitetaan numeerisesti, että sekä keskitetyllä että hajautetulla algoritmilla saavutetaan lähes optimaalinen suorituskyky. Lopuksi on laadittu algoritmi, jolla löydetään kaikki saavutettavissa olevat teho-datanopeusparit heterogeenisessä langattomassa moni-tulo moni-lähtö (MIMO) -verkossa. Verkko koostuu yhdestä makrosolusta ja useasta piensolusta. Piensolutukiasemista makrokäyttäjiin kohdistuvan häiriön teho on pidetty tietyn rajan alapuolella. Kaikkien saavutettavien teho-datanopeusparien löytämiseksi on laadittu kaksiulotteinen vektorioptimointiongelma, jossa maksimoidaan summadatanopeus pyrkien minimoimaan kokonaisteho, kun enimmäisteholle ja häiriökynnykselle on asetettu rajoitukset. Tämän ongelman tiedetään olevan NP-vaikea. Ongelman ratkaisemiseksi käytetään painotetun summadatanopeuden maksimointiongelman, ja painotetun keskineliövirheen minimointiongelman välistä suhdetta. Ehdotettua algoritmia käytettiin arvioimaan häiriörajoitusten ja saman kanavan käyttöönoton vaikutusta heterogeenisessä langattomassa verkossa.

La demande de transmissions à débits de plus en plus élevés s’accentue davantage avec l’essor de nouveaux services dans les réseaux de communication sans fils. Pour répondre à cette demande, une solution consiste à augmenter la capacité de transmission du canal radiofréquence entre la station de base et le terminal portatif. Ceci peut être réalisé en augmentant le nombre d’éléments rayonnant impliqués à l’émission et à la réception de cette liaison radiofréquence : on parle alors de technique MIMO (Multiple Input, Multiple Output). Cette thèse porte principalement sur la conception, l’optimisation et la caractérisation de systèmes multi-antennaires pour techniques de diversité et MIMO en bandes LTE (Long Term Evolution). Trois prototypes multi-bandes sont proposés dont deux systèmes planaires et un système d’antennes IFAs compactes. De nouvelles solutions multi-bandes et l’influence de la position de l’antenne sur le plan de masse sont étudiées pour réaliser de la diversité spatiale, de polarisation et de diagramme de rayonnement avec une faible corrélation entre les signaux reçus sur chaque antenne mais surtout une bonne efficacité totale. Une ligne de neutralisation est utilisée pour isoler les antennes et un fonctionnement multi-bande est réalisé. L’impédance d’entrée des antennes est étudiée avec la méthode de Youla & Carlin afin d’améliorer la bande passante de la structure compacte de type IFA. Les performances en diversité et en MIMO de ces systèmes sont évaluées dans différents environnements de propagation. Elles montrent que ces systèmes peuvent être utilisés efficacement pour des applications en diversité et MIMO. / The transmission demand for increasing data rate becomes more and more important with the development of new services in radio communication networks. To answer to this demand, one solution consists in increasing the transmission capacity of the radio channel between the base station and the handset terminal. This can be realized by increasing the number of radiating elements involved in the transmission and the reception of this radio link: we talk about MIMO (Multiple Input Multiple Output) technique. The work realized in this thesis concerns mainly design, optimization and characterization of multi-antenna systems for MIMO and diversity techniques in LTE (Long Term Evolution) bands. Three multi bands prototypes are proposed whose two planar systems and one compact IFAs antennas system. News multiband solution and antenna position influence on the PCB were studied to realize spatial, polarization and pattern diversity with low correlation between received signals on each antenna and a good efficiency. The neutralization line was used for antennas isolation and its application in multiband was realized. The antenna load impedance has been studied with Youla & Carlin method in order to improve the frequency bandwidth of the compact IFA structure. Diversity and MIMO performances of these systems were evaluated in different propagation environments. They show that these systems can be effectively used for diversity and MIMO application.

In heterogeneous dense networks where spectrum is shared, users privacy remains one of the major challenges. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk becomes information leakage.We propose a novel and efficient secrecy rate enhancing relay strategy EFFIN for information leakage neutralization. The relay matrix is chosen such that the effective leakage channel (spectral and spatial) is zero. Thus, it ensures secrecy regardless of receive processing employed at eavesdroppers and does not rely on wiretaps codes to ensure secrecy, unlike other physical layer security techniques such as artificial noise. EFFIN achieves a higher sum secrecy rate over several state-of-the-art baseline methods.

In heterogeneous dense networks where spectrum is shared, users' privacy remains one of the major challenges. On a multi-antenna relay-assisted multi-carrier interference channel, each user shares the spectral and spatial resources with all other users. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk on the spectral and spatial channels becomes information leakage. In this paper, we propose a novel secrecy rate enhancing relay strategy that utilizes both spectral and spatial resources, termed as information leakage neutralization. To this end, the relay matrix is chosen such that the effective channel from the transmitter to the colluding eavesdropper is equal to the negative of the effective channel over the relay to the colluding eavesdropper and thus the information leakage to zero. Interestingly, the optimal relay matrix in general is not block-diagonal which encourages users' encoding over the frequency channels. We proposed two information leakage neutralization strategies, namely efficient information leakage neutralization (EFFIN) and local-optimized information leakage neutralization (LOPTIN). EFFIN provides a simple and efficient design of relay processing matrix and precoding matrices at the transmitters in the scenario of limited power and computational resources. LOPTIN, despite its higher complexity, provides a better sum secrecy rate performance by optimizing the relay processing matrix and the precoding matrices jointly. The proposed methods are shown to improve the sum secrecy rates over several state-of-the-art baseline methods.

In heterogeneous dense networks where spectrum is shared, users privacy remains one of the major challenges. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk becomes information leakage.We propose a novel and efficient secrecy rate enhancing relay strategy EFFIN for information leakage neutralization. The relay matrix is chosen such that the effective leakage channel (spectral and spatial) is zero. Thus, it ensures secrecy regardless of receive processing employed at eavesdroppers and does not rely on wiretaps codes to ensure secrecy, unlike other physical layer security techniques such as artificial noise. EFFIN achieves a higher sum secrecy rate over several state-of-the-art baseline methods.