Técnicas de pré-codificação para sistemas multicelulares coordenados

Doutoramento em TelecomunicaçõesCoordenação Multicélula é um tópico de investigação em rápido crescimento e uma solução promissora para controlar a interferência entre células em sistemas celulares, melhorando a equidade do sistema e aumentando a sua capacidade. Esta tecnologia já está em estudo no LTEAdvanced sob o conceito de coordenação multiponto (COMP). Existem várias abordagens sobre coordenação multicélula, dependendo da quantidade e do tipo de informação partilhada pelas estações base, através da rede de suporte (backhaul network), e do local onde essa informação é processada, i.e., numa unidade de processamento central ou de uma forma distribuída em cada estação base. Nesta tese, são propostas técnicas de pré-codificação e alocação de potência considerando várias estratégias: centralizada, todo o processamento é feito na unidade de processamento central; semidistribuída, neste caso apenas parte do processamento é executado na unidade de processamento central, nomeadamente a potência alocada a cada utilizador servido por cada estação base; e distribuída em que o processamento é feito localmente em cada estação base. Os esquemas propostos são projectados em duas fases: primeiro são propostas soluções de pré-codificação para mitigar ou eliminar a interferência entre células, de seguida o sistema é melhorado através do desenvolvimento de vários esquemas de alocação de potência. São propostas três esquemas de alocação de potência centralizada condicionada a cada estação base e com diferentes relações entre desempenho e complexidade. São também derivados esquemas de alocação distribuídos, assumindo que um sistema multicelular pode ser visto como a sobreposição de vários sistemas com uma única célula. Com base neste conceito foi definido uma taxa de erro média virtual para cada um desses sistemas de célula única que compõem o sistema multicelular, permitindo assim projectar esquemas de alocação de potência completamente distribuídos. Todos os esquemas propostos foram avaliados em cenários realistas, bastante próximos dos considerados no LTE. Os resultados mostram que os esquemas propostos são eficientes a remover a interferência entre células e que o desempenho das técnicas de alocação de potência propostas é claramente superior ao caso de não alocação de potência. O desempenho dos sistemas completamente distribuídos é inferior aos baseados num processamento centralizado, mas em contrapartida podem ser usados em sistemas em que a rede de suporte não permita a troca de grandes quantidades de informação.Multicell coordination is a promising solution for cellular wireless systems to mitigate inter-cell interference, improving system fairness and increasing capacity and thus is already under study in LTE-A under the coordinated multipoint (CoMP) concept. There are several coordinated transmission approaches depending on the amount of information shared by the transmitters through the backhaul network and where the processing takes place i.e. in a central processing unit or in a distributed way on each base station. In this thesis, we propose joint precoding and power allocation techniques considering different strategies: Full-centralized, where all the processing takes place at the central unit; Semi-distributed, in this case only some process related with power allocation is done at the central unit; and Fulldistributed, where all the processing is done locally at each base station. The methods are designed in two phases: first the inter-cell interference is removed by applying a set of centralized or distributed precoding vectors; then the system is further optimized by centralized or distributed power allocation schemes. Three centralized power allocation algorithms with per-BS power constraint and different complexity tradeoffs are proposed. Also distributed power allocation schemes are proposed by considering the multicell system as superposition of single cell systems, where we define the average virtual bit error rate (BER) of interference-free single cell system, allowing us to compute the power allocation coefficients in a distributed manner at each BS. All proposed schemes are evaluated in realistic scenarios considering LTE specifications. The numerical evaluations show that the proposed schemes are efficient in removing inter-cell interference and improve system performance comparing to equal power allocation. Furthermore, fulldistributed schemes can be used when the amounts of information to be exchanged over the backhaul is restricted, although system performance is slightly degraded from semi-distributed and full-centralized schemes, but the complexity is considerably lower. Besides that for high degrees of freedom distributed schemes show similar behaviour to centralized ones

Wireless interference networks with limited feedback

Wir betrachten das Problem der Akquirierung von Kanalzustandsinformationen an den Sendern von drahtlosen Netzwerken und entwickeln Feedbackverfahren und Sendestrategien für verschiedene Netzwerk Architekturen. Die entwickelten Verfahren werden analysiert und die Skalierung der Performance des Gesamtsystems anhand bestimmter Systemparameter bestimmt. Zuerst betrachten wir eine einzelne Zelle eines zellularen Systems und nehmen an, dass die Beamformingvektoren durch ein festes Codebuch vorgegeben sind. Wir entwickeln und analysieren ein neues Feedbackverfahren, dass Flexibilität und Robustheit vereint und dadurch effiziente und zuverlässige Kommunikation mit den Empfängern ermöglicht. Eine Analyse des Verfahrens zeigt, dass die Skalierung des Ratenverlustes durch quantisierte Kanalzustandsinformation besser ist als bei vergleichbaren Verfahren. Für das Feedbackverfahren wird ein spezieller Algorithmus entwickelt der es ermöglicht Codebücher für verschiedene Kanalmodelle zu generieren und zu optimieren. Die analytischen Ergebnisse werden durch Simulationen validiert und bestätigen einen Gewinn gegenüber vergleichbaren Verfahren. Anschließend betrachten wir zellulare Systeme mit mehreren Zellen. Wir charakterisieren die Freiheitsgrade (degrees of freedom) unter verschiedenen Annahmen über das Kanalmodell. Des weiteren entwickeln wir verschiedene Algorithmen, die die optimalen Freiheitsgrade erreichen können. Anschließend wird ein Feedbackverfahren entwickelt, dass den Feedbackaufwand für die entwickelten Algorithmen signifikant reduziert. Wir analysieren eine breite Klasse von zellularen Systemen die beliebige koordinierte Sendestrategien verwenden. Für diese Klasse von Systemen leiten wir die Skalierung des Ratenverlustes relativ zum Feedbackaufwand her. Abschließend zeigen wir, wie die analytischen Ergebnisse auf das entwickelte Feedbackverfahren angewendet werden können. Im letzten Kapitel entwickeln wir ein Framework, dass das Potenzial von Compressed Sensing nutzt um den Messaufwand und Feedbackaufwand in zellularen Systemen mit vielen Teilnehmern signifikant zu reduzieren. Das Framework ermöglicht es die Datenraten der Nutzer innerhalb gegebener Fehlerschranken zu schätzen. Grundlage ist neben Compressed Sensing ein neues Messverfahren, dass die Überlagerung von Signalen im Kanal nutzt, um zufällige nicht adaptive Messungen der Kanalkoeffizienten am Empfänger zu ermöglichen. Diese Messungen werden zu einer zentralen Steuereinheit übertragen und dort dekodiert. Wir analysieren die Genauigkeit der Rekonstruktion für einen linearen und einen nicht-linearen Dekodierer und leiten die Skalierung mit der Anzahl der Messungen her. Abschließend zeigen wir, wie der entwickelte Ansatz in zellularen Systemen angewendet werden kann.We consider the problem of acquiring accurate channel state information at the transmitters of a wireless network. We develop different feedback and transmit strategies for different network architectures and analyze their performance. First, we consider a single cell of cellular system and assume that the beamforming vectors are given by a fixed transmit codebook. We develop and analyze a new feedback and transmit strategy which combines flexibility and robustness needed for efficient and reliable communication. We prove that it has better scaling properties compared to classical results on the limited feedback problem in the broadcast channel and that this benefit improves with an increasing number of transmit antennas. We show how feedback codebooks can be designed for different propagation environments. Link level and system level simulations sustain the analytic results showing performance gains of up to 50 % or 70 % compared to zeroforcing when using multiple antennas at the base station and multiple antennas or a single antenna at the terminals, respectively. We characterize the degrees of freedom (i.e. the multiplexing gain) of multi-cellular systems under different assumptions on the channel model and for different system setups. We propose different algorithms that possibly achieve the optimal degrees of freedom. The first algorithm aims on aligning the interference at each receiver in a subspace of the available receive space. Our second algorithm aims on directly maximizing the signal-to-interference-plus-noise ratio (SINR) of all receivers. By allowing symbol extensions over time or frequency and including a user selection we are able to achieve the alignment of interference for many system setups and exploit multi-user diversity. For coordinated transmit strategies we find the scaling of the performance loss with the feedback load. A distributed interference alignment algorithm is introduced. The algorithm makes efficient use of quantized channel state information and significantly reduces the feedback overhead. We develop a framework that we call compressive rate estimation. To this end, we assume that the composite channel gain matrix (i.e. the matrix of all channel gains between all network nodes) is compressible which means it can be approximated by a sparse or low rank representation. We develop a sensing protocol that exploits the superposition principle of the wireless channel and enables the receiving nodes to obtain non-adaptive random measurements of columns of the composite channel matrix. The random measurements are fed back to a central controller who decodes the composite channel gain matrix (or parts of it) and estimates individual user rates. We analyze the rate loss for a linear and a non-linear decoder and find the scaling laws according to the number of non-adaptive measurements

Cost-Effective Signal Processing Algorithms for Physical-Layer Security in Wireless Networks

Data privacy in traditional wireless communications is accomplished by cryptography techniques at the upper layers of the protocol stack. This thesis aims at contributing to the critical security issue residing in the physical-layer of wireless networks, namely, secrecy rate in various transmission environments. Physical-layer security opens the gate to the exploitation of channel characteristics to achieve data secure transmission. Precoding techniques, as a critical aspect in pre-processing signals prior to transmission has become an effective approach and recently drawn significant attention in the literature. In our research, novel non-linear precoders are designed focusing on the improvement of the physical-layer secrecy rate with consideration of computational complexity as well as the Bit Error Ratio (BER) performance. In the process of designing the precoder, strategies such as Lattice Reduction (LR) and Artificial Noise (AN) are employed to achieve certain design requirements. The deployment and allocation of resources such as relays to assist the transmission also have gained significant interest. In multiple-antenna relay networks, we examine various relay selection criteria with arbitrary knowledge of the channels to the users and the eavesdroppers. Furthermore, we provide novel effective relay selection criteria that can achieve a high secrecy rate performance. More importantly they do not require knowledge of the channels of the eavesdroppers and the interference. Combining the jamming technique with resource allocation of relay networks, we investigate an opportunistic relaying and jamming scheme for Multiple-Input Multiple-Output (MIMO) buffer-aided downlink relay networks. More specifically, a novel Relaying and Jamming Function Selection (RJFS) algorithm as well as a buffer-aided RJFS algorithm are developed along with their ability to achieve a higher secrecy rate. Relying on the proposed relay network, we detail the characteristics of the system, under various relay selection criteria, develop exhaustive search and greedy search-based algorithms, with or without inter-relay Interference Cancellation (IC)

Advanced Trends in Wireless Communications

Physical limitations on wireless communication channels impose huge challenges to reliable communication. Bandwidth limitations, propagation loss, noise and interference make the wireless channel a narrow pipe that does not readily accommodate rapid flow of data. Thus, researches aim to design systems that are suitable to operate in such channels, in order to have high performance quality of service. Also, the mobility of the communication systems requires further investigations to reduce the complexity and the power consumption of the receiver. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers rather than researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics

Adaptive Coded Modulation Classification and Spectrum Sensing for Cognitive Radio Systems. Adaptive Coded Modulation Techniques for Cognitive Radio Using Kalman Filter and Interacting Multiple Model Methods

The current and future trends of modern wireless communication systems place heavy demands on fast data transmissions in order to satisfy end users’ requirements anytime, anywhere. Such demands are obvious in recent applications such as smart phones, long term evolution (LTE), 4 & 5 Generations (4G & 5G), and worldwide interoperability for microwave access (WiMAX) platforms, where robust coding and modulations are essential especially in streaming on-line video material, social media and gaming. This eventually resulted in extreme exhaustion imposed on the frequency spectrum as a rare natural resource due to stagnation in current spectrum management policies. Since its advent in the late 1990s, cognitive radio (CR) has been conceived as an enabling technology aiming at the efficient utilisation of frequency spectrum that can lead to potential direct spectrum access (DSA) management. This is mainly attributed to its internal capabilities inherited from the concept of software defined radio (SDR) to sniff its surroundings, learn and adapt its operational parameters accordingly. CR systems (CRs) may commonly comprise one or all of the following core engines that characterise their architectures; namely, adaptive coded modulation (ACM), automatic modulation classification (AMC) and spectrum sensing (SS). Motivated by the above challenges, this programme of research is primarily aimed at the design and development of new paradigms to help improve the adaptability of CRs and thereby achieve the desirable signal processing tasks at the physical layer of the above core engines. Approximate modelling of Rayleigh and finite state Markov channels (FSMC) with a new concept borrowed from econometric studies have been approached. Then insightful channel estimation by using Kalman filter (KF) augmented with interacting multiple model (IMM) has been examined for the purpose of robust adaptability, which is applied for the first time in wireless communication systems. Such new IMM-KF combination has been facilitated in the feedback channel between wireless transmitter and receiver to adjust the transmitted power, by using a water-filling (WF) technique, and constellation pattern and rate in the ACM algorithm. The AMC has also benefited from such IMM-KF integration to boost the performance against conventional parametric estimation methods such as maximum likelihood estimate (MLE) for channel interrogation and the estimated parameters of both inserted into the ML classification algorithm. Expectation-maximisation (EM) has been applied to examine unknown transmitted modulation sequences and channel parameters in tandem. Finally, the non-parametric multitaper method (MTM) has been thoroughly examined for spectrum estimation (SE) and SS, by relying on Neyman-Pearson (NP) detection principle for hypothesis test, to allow licensed primary users (PUs) to coexist with opportunistic unlicensed secondary users (SUs) in the same frequency bands of interest without harmful effects. The performance of the above newly suggested paradigms have been simulated and assessed under various transmission settings and revealed substantial improvements