Spectrum Sharing in Wireless Networks via QoS-Aware Secondary Multicast Beamforming

Secondary spectrum usage has the potential to considerably increase spectrum utilization. In this paper, quality-of-service (QoS)-aware spectrum underlay of a secondary multicast network is considered. A multiantenna secondary access point (AP) is used for multicast (common information) transmission to a number of secondary single-antenna receivers. The idea is that beamforming can be used to steer power towards the secondary receivers while limiting sidelobes that cause interference to primary receivers. Various optimal formulations of beamforming are proposed, motivated by different ldquocohabitationrdquo scenarios, including robust designs that are applicable with inaccurate or limited channel state information at the secondary AP. These formulations are NP-hard computational problems; yet it is shown how convex approximation-based multicast beamforming tools (originally developed without regard to primary interference constraints) can be adapted to work in a spectrum underlay context. Extensive simulation results demonstrate the effectiveness of the proposed approaches and provide insights on the tradeoffs between different design criteria

Feedback of channel state information in multi-antenna systems based on quantization of channel Gram matrices

This dissertation deals with the proper design of efficient feedback strategies for Multiple-Input Multiple-Output (MIMO) communication systems. MIMO systems outperform single antenna systems in terms of achievable throughput and are more resilient to noise and interference, which are becoming the limiting factors in the current and future communications. Apart from the clear performance advantages, MIMO systems introduce an additional complexity factor, since they require knowledge of the propagation channel in order to be able to adapt the transmission to the propagation channel’s characteristics and achieve optimum performance. This channel knowledge, also known as Channel State Information (CSI), is estimated at the receiver and sent to the transmitter through a limited feedback link. In this dissertation, first, the minimum channel information necessary at the transmitter for the optimum precoding design is identified. This minimum information for the optimum design of the system corresponds to the channel Gram matrix. It is essential for the design of optimized systems to avoid the transmission of redundant feedback information. Following this idea, a quantization algorithm that exploits the differential geometry of the set of Gram matrices and the correlation in time present in most propagation channels is developed in order to greatly improve the feedback performance. This scheme is applied first to single-user MIMO communications, then to some particular multiuser scenarios, and finally it is extended to general multiuser broadcast communications. To conclude, the feedback link sizing is studied. An analysis of the tradeoff between size of the forward link and size of the feedback link isformulated and the radio resource allocation problem, in terms of transmission energy, time, and bandwidth of the forward and feedback links is presented.En un mundo cada vez más interconectado, donde hay una clara tendencia hacia un mayor número de comunicaciones inalámbricas simultáneas (comunicaciones M2M: Machine to Machine, redes de sensores, etc.) y en el que las necesidades de capacidad de transmisión de los enlaces de comunicaciones aumentan de manera vertiginosa (audio, video, contenidos multimedia, alta definición, etc.) el problema de la interferencia se convierte en uno de los factores limitadores de los enlaces junto con los desvanecimientos del nivel de señal y las pérdidas de propagación. Por este motivo los sistemas que emplean múltiples antenas tanto en la transmisión como en la recepción (los llamados sistemas MIMO: Multiple-Input Multiple-Output) se presentan como una de las soluciones más interesantes para satisfacer los crecientes requisitos de capacidad y comportamiento relativo a interferencias. Los sistemas MIMO permiten obtener un mejor rendimiento en términos de tasa de transmisión de información y a su vez son más robustos frente a ruido e interferencias en el canal. Esto significa que pueden usarse para aumentar la capacidad de los enlaces de comunicaciones actuales o para reducir drásticamente el consumo energético manteniendo las mismas prestaciones. Por otro lado, además de estas claras ventajas, los sistemas MIMO introducen un punto de complejidad adicional puesto que para aprovechar al máximo las posibilidades de estos sistemas es necesario tener conocimiento de la información de estado del canal (CSI: Channel State Information) tanto en el transmisor como en el receptor. Esta CSI se obtiene mediante estimación de canal en el receptor y posteriormente se envía al transmisor a través de un canal de realimentación. Esta tesis trata sobre el diseño del canal de realimentación para la transmisión de CSI, que es un elemento fundamental de los sistemas de comunicaciones del presente y del futuro. Las técnicas de transmisión que consideran activamente el efecto de la interferencia y el ruido requieren adaptarse al canal y, para ello, la realimentación de CSI es necesaria. En esta tesis se identifica, en primer lugar, la mínima información sobre el estado del canal necesaria para implementar un diseño óptimo en el transmisor, con el fin de evitar transmitir información redundante y obtener así un sistema más eficiente. Esta información es la matriz de Gram del canal MIMO. Seguidamente, se desarrolla un algoritmo de cuantificación adaptado a la geometría diferencial del conjunto que contiene la información a cuantificar y que además aprovecha la correlación temporal existente en los canales de propagación inalámbricos. Este algoritmo se implementa y evalúa primero en comunicaciones MIMO punto a punto entre dos usuarios, después se implementa para algunos casos particulares con múltiples usuarios, y finalmente se amplía para el caso general de sistemas broadcast multi-usuario. Adicionalmente, esta tesis también estudia y optimiza el dimensionamiento del canal de realimentación en función de la cantidad de recursos radio disponibles, en términos de ancho de banda, tiempo y potencia de transmisión. Para ello presenta el problema de la distribución óptima de dichos recursos radio entre el enlace de transmisión de datos y el enlace de realimentación para transmisión de información sobre estado del canal como un problema de optimización

Dispensing with channel estimation: differentially modulated cooperative wireless communications

As a benefit of bypassing the potentially excessive complexity and yet inaccurate channel estimation, differentially encoded modulation in conjunction with low-complexity noncoherent detection constitutes a viable candidate for user-cooperative systems, where estimating all the links by the relays is unrealistic. In order to stimulate further research on differentially modulated cooperative systems, a number of fundamental challenges encountered in their practical implementations are addressed, including the time-variant-channel-induced performance erosion, flexible cooperative protocol designs, resource allocation as well as its high-spectral-efficiency transceiver design. Our investigations demonstrate the quantitative benefits of cooperative wireless networks both from a pure capacity perspective as well as from a practical system design perspective

Robust Location-Aided Beam Alignment in Millimeter Wave Massive MIMO

Location-aided beam alignment has been proposed recently as a potential approach for fast link establishment in millimeter wave (mmWave) massive MIMO (mMIMO) communications. However, due to mobility and other imperfections in the estimation process, the spatial information obtained at the base station (BS) and the user (UE) is likely to be noisy, degrading beam alignment performance. In this paper, we introduce a robust beam alignment framework in order to exhibit resilience with respect to this problem. We first recast beam alignment as a decentralized coordination problem where BS and UE seek coordination on the basis of correlated yet individual position information. We formulate the optimum beam alignment solution as the solution of a Bayesian team decision problem. We then propose a suite of algorithms to approach optimality with reduced complexity. The effectiveness of the robust beam alignment procedure, compared with classical designs, is then verified on simulation settings with varying location information accuracies.Comment: 24 pages, 7 figures. The short version of this paper has been accepted to IEEE Globecom 201

Channel estimation and tracking for closed loop EO-STBC with differentially encoding feedback

Extended orthogonal space time block coding (EO-STBC) can achieve high transmit diversity over a multiple-input multiple-output (MIMO) channel. To do so, it requires channel state information on the transmitter side, which needs to be estimated and fed back from the receiver. Therefore, this paper explores an estimation and tracking scheme by means of a Kalman filter, which is integrated with EO-STBC detection and exploits the smooth evolution of the channel coefficients by applying differential feedback. For slow fading, we propose the inclusion of a drift vector in the Kalman model, which is motivated by a second order approximation of the underlying channel model and can be shown to offer advantages in terms of temporal smoothness when addressing channels whose coefficient trajectories evolve smoothly

Distortion-Tolerant Communications with Correlated Information

This dissertation is devoted to the development of distortion-tolerant communication techniques by exploiting the spatial and/or temporal correlation in a broad range of wireless communication systems under various system configurations. Signals observed in wireless communication systems are often correlated in the spatial and/or temporal domains, and the correlation can be used to facilitate system designs and to improve system performance. First, the optimum node density, i.e., the optimum number of nodes in a unit area, is identified by utilizing the spatial data correlation in the one- and two-dimensional wireless sensor networks (WSNs), under the constraint of fixed power per unit area. The WSNs distortion is quantized as the mean square error between the original and the reconstructed signals. Then we extend the analysis into WSNs with spatial-temporally correlated data. The optimum sampling in the space and time domains is derived. The analytical optimum results can provide insights and guidelines on the design of practical WSNs. Second, distributed source coding schemes are developed by exploiting the data correlation in a wireless network with spatially distributed sources. A new symmetric distributed joint source-channel coding scheme (DJSCC) is proposed by utilizing the spatial source correlation. Then the DJSCC code is applied to spatial-temporally correlated sources. The temporal correlated data is modeled as the Markov chain. Correspondingly, two decoding algorithms are proposed. The first multi-codeword message passing algorithm (MCMP) is designed for spatially correlated memoryless sources. In the second algorithm, a hidden Markov decoding process is added to the MCMP decoder to effectively exploit the data correlation in both the space and time domains. Third, we develop distortion-tolerant high mobility wireless communication systems by considering correlated channel state information (CSI) in the time domain, and study the optimum designs with imperfect CSI. The pilot-assisted channel estimation mean square error is expressed as a closed-form expression of various system parameters through asymptotic analysis. Based on the statistical properties of the channel estimation error, we quantify the impacts of imperfect CSI on system performance by developing the analytical symbol error rate and a spectral efficiency lower bound of the communication system