User Selection and Precoding Techniques for Rate Maximization in Broadcast MISO Systems

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Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks

In cognitive radio (CR) networks, there are scenarios where the secondary (lower priority) users intend to communicate with each other by opportunistically utilizing the transmit spectrum originally allocated to the existing primary (higher priority) users. For such a scenario, a secondary user usually has to trade off between two conflicting goals at the same time: one is to maximize its own transmit throughput; and the other is to minimize the amount of interference it produces at each primary receiver. In this paper, we study this fundamental tradeoff from an information-theoretic perspective by characterizing the secondary user's channel capacity under both its own transmit-power constraint as well as a set of interference-power constraints each imposed at one of the primary receivers. In particular, this paper exploits multi-antennas at the secondary transmitter to effectively balance between spatial multiplexing for the secondary transmission and interference avoidance at the primary receivers. Convex optimization techniques are used to design algorithms for the optimal secondary transmit spatial spectrum that achieves the capacity of the secondary transmission. Suboptimal solutions for ease of implementation are also presented and their performances are compared with the optimal solution. Furthermore, algorithms developed for the single-channel transmission are also extended to the case of multi-channel transmission whereby the secondary user is able to achieve opportunistic spectrum sharing via transmit adaptations not only in space, but in time and frequency domains as well.Comment: Extension of IEEE PIMRC 2007. 35 pages, 6 figures. Submitted to IEEE Journal of Special Topics in Signal Processing, special issue on Signal Processing and Networking for Dynamic Spectrum Acces

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe

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

Mean Achievable Rates in Clustered Coordinated Base Station Transmission with Block Diagonalization

We focus on the mean achievable rate per user of the coordinated base station downlink transmission in a clustered cellular environment, with transmit power constraints at the base stations. Block Diagonalization is employed within the cluster to remove interference among users while the interference from other clusters remains. The average achievable rate per user is evaluated considering the effects of the propagation channel and the interference and a theoretical framework is presented to provide its analytical expression, validated by simulation results with different power allocation schemes. As an application, the number of cells of the cluster that maximizes the mean achievable rate per user is investigated. It can be seen that in most of the cases a reduced cluster size, close to seven cells, guarantees a rate very close to the maximum achievableThis work is partly funded by projects "GRE3N": TEC2011-29006-C03-03 and "COMONSENS": CSD2008-00010En-prens

Partial coordination in clustered base station MIMO transmission

This proceeding at: IEEE Wireless Communications and Networking Conference (WCNC, 2013), took place 2013, April, 7-10, in Shaghai (China)We present partial coordination strategies in a clustered cellular environment, evaluating the achievable rate in the downlink transmission. Block Diagonalization is employed for the coordinated users within the cluster to remove interference, while the interference from non-coordinated users remains. The achievable rate is evaluated resorting to an analytical expression conditioned on the position of the users in the cluster. A partial coordination approach is proposed to reduce the coordination complexity and overhead, where users close to the base station are not coordinated. Two approaches are considered, namely the non-coordinated users can be grouped and assigned separated resources from the coordinated ones, or they can be mixed.This work was supported by projects CSD2008-00010 “COMONSENS” and TEC2011-29006-C03-03 “GRE3N”

Cooperative Precoding with Limited Feedback for MIMO Interference Channels

Multi-antenna precoding effectively mitigates the interference in wireless networks. However, the resultant performance gains can be significantly compromised in practice if the precoder design fails to account for the inaccuracy in the channel state information (CSI) feedback. This paper addresses this issue by considering finite-rate CSI feedback from receivers to their interfering transmitters in the two-user multiple-input-multiple-output (MIMO) interference channel, called cooperative feedback, and proposing a systematic method for designing transceivers comprising linear precoders and equalizers. Specifically, each precoder/equalizer is decomposed into inner and outer components for nulling the cross-link interference and achieving array gain, respectively. The inner precoders/equalizers are further optimized to suppress the residual interference resulting from finite-rate cooperative feedback. Further- more, the residual interference is regulated by additional scalar cooperative feedback signals that are designed to control transmission power using different criteria including fixed interference margin and maximum sum throughput. Finally, the required number of cooperative precoder feedback bits is derived for limiting the throughput loss due to precoder quantization.Comment: 23 pages; 5 figures; this work was presented in part at Asilomar 2011 and will appear in IEEE Trans. on Wireless Com