276 research outputs found
Precoded Cluster Hopping in Multi-Beam High Throughput Satellite Systems
Beam-Hopping (BH) and precoding are two trending technologies for the
satellite community. While BH enables flexibility to adapt the offered capacity
to the heterogeneous demand, precoding aims at boosting the spectral
efficiency. In this paper, we consider a high throughput satellite (HTS) system
that employs BH in conjunction with precoding. In particular, we propose the
concept of Cluster-Hopping (CH) that seamlessly combines the BH and precoding
paradigms and utilize their individual competencies. The cluster is defined as
a set of adjacent beams that are simultaneously illuminated. In addition, we
propose an efficient time-space illumination pattern design, where we determine
the set of clusters that can be illuminated simultaneously at each hopping
event along with the illumination duration. We model the CH time-space
illumination pattern design as an integer programming problem which can be
efficiently solved. Supporting results based on numerical simulations are
provided which validate the effectiveness of the proposed CH concept and
time-space illumination pattern design
Transmit Beamforming Design with Received-Interference Power Constraints: The Zero-Forcing Relaxation
The use of multi-antenna transmitters is emerging as an essential technology of the future wireless communication systems. While Zero-Forcing Beamforming (ZFB) has become the most popular low-complexity transmit beamforming design, it has some drawbacks basically related to the effort of "trying" to invert the channel coefficients towards the interfered users. In particular, ZFB performs poorly in the low Signal-to-Noise Ratio (SNR) regime and does not work when the interfered users outnumber the transmit antennas. In this paper, we study in detail an alternative transmit beamforming design framework, where we allow some residual received-interference power instead of trying to null it completely out. Subsequently, we provide a close-form non-iterative optimal solution that avoids the use of sophisticated convex optimization techniques that compromise its applicability onto practical systems. Supporting results based on numerical simulations show that the proposed transmit beamforming is able to perform close to the optimal with much lower computational complexity.Grant numbers : TERESA - Hybrid TERrEstrial/Satellite Air Interface for 5G and Beyond project (code : TEC2017-90093-C3-1-R).@ 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Carrier Aggregation in Multi-Beam High Throughput Satellite Systems
Carrier Aggregation (CA) is an integral part of current terrestrial networks.
Its ability to enhance the peak data rate, to efficiently utilize the limited
available spectrum resources and to satisfy the demand for data-hungry
applications has drawn large attention from different wireless network
communities. Given the benefits of CA in the terrestrial wireless environment,
it is of great interest to analyze and evaluate the potential impact of CA in
the satellite domain. In this paper, we study CA in multibeam high throughput
satellite systems. We consider both inter-transponder and intra-transponder CA
at the satellite payload level of the communication stack, and we address the
problem of carrier-user assignment assuming that multiple users can be
multiplexed in each carrier. The transmission parameters of different carriers
are generated considering the transmission characteristics of carriers in
different transponders. In particular, we propose a flexible carrier allocation
approach for a CA-enabled multibeam satellite system targeting a proportionally
fair user demand satisfaction. Simulation results and analysis shed some light
on this rather unexplored scenario and demonstrate the feasibility of the CA in
satellite communication systems
Estimación conjunta de TOA y DOA en sistemas UWB para localización
El objetivo de este proyecto es el diseño de un algoritmo de localización
para sistemas con tecnologÃa Ultra-Wideband (UWB)
Sparse channel estimation based on compressed sensing theory for UWB systems
Català : L'estimació de canal en receptors wireless esdevé un factor determinant a l'hora de incrementar les prestacions dels sistemes sense fils per tal de satisfer les exigències cada vegades més elevades dels consumidors en quant a velocitats de transmissió i qualitat. En aquesta tesi es proposa explotar la "sparsity" que mostren els canals wireless per tal de millorar els clà ssics sistemes d'estimació de canal mitjançant les noves teòries de Compressed Sensing. Aixà doncs, es proposa un nou model freqüencial de senyal on el canal i un nou algoritme de reconstrucció de senyals sparse que redueix la probabilitat de detecció de falsos camins de propagació millorant d'aquesta manera l'estimació de temps d'arribada.Castellano: En los últimos años, la revolución inalámbrica se ha convertido en una realidad. Wi-fi está en todas partes, impactando significativamente en nuestro estilo de vida. Sin embargo, las comunicaciones inalámbricas nunca tendrán las condiciones de propagación igual que los cables debido a las duras condiciones de la propagación inalámbricas. El canal de radio móvil se caracteriza por la recepción múltiple, eso es que la señal recibida no sólo contiene una camino de propagación, sino también un gran número de ondas reflejadas. Estas ondas reflejadas interfieren con la onda directa, lo que provoca una degradación significativa del rendimiento del enlace. Un sistema inalámbrico debe estar diseñado de tal manera que el efecto adverso del desvanecimiento multicamino sea reducido al mÃnimo. Afortunadamente, el multipath puede ser visto como diversidad de información dependiendo de la cantidad de Channel State Information (CSI) disponible para el sistema. Sin embargo, en la práctica CSI rara vez se dispone a priori y debe ser estimado. Por otro lado, un canal inalámbrico a menudo puede ser modelado como un canal sparse, en la que el retraso de propagación puede ser muy grande, pero el número de caminos de propagación es normalmente muy pequeño. El conocimiento previo de la sparsity del canal se puede utilizar eficazmente para mejorar la estimación de canal utilizando la nueva teorÃa de Compressed Sensing (CS). CS se origina en la idea de que no es necesario invertir una gran cantidad de energÃa en la observación de las entradas de una señal sparse porque la mayorÃa de ellas será cero. Por lo tanto, CS proporciona un marco sólido para la reducción del número de medidas necesarias para resumir señales sparse. La estimación de canal sparse se centra en este trabajo en Ultra-Wideband (UWB) porque la gran resolución temporal que proporcionan las señales UWB se traduce en un número muy grande de componentes multipath que se pueden resolver. Por lo tanto, UWB mitiga significativamente la distorsión de trayectoria múltiple y proporciona la diversidad multicamino. Esta diversidad junto con la resolución temporal de las señales UWB crear un problema de estimación de canal muy interesante. En esta tesis se estudia el uso de CS en la estimación de canal altamente sparse por medio de un nuevo enfoque de estimación basado en el modelo de frecuencial de la señal UWB. También se propone un nuevo algoritmo llamado extended Orthogonal Matching Pursuit (eOMP) basado en los mismos principios que el clásico OMP, con el fin de mejorar algunas de sus caracterÃstica.English: In recent years, the wireless revolution has become a reality. Wireless is everywhere having significant impact on our lifestyle. However, wireless will never have the same propagation conditions as wires due to the harsh conditions of the wireless propagation. The mobile radio channel is characterized by multipath reception, that is the signal offered to the receiver contains not only a direct line-of-sight radio wave, but also a large number of reflected radio waves. These reflected waves interfere with the direct wave, which causes significant degradation of the performance of the link. A wireless system has to be designed in such way that the adverse effect of multipath fading is minimized. Fortunately, multipath can be seen as a blessing depending on the amount of Channel State Information (CSI) available to the system. However, in practise CSI is seldom available a priori and needs to be estimated. On the other hand, a wireless channel can often be modeled as a sparse channel in which the delay spread could be very large, but the number of significant paths is normally very small. The prior knowledge of the channel sparseness can be effectively use to improve the channel estimation using the novel Compressed Sensing (CS) theory. CS originates from the idea that is not necessary to invest a lot of power into observing the entries of a sparse signal because most of them will be zero. Therefore, CS provides a robust framework for reducing the number of measurement required to summarize sparse signals. The sparse channel estimation here is focused on Ultra-WideBand (UWB) systems because the very fine time resolution of the UWB signal results in a very large number of resolvable multipath components. Consequently, UWB significantly mitigates multipath distortion and provides path diversity. The rich multipath coupled with the fine time resolution of the UWB signals create a challenging sparse channel estimation problem. This Master Thesis examines the use of CS in the estimation of highly sparse channel by means of a new sparse channel estimation approach based on the frequency domain model of the UWB signal. It is also proposed a new greedy algorithm named extended Orthogonal Matching Pursuit (eOMP) based on the same principles than classical Orthogonal Matching Pursuit (OMP) in order to improve some OMP characteristics. Simulation results show that the new eOMP provides lower false path detection probability compared with classical OMP, which also leads to a better TOA estimation without significant degradation of the channel estimation. Simulation results will also show that the new frequency domain sparse channel model outperforms other models presented in the literature
Integrated terrestrial-satellite wireless backhauling: resource management and benefits for 5G
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Peer ReviewedPostprint (author's final draft
Precoded Cluster Hopping in Multi-Beam High Throughput Satellite Systems
Beam-Hopping (BH) and precoding are two trending
technologies for the satellite community. While BH enables
flexibility to adapt the offered capacity to the heterogeneous
demand, precoding aims at boosting the spectral efficiency.
In this paper, we consider a high throughput satellite (HTS)
system that employs BH in conjunction with precoding. In
particular, we propose the concept of Cluster-Hopping (CH)
that seamlessly combines the BH and precoding paradigms and
utilizes their individual competencies. The cluster is defined as
a set of adjacent beams that are simultaneously illuminated. In
addition, we propose an efficient time-space illumination pattern
design, where we determine the set of clusters that can be
illuminated simultaneously at each hopping event along with the
illumination duration. We model the CH time-space illumination
pattern design as an integer programming problem which can
be efficiently solved. Supporting results based on numerical
simulations are provided which validate the effectiveness of the
proposed CH concept and time-space illumination pattern design
Successive Convex Approximation for Transmit Power Minimization in SWIPT-Multicast Systems
We propose a novel technique for total transmit power minimization and optimal precoder design in wireless multi-group (MG) multicasting (MC) systems. The considered framework consists of three different systems capable of handling heterogeneous user types viz., information decoding (ID) specific users with conventional receiver architectures, energy harvesting (EH) only users with non-linear EH module, and users with joint ID and EH capabilities having separate units for the two operations, respectively. Each user is categorized under unique group(s), which can be of MC type specifically meant for ID users, and/or an energy group consisting of EH explicit users. The joint ID and EH users are a part of the (last) EH group as well as any one of the MC groups distinctly. In this regard, we formulate an optimization problem to minimize the total transmit power with optimal precoder designs for the three aforementioned scenarios, under constraints on minimum signal-to-interference-plus-noise ratio and harvested energy by the users with respective demands. The problem may be adapted to the well-known semi-definite program, which can be typically solved via relaxation of rank-1 constraint. However, the relaxation of this constraint may in some cases lead to performance degradation, which increases with the rank of the solution obtained from the relaxed problem. Hence, we develop a novel technique motivated by the feasible-point pursuit and successive convex approximation method in order to address the rank-related issue. The benefits of the proposed method are illustrated under various operating conditions and parameter values, with comparison between the three above-mentioned scenarios
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