19 research outputs found
Channel Estimation for mmWave Massive MIMO Based Access and Backhaul in Ultra-Dense Network
Millimeter-wave (mmWave) massive MIMO used for access and backhaul in
ultra-dense network (UDN) has been considered as the promising 5G technique. We
consider such an heterogeneous network (HetNet) that ultra-dense small base
stations (BSs) exploit mmWave massive MIMO for access and backhaul, while
macrocell BS provides the control service with low frequency band. However, the
channel estimation for mmWave massive MIMO can be challenging, since the pilot
overhead to acquire the channels associated with a large number of antennas in
mmWave massive MIMO can be prohibitively high. This paper proposes a structured
compressive sensing (SCS)-based channel estimation scheme, where the angular
sparsity of mmWave channels is exploited to reduce the required pilot overhead.
Specifically, since the path loss for non-line-of-sight paths is much larger
than that for line-of-sight paths, the mmWave massive channels in the angular
domain appear the obvious sparsity. By exploiting such sparsity, the required
pilot overhead only depends on the small number of dominated multipath.
Moreover, the sparsity within the system bandwidth is almost unchanged, which
can be exploited for the further improved performance. Simulation results
demonstrate that the proposed scheme outperforms its counterpart, and it can
approach the performance bound.Comment: 6 pages, 5 figures. Millimeter-wave (mmWave), mmWave massive MIMO,
compressive sensing (CS), hybrid precoding, channel estimation, access,
backhaul, ultra-dense network (UDN), heterogeneous network (HetNet). arXiv
admin note: substantial text overlap with arXiv:1604.03695, IEEE
International Conference on Communications (ICC'16), May 2016, Kuala Lumpur,
Malaysi
Reliability performance analysis of half-duplex and full-duplex schemes with self-energy recycling
Abstract. Radio frequency energy harvesting (EH) has emerged as a promising option for improving the energy efficiency of current and future networks. Self-energy recycling (sER), as a variant of EH, has also appeared as a suitable alternative that allows to reuse part of the transmitted energy via an energy loop. In this work we study the benefits of using sER in terms of reliability improvements and compare the performance of full-duplex (FD) and half-duplex (HD) schemes when using multi-antenna techniques at the base station side. We also assume a model for the hardware energy consumption, making the analysis more realistic since most works only consider the energy spent on transmission. In addition to spectral efficiency enhancements, results show that FD performs better than HD in terms of reliability. We maximize the outage probability of the worst link in the network using a dynamic FD scheme where a small base station (SBS) determines the optimal number of antennas for transmission and reception. This scheme proves to be more efficient than classical HD and FD modes. Results show that the use of sER at the SBS introduces changes on the distribution of antennas for maximum fairness when compared to the setup without sER. Moreover, we determine the minimum number of active radio frequency chains required at the SBS in order to achieve a given reliability target
Physical Layer Security in Wireless Networks: Design and Enhancement.
PhDSecurity and privacy have become increasingly significant concerns in wireless communication
networks, due to the open nature of the wireless medium which makes the wireless
transmission vulnerable to eavesdropping and inimical attacking. The emergence and
development of decentralized and ad-hoc wireless networks pose great challenges to the
implementation of higher-layer key distribution and management in practice. Against
this background, physical layer security has emerged as an attractive approach for performing
secure transmission in a low complexity manner. This thesis concentrates on
physical layer security design and enhancement in wireless networks.
First, this thesis presents a new unifying framework to analyze the average secrecy
capacity and secrecy outage probability. Besides the exact average secrecy capacity
and secrecy outage probability, a new approach for analyzing the asymptotic behavior is
proposed to compute key performance parameters such as high signal-to-noise ratio slope,
power offset, secrecy diversity order, and secrecy array gain. Typical fading environments
such as two-wave with diffuse power and Nakagami-m are taken into account.
Second, an analytical framework of using antenna selection schemes to achieve secrecy
is provided. In particular, transmit antenna selection and generalized selection combining
are considered including its special cases of selection combining and maximal-ratio
combining.
Third, the fundamental questions surrounding the joint impact of power constraints on
the cognitive wiretap channel are addressed. Important design insights are revealed
regarding the interplay between two power constraints, namely the maximum transmit
at the secondary network and the peak interference power at the primary network.
Fourth, secure single carrier transmission is considered in the two-hop decode-andi
forward relay networks. A two-stage relay and destination selection is proposed to minimize
the eavesdropping and maximize the signal power of the link between the relay and
the destination. In two-hop amplify-and-forward untrusted relay networks, secrecy may
not be guaranteed even in the absence of external eavesdroppers. As such, cooperative
jamming with optimal power allocation is proposed to achieve non-zero secrecy rate.
Fifth and last, physical layer security in large-scale wireless sensor networks is introduced.
A stochastic geometry approach is adopted to model the positions of sensors, access
points, sinks, and eavesdroppers. Two scenarios are considered: i) the active sensors
transmit their sensing data to the access points, and ii) the active access points forward
the data to the sinks. Important insights are concluded
Reconfigurable Intelligent Surface Aided Mobile Edge Computing: From Optimization-Based to Location-Only Learning-Based Solutions
In this paper, we explore optimization-based and data-driven solutions in a
reconfigurable intelligent surface (RIS)-aided multi-user mobile edge computing
(MEC) system, where the user equipment (UEs) can partially offload their
computation tasks to the access point (AP). We aim at maximizing the total
completed task-input bits (TCTB) of all UEs with limited energy budgets during
a given time slot, through jointly optimizing the RIS reflecting coefficients,
the AP's receive beamforming vectors, and the UEs' energy partition strategies
for local computing and offloading. A three-step block coordinate descending
(BCD) algorithm is first proposed to effectively solve the non-convex TCTB
maximization problem with guaranteed convergence. In order to reduce the
computational complexity and facilitate lightweight online implementation of
the optimization algorithm, we further construct two deep learning
architectures. The first one takes channel state information (CSI) as input,
while the second one exploits the UEs' locations only for online inference. The
two data-driven approaches are trained using data samples generated by the BCD
algorithm via supervised learning. Our simulation results reveal a close match
between the performance of the optimization-based BCD algorithm and the
low-complexity learning-based architectures, all with superior performance to
existing schemes in both cases with perfect and imperfect input features.
Importantly, the location-only deep learning method is shown to offer a
particularly practical and robust solution alleviating the need for CSI
estimation and feedback when line-of-sight (LoS) direct links exist between UEs
and the AP.Comment: 15 pages, 12 figure
Intelligent Massive MIMO Systems for Beyond 5G Networks: An Overview and Future Trends
Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the potential of challenging large-scale problems in conventional massive multiple-input-multiple-output (CM-MIMO) systems. This introduces the concept of intelligent massive MIMO (I-mMIMO) systems. Due to the surge of application of different ML techniques in the enhancement of mMIMO systems for existing and emerging use cases beyond fifth-generation (B5G) networks, this article aims to provide an overview of the different aspects of the I-mMIMO systems. First, the characteristics and challenges of the CM-MIMO have been identified. Secondly, the most recent efforts aimed at applying ML to a different aspect of CM-MIMO systems are presented. Thirdly, the deployment of I-mMIMO and efforts towards standardization are discussed. Lastly, the future trends of I-mMIMO-enabled application systems are presented. The aim of this paper is to assist the readers to understand different ML approaches in CM-MIMO systems, explore some of the advantages and disadvantages, identify some of the open issues, and motivate the readers toward future trends
Transmit and Receive Signal Processing for MIMO Terrestrial Broadcast Systems
[EN] Multiple-Input Multiple-Output (MIMO) technology in Digital Terrestrial Television (DTT) networks has the potential to increase the spectral efficiency and improve network coverage to cope with the competition of limited spectrum use (e.g., assignment of digital dividend and spectrum demands of mobile broadband), the appearance of new high data rate services (e.g., ultra-high definition TV - UHDTV), and the ubiquity of the content (e.g., fixed, portable, and mobile). It is widely recognised that MIMO can provide multiple benefits such as additional receive power due to array gain, higher resilience against signal outages due to spatial diversity, and higher data rates due to the spatial multiplexing gain of the MIMO channel. These benefits can be achieved without additional transmit power nor additional bandwidth, but normally come at the expense of a higher system complexity at the transmitter and receiver ends. The final system performance gains due to the use of MIMO directly depend on physical characteristics of the propagation environment such as spatial correlation, antenna orientation, and/or power imbalances experienced at the transmit aerials. Additionally, due to complexity constraints and finite-precision arithmetic at the receivers, it is crucial for the overall system performance to carefully design specific signal processing algorithms.
This dissertation focuses on transmit and received signal processing for DTT systems using MIMO-BICM (Bit-Interleaved Coded Modulation) without feedback channel to the transmitter from the receiver terminals. At the transmitter side, this thesis presents investigations on MIMO precoding in DTT systems to overcome system degradations due to different channel conditions. At the receiver side, the focus is given on design and evaluation of practical MIMO-BICM receivers based on quantized information and its impact in both the in-chip memory size and system performance. These investigations are carried within the standardization process of DVB-NGH (Digital Video Broadcasting - Next Generation Handheld) the handheld evolution of DVB-T2 (Terrestrial - Second Generation), and ATSC 3.0 (Advanced Television Systems Committee - Third Generation), which incorporate MIMO-BICM as key technology to overcome the Shannon limit of single antenna communications. Nonetheless, this dissertation employs a generic approach in the design, analysis and evaluations, hence, the results and ideas can be applied to other wireless broadcast communication systems using MIMO-BICM.[ES] La tecnologÃa de múltiples entradas y múltiples salidas (MIMO) en redes de Televisión Digital Terrestre (TDT) tiene el potencial de incrementar la eficiencia espectral y mejorar la cobertura de red para afrontar las demandas de uso del escaso espectro electromagnético (e.g., designación del dividendo digital y la demanda de espectro por parte de las redes de comunicaciones móviles), la aparición de nuevos contenidos de alta tasa de datos (e.g., ultra-high definition TV - UHDTV) y la ubicuidad del contenido (e.g., fijo, portable y móvil). Es ampliamente reconocido que MIMO puede proporcionar múltiples beneficios como: potencia recibida adicional gracias a las ganancias de array, mayor robustez contra desvanecimientos de la señal gracias a la diversidad espacial y mayores tasas de transmisión gracias a la ganancia por multiplexado del canal MIMO. Estos beneficios se pueden conseguir sin incrementar la potencia transmitida ni el ancho de banda, pero normalmente se obtienen a expensas de una mayor complejidad del sistema tanto en el transmisor como en el receptor. Las ganancias de rendimiento finales debido al uso de MIMO dependen directamente de las caracterÃsticas fÃsicas del entorno de propagación como: la correlación entre los canales espaciales, la orientación de las antenas y/o los desbalances de potencia sufridos en las antenas transmisoras. Adicionalmente, debido a restricciones en la complejidad y aritmética de precisión finita en los receptores, es fundamental para el rendimiento global del sistema un diseño cuidadoso de algoritmos especÃficos de procesado de señal.
Esta tesis doctoral se centra en el procesado de señal, tanto en el transmisor como en el receptor, para sistemas TDT que implementan MIMO-BICM (Bit-Interleaved Coded Modulation) sin canal de retorno hacia el transmisor desde los receptores. En el transmisor esta tesis presenta investigaciones en precoding MIMO en sistemas TDT para superar las degradaciones del sistema debidas a diferentes condiciones del canal. En el receptor se presta especial atención al diseño y evaluación de receptores prácticos MIMO-BICM basados en información cuantificada y a su impacto tanto en la memoria del chip como en el rendimiento del sistema. Estas investigaciones se llevan a cabo en el contexto de estandarización de DVB-NGH (Digital Video Broadcasting - Next Generation Handheld), la evolución portátil de DVB-T2 (Second Generation Terrestrial), y ATSC 3.0 (Advanced Television Systems Commitee - Third Generation) que incorporan MIMO-BICM como clave tecnológica para superar el lÃmite de Shannon para comunicaciones con una única antena. No obstante, esta tesis doctoral emplea un método genérico tanto para el diseño, análisis y evaluación, por lo que los resultados e ideas pueden ser aplicados a otros sistemas de comunicación inalámbricos que empleen MIMO-BICM.[CA] La tecnologia de múltiples entrades i múltiples eixides (MIMO) en xarxes de Televisió Digital Terrestre (TDT) té el potencial d'incrementar l'eficiència espectral i millorar la cobertura de xarxa per a afrontar les demandes d'ús de l'escà s espectre electromagnètic (e.g., designació del dividend digital i la demanda d'espectre per part de les xarxes de comunicacions mòbils), l'aparició de nous continguts d'alta taxa de dades (e.g., ultra-high deffinition TV - UHDTV) i la ubiqüitat del contingut (e.g., fix, portà til i mòbil). És à mpliament reconegut que MIMO pot proporcionar múltiples beneficis com: potència rebuda addicional grà cies als guanys de array, major robustesa contra esvaïments del senyal grà cies a la diversitat espacial i majors taxes de transmissió grà cies al guany per multiplexat del canal MIMO. Aquests beneficis es poden aconseguir sense incrementar la potència transmesa ni l'ample de banda, però normalment s'obtenen a costa d'una major complexitat del sistema tant en el transmissor com en el receptor. Els guanys de rendiment finals a causa de l'ús de MIMO depenen directament de les caracterÃstiques fÃsiques de l'entorn de propagació com: la correlació entre els canals espacials, l'orientació de les antenes, i/o els desequilibris de potència patits en les antenes transmissores. Addicionalment, a causa de restriccions en la complexitat i aritmètica de precisió finita en els receptors, és fonamental per al rendiment global del sistema un disseny acurat d'algorismes especÃfics de processament de senyal.
Aquesta tesi doctoral se centra en el processament de senyal tant en el transmissor com en el receptor per a sistemes TDT que implementen MIMO-BICM (Bit-Interleaved Coded Modulation) sense canal de tornada cap al transmissor des dels receptors. En el transmissor aquesta tesi presenta recerques en precoding MIMO en sistemes TDT per a superar les degradacions del sistema degudes a diferents condicions del canal. En el receptor es presta especial atenció al disseny i avaluació de receptors prà ctics MIMO-BICM basats en informació quantificada i al seu impacte tant en la memòria del xip com en el rendiment del sistema. Aquestes recerques es duen a terme en el context d'estandardització de DVB-NGH (Digital Video Broadcasting - Next Generation Handheld), l'evolució portà til de DVB-T2 (Second Generation Terrestrial), i ATSC 3.0 (Advanced Television Systems Commitee - Third Generation) que incorporen MIMO-BICM com a clau tecnològica per a superar el lÃmit de Shannon per a comunicacions amb una única antena. No obstant açò, aquesta tesi doctoral empra un mètode genèric tant per al disseny, anà lisi i avaluació, per la qual cosa els resultats i idees poden ser aplicats a altres sistemes de comunicació sense fils que empren MIMO-BICM.Vargas Paredero, DE. (2016). Transmit and Receive Signal Processing for MIMO Terrestrial Broadcast Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/66081TESISPremiad