856 research outputs found
Distributed radio map reconstruction for 5G automotive
Se espera que los mapas de entorno radio sean una herramienta esencial para la optimización y gestión de recursos del 5G en vehículos. En este trabajo, consideramos el problema de la reconstrucción del mapa de entorno radio utilizando una red de sensores inalámbricos formada por nodos sensores en vehículos, nodos de acceso de una infraestructura de ciudad inteligente, etc. Debido a las limitaciones de recursos en las redes de sensores, es crucial seleccionar un pequeño número de mediciones de los sensores para reconstruir el campo. En este contexto, presentamos un novedoso algoritmo distribuido basado en el método de regresión Kriging para la reconstrucción del mapa de entorno radio en términos de potencia media recibida en lugares donde no se dispone de mediciones de los sensores. Los componentes de pérdida de trayectoria y de sombra del canal inalámbrico se estiman por separado. Para la estimación de las pérdidas por sombra, se forman grupos de sensores de forma adaptativa y su tamaño se optimiza en en términos del menor número de sensores posible minimizando la varianza ordinaria de Kriging. Se obtiene la complejidad del algoritmo propuesto y se presentan resultados de simulación para mostrar la eficacia del algoritmo para la reconstrucción del campo.GRISOLIA/2012/028, RACHEL TEC2013-47141-C4-4-RRadio maps are expected to be an essential tool for
the resource optimization and management of 5G automotive. In
this paper, we consider the problem of radio map reconstruction
using a wireless sensor network formed by sensor nodes in
vehicles, access nodes from a smart city infrastructure, etc.
Due to limited resource constraints in sensor networks, it is
crucial to select a small number of sensor measurements for
field reconstruction. In this context, we present a novel distributed
incremental clustering algorithm based on the regression Kriging
method for radio map reconstruction in terms of average received
power at locations where no sensor measurements are available.
The path-loss and shadowing components of the wireless channel
are separately estimated. For shadowing estimation, clusters of
sensors are adaptively formed and their size is optimized in
terms of the least number of sensors by minimizing the ordinary
Kriging variance. The complexity of the proposed algorithm is
analyzed and simulation results are presented to showcase the
algorithm efficacy to field reconstruction
Cooperative Passive Coherent Location: A Promising 5G Service to Support Road Safety
5G promises many new vertical service areas beyond simple communication and
data transfer. We propose CPCL (cooperative passive coherent location), a
distributed MIMO radar service, which can be offered by mobile radio network
operators as a service for public user groups. CPCL comes as an inherent part
of the radio network and takes advantage of the most important key features
proposed for 5G. It extends the well-known idea of passive radar (also known as
passive coherent location, PCL) by introducing cooperative principles. These
range from cooperative, synchronous radio signaling, and MAC up to radar data
fusion on sensor and scenario levels. By using software-defined radio and
network paradigms, as well as real-time mobile edge computing facilities
intended for 5G, CPCL promises to become a ubiquitous radar service which may
be adaptive, reconfigurable, and perhaps cognitive. As CPCL makes double use of
radio resources (both in terms of frequency bands and hardware), it can be
considered a green technology. Although we introduce the CPCL idea from the
viewpoint of vehicle-to-vehicle/infrastructure (V2X) communication, it can
definitely also be applied to many other applications in industry, transport,
logistics, and for safety and security applications
Application of Radio environment map reconstruction techniques to platoon-based cellular V2X communications
Vehicle platoons involve groups of vehicles travelling together at a constant inter-vehicle distance, with different common benefits such as increasing road efficiency and fuel saving. Vehicle platooning requires highly reliable wireless communications to keep the group structure and carry out coordinated maneuvers in a safe manner. Focusing on infrastructure-assisted cellular vehicle to anything (V2X) communications, the amount of control information to be exchanged between each platoon vehicle and the base station is a critical factor affecting the communication latency. This paper exploits the particular structure and characteristics of platooning to decrease the control information exchange necessary for the channel acquisition stage. More precisely, a scheme based on radio environment map (REM) reconstruction is proposed, where geo-localized received power values are available at only a subset of platoon vehicles, while large-scale channel parameters estimates for the rest of platoon members are provided through the application of spatial Ordinary Kriging (OK) interpolation. Distinctive features of the vehicle platooning use case are explored, such as the optimal patterns of vehicles within the platoon with available REM values for improving the quality of the reconstruction, the need for an accurate semivariogram modeling in OK, or the communication cost when establishing a centralized or a distributed architecture for achieving REM reconstruction. The evaluation results show that OK is able to reconstruct the REM in the platoon with acceptable mean squared estimation error, while reducing the control information for REM acquisition in up to 64% in the best-case scenario
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
Spectrum cartography techniques, challenges, opportunities, and applications: A survey
The spectrum cartography finds applications in several areas such as cognitive radios, spectrum aware communications, machine-type communications, Internet of Things, connected vehicles, wireless sensor networks, and radio frequency management systems, etc. This paper presents a survey on state-of-the-art of spectrum cartography techniques for the construction of various radio environment maps (REMs). Following a brief overview on spectrum cartography, various techniques considered to construct the REMs such as channel gain map, power spectral density map, power map, spectrum map, power propagation map, radio frequency map, and interference map are reviewed. In this paper, we compare the performance of the different spectrum cartography methods in terms of mean absolute error, mean square error, normalized mean square error, and root mean square error. The information presented in this paper aims to serve as a practical reference guide for various spectrum cartography methods for constructing different REMs. Finally, some of the open issues and challenges for future research and development are discussed.publishedVersio
Efficient Machine-type Communication using Multi-metric Context-awareness for Cars used as Mobile Sensors in Upcoming 5G Networks
Upcoming 5G-based communication networks will be confronted with huge
increases in the amount of transmitted sensor data related to massive
deployments of static and mobile Internet of Things (IoT) systems. Cars acting
as mobile sensors will become important data sources for cloud-based
applications like predictive maintenance and dynamic traffic forecast. Due to
the limitation of available communication resources, it is expected that the
grows in Machine-Type Communication (MTC) will cause severe interference with
Human-to-human (H2H) communication. Consequently, more efficient transmission
methods are highly required. In this paper, we present a probabilistic scheme
for efficient transmission of vehicular sensor data which leverages favorable
channel conditions and avoids transmissions when they are expected to be highly
resource-consuming. Multiple variants of the proposed scheme are evaluated in
comprehensive realworld experiments. Through machine learning based combination
of multiple context metrics, the proposed scheme is able to achieve up to 164%
higher average data rate values for sensor applications with soft deadline
requirements compared to regular periodic transmission.Comment: Best Student Paper Awar
Emerging Prototyping Activities in Joint Radar-Communications
The previous chapters have discussed the canvas of joint radar-communications
(JRC), highlighting the key approaches of radar-centric, communications-centric
and dual-function radar-communications systems. Several signal processing and
related aspects enabling these approaches including waveform design, resource
allocation, privacy and security, and intelligent surfaces have been elaborated
in detail. These topics offer comprehensive theoretical guarantees and
algorithms. However, they are largely based on theoretical models. A hardware
validation of these techniques would lend credence to the results while
enabling their embrace by industry. To this end, this chapter presents some of
the prototyping initiatives that address some salient aspects of JRC. We
describe some existing prototypes to highlight the challenges in design and
performance of JRC. We conclude by presenting some avenues that require
prototyping support in the future.Comment: Book chapter, 54 pages, 13 figures, 10 table
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