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The growing demand for high data rates for wireless communication systems leads to the development of new technologies to increase the channel capacity thus increasing the data rate. MIMO (multiple-input multiple-output) systems are best qualified for these applications. In this paper, we present a MIMO test environment for high data rate transmiss...
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... seems likely that these higher frequency bands will become important for commercial use in future WLAN systems. In Figure 1, the configuration of the SABA MIMO testbed is shown. The testbed supports up to eight transceiver modules. ...
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... industrial PC rack in the left part of Figure 1 includes the digital signal processing, embedding a host PC which is connected to two carrier boards with FPGAs modules via cPCI interface. Together the two carrier boards provide eight slots for FPGA modules. ...
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... real MIMO system was modeled and simulated us- ing the scattering matrix form introduced above. Figure 10 shows the results of these simulations which are based on an indoor scenario at a frequency of 10.5 GHz. The number of the base and mobile station antennas is 8 and 4. The modu- lation used is QPSK. ...
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... block diagram of Figure 11 gives an overview of the analog signal processing of a transceiver. Each transceiver of our demonstrator consists of filters, amplifiers, controlled attenuation circuits, mixers, LO frequency processing, volt- age/current supply, sensors, and control and surveillance circuits. ...
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... they should be constant within one calibration period. As no precise attenuation val- ues are required, the circuit of Figure 12 has been chosen, which is distinguished by a very simple structure using only four PIN diodes for the required three stages. The PIN diodes are connected between the microstrip transmission lines and the stubs, marked with the numbers 1 to 4 in the layout. ...
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... specifications of this four-port component re- sult from the following requirements: low insertion loss in the transmit or receive path (< 2 dB), high isolation within the corresponding off-state (> 40 dB), connection of the cal- ibration port to the transmitter output or receiver input with controllable attenuation factors for supplying the calibration signals at different levels, sufficient low return loss at all ports during all states of the switch, and fast switch time to fulfill the timing requirements. Figure 13 shows the antenna and calibration switch realized using microstrip technology. The switch consists of 90 • hybrids that are connected in series. ...
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Citations
... Along with multiuser MIMO [96,97,98], cognitive radio is the field where most experimental research activities are being carried out through testbeds [99,100,101,102,103]. Here, the main focus is the dynamic use of spectrum by networks of systems coordinated by cognitive entities which reside on the network nodes. ...
The scarcity of spectral resources in wireless communications, due to a fixed frequency allocation policy, is a strong limitation to the increasing demand for higher data rates. However, measurements showed that a large part of frequency channels are underutilized or almost unoccupied. The cognitive radio paradigm arises as a tempting solution to the spectral congestion problem. A cognitive radio must be able to identify transmission opportunities in unused channels and to avoid generating harmful interference with the licensed primary users. Its key enabling technology is the spectrum sensing unit, whose ultimate goal consists in providing an indication whether a primary transmission is taking place in the observed channel. Such indication is determined as the result of a binary hypothesis testing experiment wherein null hypothesis (alternate hypothesis) corresponds to the absence (presence) of the primary signal. The first parts of this thesis describes the spectrum sensing problem and presents some of the best performing detection techniques. Energy Detection and multi-antenna Eigenvalue-Based Detection algorithms are considered. Important aspects are taken into account, like the impact of noise estimation or the effect of primary user traffic. The performance of each detector is assessed in terms of false alarm probability and detection probability. In most experimental research, cognitive radio techniques are deployed in software-defined radio systems, radio transceivers that allow operating parameters (like modulation type, bandwidth, output power, etc.) to be set or altered by software.In the second part of the thesis, we introduce the software-defined radio concept. Then, we focus on the implementation of Energy Detection and Eigenvalue-Based Detection algorithms: first, the used software platform, GNU Radio, is described, secondly, the implementation of a parallel energy detector and a multi-antenna eigenbased detector is illustrated and details on the used methodologies are given. Finally, we present the deployed experimental cognitive testbeds and the used radio peripherals. The obtained algorithmic results along with the software-defined radio implementation may offer a set of tools able to create a realistic cognitive radio system with real-time spectrum sensing capabilities.
... In the context of physical layer research, topics like multiuser MIMO, inter-cell cooperation and interference management are today very active. Many experimental test beds have been reported in the literature, e.g., [32], [30], [21], [34], [35], [36], [37], [38], [39], [40]. In most cases, these test beds consist of a single base station equipped with multiple antennas which makes possible to exploit the spatial diversity in order to increase the spectral efficiency. ...
Research on intelligent and reconfigurable wireless systems is in continuous evolution. Nevertheless, in order to fix some keystones, more and more researchers are entering the idea of research-oriented test beds. Unfortunately, it is very difficult for a wide number of research groups to start with their own set up, since the potential costs and efforts could not pay back in term of expected research results. Software Defined Radio solutions offer an easy way to communication researchers for the development of customized research test beds. While several hardware products are commercially available, the software is most of the times open source and ready to use for third party users. Even though the software solution developers claim complete easiness in the development of custom applications, in reality there are a number of practical hardware and software issues that research groups need to face, before they are up and running in generating results. With this chapter we would like to provide a tutorial guide, based on direct experience, on how to enter in the world of test bed-based research, providing both insight on the issues encountered in every day development, and practical solutions. Finally, an overview on common research-oriented software products for SDR development, namely GNU Radio, Iris, and ASGARD, will be provided, including how to practically start the software development of simple applications. Finally, best practices and examples of all the software platforms will be provided, giving inspiration to researchers on how to possibly build their own customized systems.
... Por esta razón, las simulaciones realizadas por ordenador sólo son útiles como punto de partida en la comprensión de los conceptos clave de las comunicaciones digitales inalámbricas modernas pero no permiten estudiar y comprender cuestiones de implementación muy importantes. Durante los últimos años, se han construido diferentes bancos de pruebas multi-antena de propósito general para evaluar el rendimiento de diversas técnicas de procesado de señal y/o estándares (por ejemplo, [4] [6]). A primera vista, uno puede pensar que los estudiantes universitarios pueden participar en el desarrollo de bancos de pruebas pero, de hecho , sólo los estudiantes de posgrado con experiencia de alto nivel están involucrados en tales desarrollos . ...
... Por esta razón, las simulaciones realizadas por ordenador sólo son útiles como punto de partida en la comprensión de los conceptos clave de las comunicaciones digitales inalámbricas modernas pero no permiten estudiar y comprender cuestiones de implementación muy importantes. Durante los últimos años, se han construido diferentes bancos de pruebas multi-antena de propósito general para evaluar el rendimiento de diversas técnicas de procesado de señal y/o estándares (por ejemplo, [4, 6]). A primera vista, uno puede pensar que los estudiantes universitarios pueden participar en el desarrollo de bancos de pruebas pero, de hecho , sólo los estudiantes de posgrado con experiencia de alto nivel están involucrados en tales desarrollos . ...
Resumen Este trabajo presenta una herramienta de aprendi-zaje asistido por banco de pruebas formada por tres elementos: plataforma hardware, arquitectura de software multicapa y herramienta gráfica (gtTAL). Para el desarrollo de la herramienta se ha optado por una arquitectura multicapa donde el nivel más alto es una interfaz gráfica que permite la interacción con la plataforma sin necesidad de tener conocimientos de programación de hardware a bajo nivel. Por tanto, los estudiantes pueden testear algoritmos fácilmente sin desarrollar un nuevo programa desde cero, redu-ciendo significativamente el tiempo empleado para las tareas de implementación y optimización.
... During the last years, different general-purpose multiple-antenna testbeds have been constructed to evaluate the performance of diverse signal processing techniques and/or standards (e.g. (Borkowski et al., 2006;Caban et al., 2006)). At a first glance, one may think that undergraduate students can participate in the development of testbeds but, in fact, only postgraduate students with high expertise are involved in such teams. ...
We introduce gtTAL, a graphical tool implemented on top of a distributed multilayer architecture which is specifically suitable for multiple-antenna hardware testbeds. gtTAL helps in teaching digital communications by allowing interaction with the hardware testbed at an abstraction level suitable for undergraduate students. Instead of using the low-level interfaces provided by hardware manufacturers, the multilayer software architecture supplies a high level interface access for testbeds, releasing students from the necessity of knowing low-level details of the hardware to start to practice with it. Therefore, they can easily test algorithms without developing a new program from scratch, speeding up the time needed for both the implementation and the debugging tasks. Indeed, the multilayer software architecture allows learning how to deal with real-world digital communication systems at different abstraction levels, varying from the lowest level software running in real-time in DSPs or FPGAs, to the highest level software like gtTAL. These three elements: hardware testbed, multilayer software architecture and graphical tool (gtTAL), constitutes what we termed testbed-assisted learning.
MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.
Software Defined Radio (SDR) can move the complicated signal processing and handling procedures involved in communications from radio equipment into computer software. Consequently, SDR equipment could consist of only a few chips connected to an antenna. In this paper, we present an implemented SDR testbed, which consists of four complete SDR nodes. Using the designed testbed, we have conducted two case studies. The first is designed to facilitate video transmission via adaptive LTE links. Our experimental results demonstrate that adaptive LTE link video transmission could reduce the bandwidth usage for data transmission. In the second case study, we perform UE location estimation by leveraging the signal strength from nearby cell towers, pertinent to various applications, such as public safety and disaster rescue scenarios where GPS (Global Position System) is not available (e.g., indoor environment). Our experimental results show that it is feasible to accurately derive the location of a UE (User Equipment) by signal strength. In addition, we design a Hardware In the Loop (HIL) simulation environment using the Vienna LTE simulator, srsLTE library, and our SDR testbed. We develop a software wrapper to connect the Vienna LTE simulator to our SDR testbed via the srsLTE library. Our experimental results demonstrate the comparative performance of simulated UEs and eNodeBs against real SDR UEs and eNodeBs, as well as how a simulated environment can interact with a real-world implementation.
Based on our experience in MIMO testbed design and implemen-tation, we provide an up-to-date classification of the most rele-vant MIMO testbeds developed so far by the research commu-nity. First, we include an overview of the different tools enabling real test and measurement, making a clear distinction among testbeds, demonstrators and prototypes, and emphasising their key features. We also describe the structure of a typical MIMO testbed, detailing its hardware components and software mod-ules. Baseband components, RF front-ends and software devel-opment tools are analysed, enabling us to point out the challenges that must be overcome in the future. Finally, several guidelines for the evolution of testbeds are proposed.
This paper presents field experiments on a Multi-Input Multi-Output (MIMO) system that combines Adaptive Beamforming (ABF)
and Spatial Multiplexing (SM) procedures. The combination of SM signal processing with ABF is applied to WiBro, the South
Korean Orthogonal Frequency Division Multiplexing (OFDM) system that follows the IEEE 802.16e standard. The field experimental
results show that ABF-MIMO OFDM system outperforms a simple MIMO OFDM system by 2dB (1.5dB) in the signal to noise ratio
(SNR) for 16-QAM (64-QAM) under low correlated fading channel and 4dB (2.5dB) in the SNR for 16-QAM (64-QAM) under highly
correlated fading channel, respectively, at the frame error rate (FER) of 1%. Details on the implementation of ABF-MIMO OFDM
system is also presented in this paper. Through the system implementation and its field experimental results, we verify that
the combination of MIMO OFDM system with ABF provides improved performance over a simple MIMO OFDM system in real propagation
channel environment and, in particular, it is more effective in highly correlated fading channel.
KeywordsMIMO–Adaptive beamforming (ABF)–OFDM–IEEE 802.16e–WiBro
We present ¿FlexVehd¿, a flexible radio testbed for experimental testing of transmission and reception algorithms in vehicular environments. The main feature of our testbed is to provide maximum flexibility to researchers when conducting their experiments. FlexVehd allows the user to implement in software the signal construction at transmission and its reconstruction at reception, because it incorporates the necessary interfacing mechanisms between high level programming languages and radio hardware. This benefits rapid prototyping of new transmission and reception techniques at a high abstraction level (i.e. Matlab/Simulink, C/C++...), while preserving the realism of experimental tests. In particular, we present an implementation of the IEEE 802.11p PHY layer and its experimental performance results for high vehicle speeds.