D21.3 Analysis of initial results at EuWIN@CTTC

Deliverable D21.3 del projecte europeu NEWCOM#The nature of this Deliverable of WP2.1 (“Radio interfaces for next-generation wireless systems”) is mainly descriptive and its purpose is to provide a report on the status of the different Joint Research Activities (JRAs) currently ongoing, some of them being performed on the facilities that are available at EuWInPeer ReviewedPreprin

Synchronization in digital communication systems: performance bounds and practical algorithms

Communication channels often transfer signals from different transmitters. To avoid interference the available frequency spectrum is divided into non-overlapping frequency bands (bandpass channels) and each transmitter is assigned to a different bandpass channel. The transmission of a signal over a bandpass channel requires a shift of its frequency-content to a frequency range that is compatible with the designated frequency band (modulation). At the receiver, the modulated signal is demodulated (frequency shifted back to the original frequency band) in order to recover the original signal. The modulation/demodulation process requires the presence of a locally generated sinusoidal signal at both the transmitter and the receiver. To enable a reliable information transfer, it is imperative that these two sinusoids are accurately synchronized. Recently, several powerful channel codes have been developed which enable reliable communication at a very low signal-to-noise ratio (SNR). A by-product of these developments is that synchronization must now be performed at a SNR that is lower than ever before. Of course, this imposes high requirements on the synchronizer design. This doctoral thesis investigates to what extent (performance bounds) and in what way (practical algorithms) the structure that the channel code enforces upon the transmitted signal can be exploited to improve the synchronization accuracy at low SNR

Sparse graph-based coding schemes for continuous phase modulations

The use of the continuous phase modulation (CPM) is interesting when the channel represents a strong non-linearity and in the case of limited spectral support; particularly for the uplink, where the satellite holds an amplifier per carrier, and for downlinks where the terminal equipment works very close to the saturation region. Numerous studies have been conducted on this issue but the proposed solutions use iterative CPM demodulation/decoding concatenated with convolutional or block error correcting codes. The use of LDPC codes has not yet been introduced. Particularly, no works, to our knowledge, have been done on the optimization of sparse graph-based codes adapted for the context described here. In this study, we propose to perform the asymptotic analysis and the design of turbo-CPM systems based on the optimization of sparse graph-based codes. Moreover, an analysis on the corresponding receiver will be done

Exposing a waveform interface to the wireless channel for scalable video broadcast

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 157-167).Video broadcast and mobile video challenge the conventional wireless design. In broadcast and mobile scenarios the bit-rate supported by the channel differs across receivers and varies quickly over time. The conventional design however forces the source to pick a single bit-rate and degrades sharply when the channel cannot support it. This thesis presents SoftCast, a clean-slate design for wireless video where the source transmits one video stream that each receiver decodes to a video quality commensurate with its specific instantaneous channel quality. To do so, SoftCast ensures the samples of the digital video signal transmitted on the channel are linearly related to the pixels' luminance. Thus, when channel noise perturbs the transmitted signal samples, the perturbation naturally translates into approximation in the original video pixels. Hence, a receiver with a good channel (low noise) obtains a high fidelity video, and a receiver with a bad channel (high noise) obtains a low fidelity video. SoftCast's linear design in essence resembles the traditional analog approach to communication, which was abandoned in most major communication systems, as it does not enjoy the theoretical opimality of the digital separate design in point-topoint channels nor its effectiveness at compressing the source data. In this thesis, I show that in combination with decorrelating transforms common to modern digital video compression, the analog approach can achieve performance competitive with the prevalent digital design for a wide variety of practical point-to-point scenarios, and outperforms it in the broadcast and mobile scenarios. Since the conventional bit-pipe interface of the wireless physical layer (PHY) forces the separation of source and channel coding, to realize SoftCast, architectural changes to the wireless PHY are necessary. This thesis discusses the design of RawPHY, a reorganization of the PHY which exposes a waveform interface to the channel while shielding the designers of the higher layers from much of the perplexity of the wireless channel. I implement SoftCast and RawPHY using the GNURadio software and the USRP platform. Results from a 20-node testbed show that SoftCast improves the average video quality (i.e., PSNR) across diverse broadcast receivers in our testbed by up to 5.5 dB in comparison to conventional single- or multi-layer video. Even for a single receiver, it eliminates video glitches caused by mobility and increases robustness to packet loss by an order of magnitude.by Szymon Kazimierz Jakubczak.Ph.D

A Tutorial on the Tracking, Telemetry, and Command (TT&C) for Space Missions

This paper presents a tutorial on the Tracking, Telemetry, and Command (TT&C) for spacecraft and satellite missions. In particular, it provides a thorough summary of the design of the TT&C, starting from elementary system aspects and going down to the details of the on-board TT&C subsystem design, its units, and the physical layer. The paper is then complemented with a description of emerging TT&C techniques and technologies, the standardization framework, and practical examples of actual spacecraft design of European space missions. The here-presented tutorial is thought for professionals (also in other telecommunication engineering fields) willing to face the challenges and state-of-the-art of the TT&C, and know more about this fundamental function that allows us to control and monitor our spacecraft on a daily basis

Cooperative systems based signal processing techniques with applications to three-dimensional video transmission

Three-dimensional (3-D) video has recently emerged to offer an immersive multimedia experience that can not be offered by two-dimensional (2-D) video applications. Currently, both industry and academia are focused on delivering 3-D video services to wireless communication systems. Modern video communication systems currently adopt cooperative communication and orthogonal frequency division multiplexing (OFDM) as they are an attractive solution to combat fading in wireless communication systems and achieve high data-rates. However, this strong motivation to transmit the video signals over wireless systems faces many challenges. These are mainly channel bandwidth limitations, variations of signal-to-noise ratio (SNR) in wireless channels, and the impairments in the physical layer such as time varying phase noise (PHN), and carrier frequency offset (CFO). In response to these challenges, this thesis seeks to develop efficient 3-D video transmission methods and signal processing algorithms that can overcome the effects of error-prone wireless channels and impairments in the physical layer. In the first part of the thesis, an efficient unequal error protection (UEP) scheme, called video packet partitioning, and a new 3-D video transceiver structure are proposed. The proposed video transceiver uses switching operations between various UEP schemes based on the packet partitioning to achieve a trade- off between system complexity and performance. Experimental results show that the proposed system achieves significantly high video quality at different SNRs with the lowest possible bandwidth and system complexity compared to direct transmission schemes. The second part of the thesis proposes a new approach to joint source-channel coding (JSCC) that simultaneously assigns source code rates, the number of high and low priority packets, and channel code rates for the application, network, and physical layers, respectively. The proposed JSCC algorithm takes into account the rate budget constraint and the available instantaneous SNR of the best relay selection in cooperative systems. Experimental results show that the proposed JSCC algorithm outperforms existing algorithms in terms of peak signal-to-noise ratio (PSNR). In the third part of the thesis, a computationally efficient training based approach for joint channel, CFO, and PHN estimation in OFDM systems is pro- posed. The proposed estimator is based on an expectation conditional maximization (ECM) algorithm. To compare the estimation accuracy of the proposed estimator, the hybrid Cram´er-Rao lower bound (HCRB) of hybrid parameters of interest is derived. Next, to detect the signal in the presence of PHN, an iterative receiver based on the extended Kalman filter (EKF) for joint data detection and PHN mitigation is proposed. It is demonstrated by numerical simulations that, compared to existing algorithms, the performance of the proposed ECM-based estimator in terms of the mean square error (MSE) is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high SNRs. Finally, this study extends the research on joint channel, PHN, and CFO estimation one step forward from OFDM systems to cooperative OFDM systems. An iterative algorithm based on the ECM in cooperative OFDM networks in the presence of unknown channel gains, PHNs and CFOs is applied. Moreover, the HCRB for the joint estimation problem in both decode-and-forward (DF) and amplify-and-forward (AF) relay systems is presented. An iterative algorithm based on the EKF for data detection and tracking the unknown time-varying PHN throughout the OFDM data packet is also used. For more efficient 3-D video transmission, the estimation algorithms and UEP schemes based packet portioning were combined to achieve a more robust video bit stream in the presence of PHNs. Applying this combination, simulation results demonstrate that promising bit-error-rate (BER) and PSNR performance can be achieved at the destination at different SNRs and PHN variance. The proposed schemes and algorithms offer solutions for existing problems in the techniques for applications to 3-D video transmission

Hybrid solutions to instantaneous MIMO blind separation and decoding: narrowband, QAM and square cases

Future wireless communication systems are desired to support high data rates and high quality transmission when considering the growing multimedia applications. Increasing the channel throughput leads to the multiple input and multiple output and blind equalization techniques in recent years. Thereby blind MIMO equalization has attracted a great interest.Both system performance and computational complexities play important roles in real time communications. Reducing the computational load and providing accurate performances are the main challenges in present systems. In this thesis, a hybrid method which can provide an affordable complexity with good performance for Blind Equalization in large constellation MIMO systems is proposed first. Saving computational cost happens both in the signal sep- aration part and in signal detection part. First, based on Quadrature amplitude modulation signal characteristics, an efficient and simple nonlinear function for the Independent Compo- nent Analysis is introduced. Second, using the idea of the sphere decoding, we choose the soft information of channels in a sphere, and overcome the so- called curse of dimensionality of the Expectation Maximization (EM) algorithm and enhance the final results simultaneously. Mathematically, we demonstrate in the digital communication cases, the EM algorithm shows Newton -like convergence.Despite the widespread use of forward -error coding (FEC), most multiple input multiple output (MIMO) blind channel estimation techniques ignore its presence, and instead make the sim- plifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In final part of this work, we exploit the iterative channel estimation and decoding performance for blind MIMO equalization. Experiments show the improvements achievable by exploiting the existence of coding structures and that it can access the performance of a BCJR equalizer with perfect channel information in a reasonable SNR range. All results are confirmed experimentally for the example of blind equalization in block fading MIMO systems

Towards large-scale and collaborative spectrum monitoring systems using IoT devices

Mención Internacional en el título de doctorThe Electromagnetic (EM) spectrum is well regulated by frequency assignment authorities, national regulatory agencies and the International Communication Union (ITU). Nowadays more and more devices such as mobile phones and Internet-of-Things (IoT) sensors make use of wireless communication. Additionally we need a more efficient use and a better understanding of the EM space to allocate and manage efficiently all communications. Governments and telecommunication operators perform spectrum measurements using expensive and bulky equipments scheduling very specific and limited spectrum campaigns. However, this approach does not scale as it can not allow to widely scan and analyze the spectrum 24/7 in real time due to the high cost of the large deployment. A pervasive deployment of spectrum sensors is required to solve this problem, allowing to monitor and analyze the EM radio waves in real time, across all possible frequencies, and physical locations. This thesis presents ElectroSense, a crowdsourcing and collaborative system that enables large scale deployments using Internet-of-Things (IoT) spectrum sensors to collect EM spectrum data which is analyzed in a big data infrastructure. The ElectroSense platform seeks a more efficient, safe and reliable real-time monitoring of the EM space by improving the accessibility and the democratization of spectrum data for the scientific community, stakeholders and the general public. In this work, we first present the ElectroSense architecture, and the design challenges that must be faced to attract a large community of users and all potential stakeholders. It is envisioned that a large number of sensors deployed in ElectroSense will be at affordable cost, supported by more powerful spectrum sensors when possible. Although low-cost Radio Frequency (RF) sensors have an acceptable performance for measuring the EM spectrum, they present several drawbacks (e.g. frequency range, Analog-to-Digital Converter (ADC), maximum sampling rate, etc.) that can negatively affect the quality of collected spectrum data as well as the applications of interest for the community. In order to counteract the above-mentioned limitations, we propose to exploit the fact that a dense network of spectrum sensors will be in range of the same transmitter(s). We envision to exploit this idea to enable smart collaborative algorithms among IoT RF sensors. In this thesis we identify the main research challenges to enable smart collaborative algorithms among low-cost RF sensors. We explore different crowdsourcing and collaborative scenarios where low-cost spectrum sensors work together in a distributed manner. First, we propose a fast and precise frequency offset estimation method for lowcost spectrum receivers that makes use of Long Term Evolution (LTE) signals broadcasted by the base stations. Second, we propose a novel, fast and precise Time-of-Arrival (ToA) estimation method for aircraft signals using low-cost IoT spectrum sensors that can achieve sub-nanosecond precision. Third, we propose a collaborative time division approach among sensors for sensing the spectrum in order to reduce the network uplink bandwidth for each spectrum sensor. By last, we present a methodology to enable the signal reconstruction in the backend. By multiplexing in frequency a certain number of non-coherent low-cost spectrum sensors, we are able to cover a signal bandwidth that would not otherwise be possible using a single receiver. At the time of writing we are the first looking at the problem of collaborative signal reconstruction and decoding using In-phase & Quadrature (I/Q) data received from low-cost RF sensors. Our results reported in this thesis and obtained from the experiments made in real scenarios, suggest that it is feasible to enable collaborative spectrum monitoring strategies and signal decoding using commodity hardware as RF sensing sensors.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Bozidar Radunovic.- Secretario: Paolo Casari.- Vocal: Fco. Javier Escribano Aparici