Advanced techniques for spectrally efficient DVB-S2X systems

We investigate different techniques to improve the spectral efficiency of systems based on the DVB-S2 standard, when the transmitted signal bandwidth cannot be increased because it has already been optimized to the maximum value allowed by transponder filters. We will investigate and compare several techniques to involve different sections of the transceiver scheme. The techniques that will be considered include the use of advanced detection algorithms, the adoption of time packing, and the optimization of the constellation and shaping pulses. The LDPC codes recently proposed for the evolution of the DVB-S2 standard will be considered, as well as the adoption of iterative detection and decoding. Information theoretical analysis will be followed by the study of practical modulation and coding schemes

Improving the Spectral Efficiency of Nonlinear Satellite Systems through Time-Frequency Packing and Advanced Processing

We consider realistic satellite communications systems for broadband and broadcasting applications, based on frequency-division-multiplexed linear modulations, where spectral efficiency is one of the main figures of merit. For these systems, we investigate their ultimate performance limits by using a framework to compute the spectral efficiency when suboptimal receivers are adopted and evaluating the performance improvements that can be obtained through the adoption of the time-frequency packing technique. Our analysis reveals that introducing controlled interference can significantly increase the efficiency of these systems. Moreover, if a receiver which is able to account for the interference and the nonlinear impairments is adopted, rather than a classical predistorter at the transmitter coupled with a simpler receiver, the benefits in terms of spectral efficiency can be even larger. Finally, we consider practical coded schemes and show the potential advantages of the optimized signaling formats when combined with iterative detection/decoding.Comment: 8 pages, 8 figure

Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding

Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory). Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE) algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations

Iterative pre-distortion of the non-linear satellite channel

Digital Video Broadcasting - Satellite - Second Generation (DVB-S2) is the current European standard for satellite broadcast and broadband communications. It relies on high order modulations up to 32-amplitude/phase-shift-keying (APSK) in order to increase the system spectral efficiency. Unfortunately, as the modulation order increases, the receiver becomes more sensitive to physical layer impairments, and notably to the distortions induced by the power amplifier and the channelizing filters aboard the satellite. Pre-distortion of the non-linear satellite channel has been studied for many years. However, the performance of existing pre-distortion algorithms generally becomes poor when high-order modulations are used on a non-linear channel with a long memory. In this paper, we investigate a new iterative method that pre-distorts blocks of transmitted symbols so as to minimize the Euclidian distance between the transmitted and received symbols. We also propose approximations to relax the pre-distorter complexity while keeping its performance acceptable

A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community

In recent years, deep learning (DL), a re-branding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, natural language processing, etc. Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV; e.g., statistics, fusion, and machine learning, to name a few. This means that the RS community should be aware of, if not at the leading edge of, of advancements like DL. Herein, we provide the most comprehensive survey of state-of-the-art RS DL research. We also review recent new developments in the DL field that can be used in DL for RS. Namely, we focus on theories, tools and challenges for the RS community. Specifically, we focus on unsolved challenges and opportunities as it relates to (i) inadequate data sets, (ii) human-understandable solutions for modelling physical phenomena, (iii) Big Data, (iv) non-traditional heterogeneous data sources, (v) DL architectures and learning algorithms for spectral, spatial and temporal data, (vi) transfer learning, (vii) an improved theoretical understanding of DL systems, (viii) high barriers to entry, and (ix) training and optimizing the DL.Comment: 64 pages, 411 references. To appear in Journal of Applied Remote Sensin

Advanced low-complexity multiuser receivers

It tema centrale di questa tesi è la rivelazione multi-utente per sistemi di comunicazione wireless ad elevata efficienza spettrale. Lo scopo del lavoro è quello di proporre nuovi ricevitori multi-utente a bassa complessità con elevate prestazioni. Sono considerati sistemi satellitari basati su FDM (Frequency Division Multiplexing), in cui ogni utente adotta una modulazione CPM (Continuous Phase Modulation) concatenata serialmente con un codificatore tramite un interlacciatore e decodifica iterativa. Si considerano, inoltre, canali lineari in presenza di AWGN (additive white Gaussian noise). In particolare, si studiano sistemi FDM, in cui i canali adiacenti possono sovrapporsi in frequenza per aumentere l'efficienza spettrale, e sistemi CDMA (code division multiple access). Per gli scenari presi in esame, proponiamo schemi di rivelazione con un eccellente compromesso tra prestazioni e complessità computazionale, che permettono di implementare schemi di trasmissione con straordinaria efficienza spettrale, al prezzo di un limitato aumento di complessità rispetto ad un classico ricevitore singolo-utente che ignora l'interferenza.This thesis deals with multiuser detection (MUD) for spectrally-efficient wireless communication systems. The aim of this work is to propose new advanced low-complexity multiuser receivers with near-optimal detection performance. We consider frequency division multiplexing (FDM) satellite systems where each user employs a continuous phase modulation (CPM), serially concatenated with an outer code through an interleaver, and iterative detection/decoding. We also consider linear channels impaired by additive white Gaussian noise (AWGN), focusing on FDM systems where adjacent channels are allowed to overlap in frequency, and on code division multiple access systems (CDMA). For the considered scenarios, we propose detection schemes with an excel- lent performance/complexity tradeoff which allow us to implement transmission schemes with unprecedented spectral efficiency at a price of a limited complexity increase with respect to a classical single-user receiver which neglects the interference