Channel Acquisition for HF Skywave Massive MIMO-OFDM Communications

In this paper, we investigate channel acquisition for high frequency (HF) skywave massive multiple-input multiple-output (MIMO) communications with orthogonal frequency division multiplexing (OFDM) modulation. We first introduce the concept of triple beams (TBs) in the space-frequency-time (SFT) domain and establish a TB based channel model using sampled triple steering vectors. With the established channel model, we then investigate the optimal channel estimation and pilot design for pilot segments. Specifically, we find the conditions that allow pilot reuse among multiple user terminals (UTs), which significantly reduces pilot overhead. Moreover, we propose a channel prediction method for data segments based on the estimated TB domain channel. To reduce the complexity, we are able to formulate the channel estimation as a sparse signal recovery problem due to the channel sparsity in the TB domain and then obtain the channel by the proposed constrained Bethe free energy minimization (CBFEM) based channel estimation algorithm, which can be implemented with low complexity by exploiting the structure of the TB matrix together with the chirp z-transform (CZT). Simulation results demonstrate the superior performance of the proposed channel acquisition approach.Comment: 30 pages, 4 figure

Optimizing the mmWave Channel Estimation Duration by Rate Prediction

In millimeter-wave (mmWave) wireless communications, the duration of the channel estimation plays a major role to establish the links before data transmission. However, fixed or long channel estimation can substantially hinder the achievable transmit data rates. In this letter, we propose a new scheme that optimizes the channel estimation duration to establish the link between the base station (BS) and a mobile station (MS) in mmWave communications. Before pilot transmissions, the BS predicts the downlink effective rate that would be achieved after channel estimation with the pilot precoder and compares this predicted rate with the current rate, based on the current channel estimates. The proposed scheme optimizes the mmWave channel estimation duration by ending pilot transmissions when the predicted rate is lower than the current rate

Hierarchical compressed sensing

Compressed sensing is a paradigm within signal processing that provides the means for recovering structured signals from linear measurements in a highly efficient manner. Originally devised for the recovery of sparse signals, it has become clear that a similar methodology would also carry over to a wealth of other classes of structured signals. In this work, we provide an overview over the theory of compressed sensing for a particularly rich family of such signals, namely those of hierarchically structured signals. Examples of such signals are constituted by blocked vectors, with only few non-vanishing sparse blocks. We present recovery algorithms based on efficient hierarchical hard-thresholding. The algorithms are guaranteed to converge, in a stable fashion both with respect to measurement noise as well as to model mismatches, to the correct solution provided the measurement map acts isometrically restricted to the signal class. We then provide a series of results establishing the required condition for large classes of measurement ensembles. Building upon this machinery, we sketch practical applications of this framework in machine-type communications and quantum tomography.Comment: This book chapter is a report on findings within the DFG-funded priority program `Compressed Sensing in Information Processing' (CoSIP

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

MIMO underwater acoustic communications over time-varying channels: from theory to practice

Despite more than 70% of our planet surface is covered by water, today the underwater world can still be considered largely unknown. Rivers, lakes, seas and oceans have always been a fundamental resource for human life development, but at the same time they have often represented natural obstacles very hard to surmount. The most impressive example is probably given by the ocean, whose vastness severely limited geographical explorations and discoveries for tens of centuries. Anyway, the growing curiosity about what happens below the water surface has gradually led man to immerse in this unknown environment, trying to overcome its inaccessibility and figure out its secrets. Underwater investigation and exploring have been increasingly supported by technology, advanced over time for different purposes (military, commercial, scientific). In this regard, providing a communication link between remote users has been recognized as one of the main issues to be addressed. The first significant solutions derived from the radio-frequency world, subject of study since the 19th century. Unfortunately both wired and wireless RF inspired signal propagation strategies were not evaluated as successful. The former ones, since considering the deployment of meters (up to kilometers) of cable in depth, were too costly and difficult, while the latter ones did not offer good performance in terms of communication range due to signal attenuation. An alternative way, examined with particular interest from the beginning of the 20th century, has been that one offered by acoustics. Actually, the study of sound and its propagation through different media has been an intriguing topic since the Old World Age, hence the attempt of messaging underwater has seemed to be a great opportunity to convey theoretical principles in a real application. In addition, not only humans but also marine animals use acoustic waves to communicate, even over several kilometers distances as demonstrated by whales. So, since already existing in nature, acoustic communications have been considered as potentially successful, furthermore representing an effective trade-off between feasibility and performance, especially if compared to the other electromagnetic signals-based methods. Communication over RF channels has been extensively investigated so as to become a mature technology. The thorough knowledge about OSI (Open Systems Interconnection) model physical layer issues has allowed the researchers attention to be drawn to the upper layers. Following this direction, the recent advances in technology in this field have been accomplished mainly due to novelties in networks managing rather than to enhancements in the signal propagation study. Moving to acoustics, unfortunately this approach results to be failing if applied in the underwater scenario, as the major challenges rise indeed from physics matters. The underwater environment is varied and variable, so understanding the mechanisms that govern the propagation of sound in water is a key element for the design of a well-performing communication system. In this sense, the physical layer has therefore regained the centrality that has been diminished in other contexts. The underwater acoustic communications can be adopted in a wide range of applications. The best-known are coastal monitoring, target detection, AUVs (Autonomous Underwater Vehicles) remote control, tsunami alarm, environmental data collection and transmission. Those ones are very specific activities, so the devices to be employed must sometimes meet very strict requirements. In this regard, the solutions commercially available provide good performance (that are paid in terms of high costs). On the other hand, the fact that hardware and software are usually copyrighted leads to have a closed system. Having reconfigurable devices is instead an opportunity to match the technology with the environment features and variations, especially in real-time applications. Recently, the need to overcome these constraints has encouraged the debate about underwater technology challenges. The work by Demirors et al. [1] reports an interesting discussion about the implementation of software-defined underwater acoustic networks (UWANs), highlighting how this solution can provide enhancements in terms of software portability, computational capacity, energy efficiency and real-time reconfigurability. Furthermore, the authors propose the architecture of a software-defined acoustic modem and evaluate its performance and capabilities with tank and lake experiments. Considering the comments outlined above, the following dissertation deals with the design of an acoustic communication system. The preliminary theoretical analysis regarding physical layer concerns, such as signal propagation and channel behavior, represents the starting point from which several proposals regarding the implementation of UWANs are introduced. In particular the context of Multiple-Input Multiple-Output (MIMO) communications is investigated, presenting several solutions about transmission schemes and receiver implementation. Furthermore, concerning UWANs management, some strategies for access and error control, established at the data link layer level, are detailed. It is worth highlighting that the goal of this contribution is not to present a disjointed discussion about the topics just listed. The objective is instead to propose practical solutions developed hand in hand with theory, making choices firstly by looking at what nature allows