Partial-Data Superimposed Training with Data Precoding for OFDM Systems

Superimposed training (ST) is a recently addressed technique used for channel estimation where known training sequences are arithmetically added to data symbols, avoiding the use of dedicated pilot subcarriers, and thus, increasing the available bandwidth compared with traditional pilot symbol assisted modulation schemes. However, the system handles data interference over channel estimation as a result of the ST process; also, data detection is degraded by pilot interference. Recent ST methods have analyzed the data interference and presented schemes that deal with it. We propose a novel superimposed model over a precoded data scheme, named partial-data superimposed training (PDST), where an interference control factor assigns the adequate information level to be added to the training sequence in orthogonal frequency division multiplexing systems. Also, a data detection method is introduced to improve the symbol error rate performance. Moreover, a capacity analysis of the system has been derived. Finally, simulation results confirm that performance of PDST is superior to previous proposals

Advanced signal processing solutions for ATR and spectrum sharing in distributed radar systems

Previously held under moratorium from 11 September 2017 until 16 February 2022This Thesis presents advanced signal processing solutions for Automatic Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems. Two Synthetic Aperture Radar (SAR) ATR algorithms are described for full- and single-polarimetric images, and tested on the GOTCHA and the MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments, that, being discrete defined, provide better representations of targets’ details. The proposed image moments based framework can be extended to the availability of several images from multiple sensors through the implementation of a simple fusion rule. A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopter’s rotor and received by the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating the number, the length and the rotation speed of the blades, parameters that are peculiar for each helicopter’s model. The algorithm is extended to deal with the identification of multiple helicopters flying in formation that cannot be resolved in another domain. Moreover, a fusion rule is presented to integrate the results of the identification performed from several sensors in a distributed radar system. Tests performed both on simulated signals and on real signals acquired from a scale model of a helicopter, confirm the validity of the algorithm. Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp sub-carriers generated through the Fractional Fourier Transform (FrFT), with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based waveform is extensively tested and compared with Orthogonal Frequency Division Multiplexing (OFDM) and LFM waveforms, in order to assess both its radar and communication performance.This Thesis presents advanced signal processing solutions for Automatic Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems. Two Synthetic Aperture Radar (SAR) ATR algorithms are described for full- and single-polarimetric images, and tested on the GOTCHA and the MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments, that, being discrete defined, provide better representations of targets’ details. The proposed image moments based framework can be extended to the availability of several images from multiple sensors through the implementation of a simple fusion rule. A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopter’s rotor and received by the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating the number, the length and the rotation speed of the blades, parameters that are peculiar for each helicopter’s model. The algorithm is extended to deal with the identification of multiple helicopters flying in formation that cannot be resolved in another domain. Moreover, a fusion rule is presented to integrate the results of the identification performed from several sensors in a distributed radar system. Tests performed both on simulated signals and on real signals acquired from a scale model of a helicopter, confirm the validity of the algorithm. Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp sub-carriers generated through the Fractional Fourier Transform (FrFT), with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based waveform is extensively tested and compared with Orthogonal Frequency Division Multiplexing (OFDM) and LFM waveforms, in order to assess both its radar and communication performance

Link adaptation for MC-CDMA radio interface

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Laboratory and field trials evaluation of transmit delay Diversity applied to DVB-T/H networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The requirements for future DVB-T/H networks demand that broadcasters design and deploy networks that provide ubiquitous reception in challenging indoors and other obstructed situations. It is essential that such networks are designed cost-effectively and with minimized environmental impact. The use of transmit diversity techniques with multiple antennas have long been proposed to improve the performance and capacity of wireless systems. Transmit diversity exploits the scattering effect inherent in the channel by means of transmitting multiple signals in a controlled manner from spatially separated antennas, allowing independently faded signals to arrive at the receiver and improves the chances of decoding a signal of acceptable quality. Transmit diversity can complement receive diversity by adding an additional diversity gain and in situations where receiver diversity is not practical, transmit diversity alone delivers a comparable amount of diversity gain. Transmit Delay Diversity (DD) can be applied to systems employing the DVB standard without receiver equipment modifications. Although transmit DD can provide a gain in NLOS situations, it can introduce degradation in LOS situation. The aim of this thesis is to investigate the effectiveness in real-word applications of novel diversity techniques for broadcast transmitter networks. Tests involved laboratory experiments using a wireless MIMO channel emulator and the deployment of a field measurement campaign dedicated to driving, indoor and rooftop reception. The relationship between the diversity gain, the propagation environment and several parameters such as the transmit antenna separation, the receiver speed and the Forward Error Correction Codes (FEC) configuration are investigated. Results includes the effect of real-word parameter usually not modeled in the software simulation analysis, such as antenna radiation patterns and mutual coupling, scattering vegetation impact, non-Gaussian noise sources and receiver implementation. Moreover, a practical analysis of the effectiveness of experimental techniques to mitigate the loss due to transmit DD loss in rooftop reception is presented. The results of this thesis confirmed, completed and extended the existing predictions with real word measurement results

Sensors and Systems for Indoor Positioning

This reprint is a reprint of the articles that appeared in Sensors' (MDPI) Special Issue on “Sensors and Systems for Indoor Positioning". The published original contributions focused on systems and technologies to enable indoor applications

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

Intelligent Approaches for Energy-Efficient Resource Allocation in the Cognitive Radio Network

The cognitive radio (CR) is evolved as the promising technology to alleviate the spectrum scarcity issues by allowing the secondary users (SUs) to use the licensed band in an opportunistic manner. Various challenges need to be addressed before the successful deployment of CR technology. This thesis work presents intelligent resource allocation techniques for improving energy efficiency (EE) of low battery powered CR nodes where resources refer to certain important parameters that directly or indirectly affect EE. As far as the primary user (PU) is concerned, the SUs are allowed to transmit on the licensed band until their transmission power would not cause any interference to the primary network. Also, the SUs must use the licensed band efficiently during the PU’s absence. Therefore, the two key factors such as protection to the primary network and throughput above the threshold are important from the PU’s and SUs’ perspective, respectively. In deployment of CR, malicious users may be more active to prevent the CR users from accessing the spectrum or cause unnecessary interference to the both primary and secondary transmission. Considering these aspects, this thesis focuses on developing novel approaches for energy-efficient resource allocation under the constraints of interference to the PR, minimum achievable data rate and maximum transmission power by optimizing the resource parameters such as sensing time and the secondary transmission power with suitably selecting SUs. Two different domains considered in this thesis are the soft decision fusion (SDF)-based cooperative spectrum sensing CR network (CRN) models without and with the primary user emulation attack (PUEA). An efficient iterative algorithm called iterative Dinkelbach method (IDM) is proposed to maximize EE with suitable SUs in the absence of the attacker. In the proposed approaches, different constraints are evaluated considering the negative impact of the PUE attacker on the secondary transmission while maximizing EE with the PUE attacker. The optimization problem associated with the non-convex constraints is solved by our proposed iterative resource allocation algorithms (novel iterative resource allocation (NIRA) and novel adaptive resource allocation (NARA)) with suitable selection of SUs for jointly optimizing the sensing time and power allocation. In the CR enhanced vehicular ad hoc network (CR-VANET), the time varying channel responses with the vehicular movement are considered without and with the attacker. In the absence of the PUE attacker, an interference-aware power allocation scheme based on normalized least mean square (NLMS) algorithm is proposed to maximize EE considering the dynamic constraints. In the presence of the attacker, the optimization problem associated with the non-convex and time-varying constraints is solved by an efficient approach based on genetic algorithm (GA). Further, an investigation is attempted to apply the CR technology in industrial, scientific and medical (ISM) band through spectrum occupancy prediction, sub-band selection and optimal power allocation to the CR users using the real time indoor measurement data. Efficacies of the proposed approaches are verified through extensive simulation studies in the MATLAB environment and by comparing with the existing literature. Further, the impacts of different network parameters on the system performance are analyzed in detail. The proposed approaches will be highly helpful in designing energy-efficient CRN model with low complexity for future CR deployment

Authentication and Message Integrity Verification without Secrets

Embedding network capabilities in a plethora of new devices and infrastructures--the Internet-of-Things, vehicular and aviation networks, the critical national infrastructure, industrial plants--are dramatically transforming the modern way of living. The rapid deployment pace of these emerging applications has brought unprecedented security challenges related to data confidentiality, user privacy, and critical infrastructure availability. A significant portion of these threats is attributed to the broadcast nature of the wireless medium, which exposes systems to easy-to-launch passive and active attacks. The slow security standards rollout combined with the ever-shrinking time-to-market, the device heterogeneity and the lack of user-friendly input interfaces (screen, keyboard, etc.) only exacerbate the security challenges. In this dissertation, we address the fundamental problem of trust establishment in the context of emerging network applications. We present techniques integrating physical layer properties with cryptographic primitives to guarantee message integrity and bootstrap initial trust without relying on any prior secrets. We present the ``helper'' security paradigm in which security is outsourced to one or more dedicated devices to allow for the scalable pairing of off-the-shelf heterogeneous devices. In addition, we present our work on message integrity verification of navigation information for aircrafts (speed, location, and heading) by exploiting the Doppler spread of the wireless channel. Finally, we develop a secure and fast voting technique for distributed networks which allows fast coordination of a group of devices without the overhead of messaging

Bandwidth Compressed Waveform and System Design for Wireless and Optical Communications: Theory and Practice

This thesis addresses theoretical and practical challenges of spectrally efficient frequency division multiplexing (SEFDM) systems in both wireless and optical domains. SEFDM improves spectral efficiency relative to the well-known orthogonal frequency division multiplexing (OFDM) by non-orthogonally multiplexing overlapped sub-carriers. However, the deliberate violation of orthogonality results in inter carrier interference (ICI) and associated detection complexity, thus posing many challenges to practical implementations. This thesis will present solutions for these issues. The thesis commences with the fundamentals by presenting the existing challenges of SEFDM, which are subsequently solved by proposed transceivers. An iterative detection (ID) detector iteratively removes self-created ICI. Following that, a hybrid ID together with fixed sphere decoding (FSD) shows an optimised performance/complexity trade-off. A complexity reduced Block-SEFDM can subdivide the signal detection into several blocks. Finally, a coded Turbo-SEFDM is proved to be an efficient technique that is compatible with the existing mobile standards. The thesis also reports the design and development of wireless and optical practical systems. In the optical domain, given the same spectral efficiency, a low-order modulation scheme is proved to have a better bit error rate (BER) performance when replacing a higher order one. In the wireless domain, an experimental testbed utilizing the LTE-Advanced carrier aggregation (CA) with SEFDM is operated in a realistic radio frequency (RF) environment. Experimental results show that 40% higher data rate can be achieved without extra spectrum occupation. Additionally, a new waveform, termed Nyquist-SEFDM, which compresses bandwidth and suppresses out-of-band power leakage is investigated. A 4th generation (4G) and 5th generation (5G) coexistence experiment is followed to verify its feasibility. Furthermore, a 60 GHz SEFDM testbed is designed and built in a point-to-point indoor fiber wireless experiment showing 67% data rate improvement compared to OFDM. Finally, to meet the requirements of future networks, two simplified SEFDM transceivers are designed together with application scenarios and experimental verifications

Doctoral Thesis: Massive MIMO in Real Propagation Environments

Mobile communications are now evolving towards the fifth generation (5G). In the near future, we expect an explosive increase in the number of connected devices, such as phones, tablets, sensors, connected vehicles and so on. Much higher data rates than in today's 4G systems are required. In the 5G visions, better coverage in remote regions is also included, aiming for bringing the current "4 billion unconnected" population into the online world. There is also a great interest in "green communications", for less energy consumption in the ICT (information and communication technology) industry. Massive MIMO is a potential technology to fulfill the requirements and visions. By equipping a base station with a large number, say tens to hundreds, of antennas, many terminals can be served in the same time-frequency resource without severe inter-user interference. Through "aggressive" spatial multiplexing, higher data rates can be achieved without increasing the required spectrum. Processing efforts can be made at the base station side, allowing terminals to have simple and cheap hardware. By exploiting the many spatial degrees of freedom, linear precoding/detection schemes can be used to achieve near-optimal performance. The large number of antennas also brings the advantage of large array gain, resulting in an increase in received signal strength. Better coverage is thus achieved. On the other hand, transmit power from base stations and terminals can be scaled down to pursue energy efficiency. In the last five years, a lot of theoretical studies have been done, showing the extraordinary advantages of massive MIMO. However, the investigations are mainly based on theoretical channels with independent and identically distributed (i.i.d.) Gaussian coefficients, and sometimes assuming unlimited number of antennas. When bringing this new technology from theory to practice, it is important to understand massive MIMO behavior in real propagation channels using practical antenna arrays. Not much has been known about real massive MIMO channels, and whether the claims about massive MIMO still hold there, until the studies in this thesis were done. The thesis study connects the "ideal" world of theory to the "non-ideal" reality. Channel measurements for massive MIMO in the 2.6 GHz band were performed, in different propagation environments and using different types of antenna arrays. Based on obtained real-life channel data, the studies include • channel characterization to identify important massive MIMO properties, • evaluation of propagation conditions in real channels and corresponding massive MIMO performance, • channel modeling for massive MIMO to capture the identified channel properties, and • reduction of massive MIMO hardware complexity through antenna selection. The investigations in the thesis conclude that massive MIMO works efficiently in real propagation environments. The theoretical advantages, as observed in i.i.d. Rayleigh channels, can also be harvested in real channels. Important propagation effects are identified for massive MIMO scenarios, including channel variations over large arrays, multipath-component (MPC) lifetime, and 3D propagation. These propagation properties are modeled and included into the COST 2100 MIMO channel model as an extension for massive MIMO. The study on antenna selection shows that characteristics in real channels allow for significant reductions of massive MIMO complexity without significant performance loss. As one of the world's first research work on massive MIMO behavior in real propagation channels, the studies in this thesis promote massive MIMO as a practical technology for future communication systems