Performance evaluation of non-prefiltering vs. time reversal prefiltering in distributed and uncoordinated IR-UWB ad-hoc networks

Time Reversal (TR) is a prefiltering scheme mostly analyzed in the context of centralized and synchronous IR-UWB networks, in order to leverage the trade-off between communication performance and device complexity, in particular in presence of multiuser interference. Several strong assumptions have been typically adopted in the analysis of TR, such as the absence of Inter-Symbol / Inter-Frame Interference (ISI/IFI) and multipath dispersion due to complex signal propagation. This work has the main goal of comparing the performance of TR-based systems with traditional non-prefiltered schemes, in the novel context of a distributed and uncoordinated IR-UWB network, under more realistic assumptions including the presence of ISI/IFI and multipath dispersion. Results show that, lack of power control and imperfect channel knowledge affect the performance of both non-prefiltered and TR systems; in these conditions, TR prefiltering still guarantees a performance improvement in sparse/low-loaded and overloaded network scenarios, while the opposite is true for less extreme scenarios, calling for the developement of an adaptive scheme that enables/disables TR prefiltering depending on network conditions

Experimental Investigation Of Ultrawideband Wireless Systems: Waveform Generation, Propagation Estimation, And Dispersion Compensation

Ultrawideband (UWB) is an emerging technology for the future high-speed wireless communication systems. Although this technology offers several unique advantages like robustness to fading, large channel capacity and strong anti-jamming ability, there are a number of practical challenges which are topics of current research. One key challenge is the increased multipath dispersion which results because of the fine temporal resolution. The received response consists of different components, which have certain delays and attenuations due to the paths they took in their propagation from the transmitter to the receiver. Although such challenges have been investigated to some extent, they have not been fully explored in connection with sophisticated transmit beamforming techniques in realistic multipath environments. The work presented here spans three main aspects of UWB systems including waveform generation, propagation estimation, and dispersion compensation. We assess the accuracy of the measured impulse responses extracted from the spread spectrum channel sounding over a frequency band spanning 2-12 GHz. Based on the measured responses, different transmit beamforming techniques are investigated to achieve high-speed data transmission in rich multipath channels. We extend our work to multiple antenna systems and implement the first experimental test-bed to investigate practical challenges such as imperfect channel estimation or coherency between the multiple transmitters over the full UWB band. Finally, we introduce a new microwave photonic arbitrary waveform generation technique to demonstrate the first optical-wireless transmitter system for both characterizing channel dispersion and generating predistorted waveforms to achieve spatio-temporal focusing through the multipath channels

Forward Error Correction in Memoryless Optical Modulation

The unprecedented growth in demand for digital media has led to an all-time high in society’s demand for information. This demand will in all likelihood continue to grow as technology such as 3D television service, on-demand video and peer-to-peer networking continue to become more common place. The large amount of information required is currently transmitted optically using a wavelength division multiplexing (WDM) network structure. The need to increase the capacity of the existing WDM network infrastructure efficiently is essential to continue to provide new high bandwidth services to end-users, while at the same time minimizing network providers’ costs. In WDM systems the key to reducing the cost per transported information bit is to effectively share all optical components. These components must operate within the same wavelength limited window; therefore it is necessary to place the WDM channels as close together as possible. At the same time, the correct modulation format must be selected in order to create flexible, cost-effective, high-capacity optical networks. This thesis presents a detailed comparison of Differential Quadrature Phase Shift Keying (DQPSK) to other modulation formats. This comparison is implemented through a series of simulations in which the bit error rate of various modulation formats are compared both with and without the presence of forward error correction techniques. Based off of these simulation results, the top performing modulation formats are placed into a multiplexed simulation to assess their overall robustness in the face of multiple filtering impairments

Phase estimation receiver for full-field detection: a novel receiver structure for electronic dispersion compensation of metropolitan area networks

The development of ultra high speed (~20 Gsamples/s) analogue to digital converters (ADCs), and the delayed deployment of 40 Gbit/s transmission due to the economic downturn, has stimulated the investigation of digital signal processing (DSP) techniques for compensation of optical transmission impairments. In the future, DSP will offer an entire suite of tools to compensate for optical impairments and facilitate the use of advanced modulation formats. Chromatic dispersion is a very significant impairment for high speed optical transmission. This thesis investigates a novel electronic method of dispersion compensation which allows for cost-effective accurate detection of the amplitude and phase of the optical field into the radio frequency domain. The first electronic dispersion compensation (EDC) schemes accessed only the amplitude information using square law detection and achieved an increase in transmission distances. This thesis presents a method by using a frequency sensitive filter to estimate the phase of the received optical field and, in conjunction with the amplitude information, the entire field can be digitised using ADCs. This allows DSP technologies to take the next step in optical communications without requiring complex coherent detection. This is of particular of interest in metropolitan area networks. The full-field receiver investigated requires only an additional asymmetrical Mach-Zehnder interferometer and balanced photodiode to achieve a 50% increase in EDC reach compared to amplitude only detection

COMPRESSIVE QUANTIZATION FOR SCALABLE CLOUD RADIO ACCESS NETWORKS

With the proliferation of new mobile devices and applications, the demand for ubiquitous wireless services has increased dramatically in recent years. The explosive growth in the wireless traffic requires the wireless networks to be scalable so that they can be efficiently extended to meet the wireless communication demands. In a wireless network, the interference power typically grows with the number of devices without necessary coordination among them. On the other hand, large scale coordination is always difficult due to the low-bandwidth and high-latency interfaces between access points (APs) in traditional wireless networks. To address this challenge, cloud radio access network (C-RAN) has been proposed, where a pool of base band units (BBUs) are connected to the distributed remote radio heads (RRHs) via high bandwidth and low latency links (i.e., the front-haul) and are responsible for all the baseband processing. But the insufficient front-haul link capacity may limit the scale of C-RAN and prevent it from fully utilizing the benefits made possible by the centralized baseband processing. As a result, the front-haul link capacity becomes a bottleneck in the scalability of C-RAN. In this dissertation, we explore the scalable C-RAN in the effort of tackling this challenge. In the first aspect of this dissertation, we investigate the scalability issues in the existing wireless networks and propose a novel time-reversal (TR) based scalable wireless network in which the interference power is naturally mitigated by the focusing effects of TR communications without coordination among APs or terminal devices (TDs). Due to this nice feature, it is shown that the system can be easily extended to serve more TDs. Motivated by the nice properties of TR communications in providing scalable wireless networking solutions, in the second aspect of this dissertation, we apply the TR based communications to the C-RAN and discover the TR tunneling effects which alleviate the traffic load in the front-haul links caused by the increment of TDs. We further design waveforming schemes to optimize the downlink and uplink transmissions in the TR based C-RAN, which are shown to improve the downlink and uplink transmission accuracies. Consequently, the traffic load in the front-haul links is further alleviated by the reducing re-transmissions caused by transmission errors. Moreover, inspired by the TR-based C-RAN, we propose the compressive quantization scheme which applies to the uplink of multi-antenna C-RAN so that more antennas can be utilized with the limited front-haul capacity, which provide rich spatial diversity such that the massive TDs can be served more efficiently

Radio Analytics for Indoor Monitoring and Human Recognition

In the era of Internet of Things (IoT), researchers have been developing new technologies and intelligent systems to answer the question of who, what, when, where, and how of things happening in the environment. Among the various techniques that measure what is happening in the surroundings, wireless sensing stands out because of its ubiquity and prevalence. On one hand, different indoor activities bring distinctive perturbations to wireless radio propagation. On the other hand, thanks to the nature of multipath, indoor environmental information is recorded and embedded in the wireless channel state information (CSI). Hence, by deploying wireless transceivers to sense the radio propagation environment and analyzing the CSI, one can extend human senses and enrich her/his insight into surrounding environments and activities. By leveraging the natural multipath propagation of electromagnetic (EM) waves, radio analytics is proposed as a promising technology that deciphers radio propagation characteristics and reveals rich environmental information surrounding us. As one approach of radio analytics, time-reversal (TR) technique exploits the information of large degrees-of-freedom delivered by CSI and provides a high-resolution spatial-temporal resonance, by treating each multipath component in a wireless channel as a distributed virtual antenna. The TR spatial-temporal resonance is indeed a resonance of EM field in response to the propagation environment, and it changes whenever the propagation environment changes. Inspired by the principle of TR and motivated by the development of IoT, in this dissertation, we propose several radio analytic systems that leverage multipath information to realize IoT applications of recognizing different events and identifying people in an indoor environment. In the first part, we design three indoor monitoring systems that analyze different event-determined features extracted from either a single CSI sample or a CSI time series. The first proposed indoor monitoring system distinguishes between different indoor events by matching the instantaneous CSI to a multipath profile calibrated in a training database whose similarity is quantified by the time-reversal resonance strength (TRRS). Later on, we derive the statistics of TRRS, and we propose a new TR based indoor monitoring system that differentiates between different indoor events based on the statistical behavior of TRRS. Unlike the previous two indoor monitoring systems which treats each CSI as an independent feature, we propose the third indoor monitoring system by exploiting the temporal information embedded in the CSI time series as an additional feature to comprehensively understand indoor events. Results of extensive experiments demonstrate the proposed systems as promising solutions to future indoor monitoring IoT applications. In the second part of this dissertation, we propose the concept of human radio biometrics and design a through-the-wall human identification system that is implemented on commercial WiFi devices. As a human present in an indoor environment, the radio waves propagate around will interact with the human body through reflection and scattering. We define human radio biometrics as the attenuation and alteration of wireless signals brought by human. We achieve an accurate through-the-wall human recognition by utilizing the fact that the radio biometrics are uniquely determined by the biological characteristics of each human. Through extensive experiments, we validate the existence of radio biometrics and evaluate the accuracy of the proposed human identification system. Unlike conventional approaches for biometric recognition, the proposed radio biometrics system can identify human through a wall and supports commercial WiFi infrastructure, thus illustrating its potential for human recognition IoT applications

Resource allocation in future green wireless networks : applications and challenges

Over the past few years, green radio communication has been an emerging topic since the footprint from the Information and Communication Technologies (ICT) is predicted to increase 7.3% annually and then exceed 14% of the global footprint by 2040. Moreover, the explosive progress of ICT, e.g., the fifth generation (5G) networks, has resulted in expectations of achieving 10-fold longer device battery lifetime, and 1000-fold higher global mobile data traffic over the fourth generation (4G) networks. Therefore, the demands for increasing the data rate and the lifetime while reducing the footprint in the next-generation wireless networks call for more efficient utilization of energy and other resources. To overcome this challenge, the concepts of small-cell, energy harvesting, and wireless information and power transfer networks can be evaluated as promising solutions for re-greening the world. In this dissertation, the technical contributions in terms of saving economical cost, protecting the environment, and guaranteeing human health are provided. More specifically, novel communication scenarios are proposed to minimize energy consumption and hence save economic costs. Further, energy harvesting (EH) techniques are applied to exploit available green resources in order to reduce carbon footprint and then protect the environment. In locations where implemented user devices might not harvest energy directly from natural resources, base stations could harvest-and-store green energy and then use such energy to power the devices wirelessly. However, wireless power transfer (WPT) techniques should be used in a wise manner to avoid electromagnetic pollution and then guarantee human health. To achieve all these aspects simultaneously, this thesis proposes promising schemes to optimally manage and allocate resources in future networks. Given this direction, in the first part, Chapter 2 mainly studies a transmission power minimization scheme for a two-tier heterogeneous network (HetNet) over frequency selective fading channels. In addition, the HetNet backhaul connection is unable to support a sufficient throughput for signaling an information exchange between two tiers. A novel idea is introduced in which the time reversal (TR) beamforming technique is used at a femtocell while zero-forcing-based beamforming is deployed at a macrocell. Thus, a downlink power minimizationscheme is proposed, and optimal closed-form solutions are provided. In the second part, Chapters 3, 4, and 5 concentrate on EH and wireless information and power transfer (WIPT) using RF signals. More specifically, Chapter 3 presents an overview of the recent progress in green radio communications and discusses potential technologies for some emerging topics on the platforms of EH and WPT. Chapter 4 develops a new integrated information and energy receiver architecture based on the direct use of alternating current (AC) for computation. It is shown that the proposed approach enhances not only the computational ability but also the energy efficiency over the conventional one. Furthermore, Chapter 5 proposes a novel resource allocation scheme in simultaneous wireless information and power transfer (SWIPT) networks where three crucial issues: power-efficient improvement, user-fairness guarantee, and non-ideal channel reciprocity effect mitigation, are jointly addressed. Hence, novel methods to derive optimal and suboptimal solutions are provided. In the third part, Chapters 6, 7, and 8 focus on simultaneous lightwave information and power transfer (SLIPT) for indoor applications, as a complementary technology to RF SWIPT. In this research, Chapter 6 investigates a hybrid RF/visible light communication (VLC) ultrasmall cell network where optical transmitters deliver information and power using the visible light, whereas an RF access point works as a complementary power transfer system. Thus, a novel resource allocation scheme exploiting RF and visible light for power transfer is devised. Chapter 7 proposes the use of lightwave power transfer to enable future sustainable Federated Learning (FL)-based wireless networks. FL is a new data privacy protection technique for training shared machine learning models in a distributed approach. However, the involvement of energy-constrained mobile devices in the construction of the shared learning models may significantly reduce their lifetime. The proposed approach can support the FL-based wireless network to overcome the issue of limited energy at mobile devices. Chapter 8 introduces a novel framework for collaborative RF and lightwave power transfer for wireless communication networks. The constraints on the transmission power set by safety regulations result in significant challenges to enhance the power transfer performance. Thus, the study of technologies complementary to conventional RF SWIPT is essential. To cope with this isue, this chapter proposes a novel collaborative RF and lightwave power transfer technology for next-generation wireless networks