AoA-aware Probabilistic Indoor Location Fingerprinting using Channel State Information

With expeditious development of wireless communications, location fingerprinting (LF) has nurtured considerable indoor location based services (ILBSs) in the field of Internet of Things (IoT). For most pattern-matching based LF solutions, previous works either appeal to the simple received signal strength (RSS), which suffers from dramatic performance degradation due to sophisticated environmental dynamics, or rely on the fine-grained physical layer channel state information (CSI), whose intricate structure leads to an increased computational complexity. Meanwhile, the harsh indoor environment can also breed similar radio signatures among certain predefined reference points (RPs), which may be randomly distributed in the area of interest, thus mightily tampering the location mapping accuracy. To work out these dilemmas, during the offline site survey, we first adopt autoregressive (AR) modeling entropy of CSI amplitude as location fingerprint, which shares the structural simplicity of RSS while reserving the most location-specific statistical channel information. Moreover, an additional angle of arrival (AoA) fingerprint can be accurately retrieved from CSI phase through an enhanced subspace based algorithm, which serves to further eliminate the error-prone RP candidates. In the online phase, by exploiting both CSI amplitude and phase information, a novel bivariate kernel regression scheme is proposed to precisely infer the target's location. Results from extensive indoor experiments validate the superior localization performance of our proposed system over previous approaches

Visible Light Communication (VLC)

Visible light communication (VLC) using light-emitting diodes (LEDs) or laser diodes (LDs) has been envisioned as one of the key enabling technologies for 6G and Internet of Things (IoT) systems, owing to its appealing advantages, including abundant and unregulated spectrum resources, no electromagnetic interference (EMI) radiation and high security. However, despite its many advantages, VLC faces several technical challenges, such as the limited bandwidth and severe nonlinearity of opto-electronic devices, link blockage and user mobility. Therefore, significant efforts are needed from the global VLC community to develop VLC technology further. This Special Issue, “Visible Light Communication (VLC)”, provides an opportunity for global researchers to share their new ideas and cutting-edge techniques to address the above-mentioned challenges. The 16 papers published in this Special Issue represent the fascinating progress of VLC in various contexts, including general indoor and underwater scenarios, and the emerging application of machine learning/artificial intelligence (ML/AI) techniques in VLC

Algorithms for channel impairment mitigation in broadband wireless communications

Ph.DDOCTOR OF PHILOSOPH

Energy Efficiency in Communications and Networks

The topic of "Energy Efficiency in Communications and Networks" attracts growing attention due to economical and environmental reasons. The amount of power consumed by information and communication technologies (ICT) is rapidly increasing, as well as the energy bill of service providers. According to a number of studies, ICT alone is responsible for a percentage which varies from 2% to 10% of the world power consumption. Thus, driving rising cost and sustainability concerns about the energy footprint of the IT infrastructure. Energy-efficiency is an aspect that until recently was only considered for battery driven devices. Today we see energy-efficiency becoming a pervasive issue that will need to be considered in all technology areas from device technology to systems management. This book is seeking to provide a compilation of novel research contributions on hardware design, architectures, protocols and algorithms that will improve the energy efficiency of communication devices and networks and lead to a more energy proportional technology infrastructure

CELLULAR-ENABLED MACHINE TYPE COMMUNICATIONS: RECENT TECHNOLOGIES AND COGNITIVE RADIO APPROACHES

The scarcity of bandwidth has always been the main obstacle for providing reliable high data-rate wireless links, which are in great demand to accommodate nowadays and immediate future wireless applications. In addition, recent reports have showed inefficient usage and under-utilization of the available bandwidth. Cognitive radio (CR) has recently emerged as a promising solution to enhance the spectrum utilization, where it offers the ability for unlicensed users to access the licensed spectrum opportunistically. By allowing opportunistic spectrum access which is the main concept for the interweave network model, the overall spectrum utilization can be improved. This requires cognitive radio networks (CRNs) to consider the spectrum sensing and monitoring as an essential enabling process for the interweave network model. Machine-to-machine (M2M) communication, which is the basic enabler for the Internet-of-Things (IoT), has emerged to be a key element in future networks. Machines are expected to communicate with each other exchanging information and data without human intervention. The ultimate objective of M2M communications is to construct comprehensive connections among all machines distributed over an extensive coverage area. Due to the radical change in the number of users, the network has to carefully utilize the available resources in order to maintain reasonable quality-of-service (QoS). Generally, one of the most important resources in wireless communications is the frequency spectrum. To utilize the frequency spectrum in IoT environment, it can be argued that cognitive radio concept is a possible solution from the cost and performance perspectives. Thus, supporting numerous number of machines is possible by employing dual-mode base stations which can apply cognitive radio concept in addition to the legacy licensed frequency assignment. In this thesis, a detailed review of the state of the art related to the application of spectrum sensing in CR communications is considered. We present the latest advances related to the implementation of the legacy spectrum sensing approaches. We also address the implementation challenges for cognitive radios in the direction of spectrum sensing and monitoring. We propose a novel algorithm to solve the reduced throughput issue due to the scheduled spectrum sensing and monitoring. Further, two new architectures are considered to significantly reduce the power consumption required by the CR to enable wideband sensing. Both systems rely on the 1-bit quantization at the receiver side. The system performance is analytically investigated and simulated. Also, complexity and power consumption are investigated and studied. Furthermore, we address the challenges that are expected from the next generation M2M network as an integral part of the future IoT. This mainly includes the design of low-power low-cost machine with reduced bandwidth. The trade-off between cost, feasibility, and performance are also discussed. Because of the relaxation of the frequency and spatial diversities, in addition, to enabling the extended coverage mode, initial synchronization and cell search have new challenges for cellular-enabled M2M systems. We study conventional solutions with their pros and cons including timing acquisition, cell detection, and frequency offset estimation algorithms. We provide a technique to enhance the performance in the presence of the harsh detection environment for LTE-based machines. Furthermore, we present a frequency tracking algorithm for cellular M2M systems that utilizes the new repetitive feature of the broadcast channel symbols in next generation Long Term Evolution (LTE) systems. In the direction of narrowband IoT support, we propose a cell search and initial synchronization algorithm that utilizes the new set of narrowband synchronization signals. The proposed algorithms have been simulated at very low signal to noise ratios and in different fading environments

High-performance signal acquisition algorithms for wireless communications receivers

Due to the uncertainties introduced by the propagation channel, and RF and mixed signal circuits imperfections, digital communication receivers require efficient and robust signal acquisition algorithms for timing and carrier recovery, and interfer- ence rejection. The main theme of this work is the development of efficient and robust signal synchronization and interference rejection schemes for narrowband, wideband and ultra wideband communications systems. A series of novel signal acquisition schemes together with their performance analysis and comparisons with existing state-of-the- art results are introduced. The design effort is first focused on narrowband systems, and then on wideband and ultra wideband systems. For single carrier modulated narrowband systems, it is found that conventional timing recovery schemes present low efficiency, e.g., certain feedback timing recov- ery schemes exhibit the so-called hang-up phenomenon, while another class of blind feedforward timing recovery schemes presents large self-noise. Based on a general re- search framework, we propose new anti-hangup algorithms and prefiltering techniques to speed up the feedback timing recovery and reduce the self-noise of feedforward tim- ing estimators, respectively. Orthogonal frequency division multiplexing (OFDM) technique is well suited for wideband wireless systems. However, OFDM receivers require high performance car-rier and timing synchronization. A new coarse synchronization scheme is proposed for efficient carrier frequency offset and timing acquisition. Also, a novel highly accurate decision-directed algorithm is proposed to track and compensate the residual phase and timing errors after the coarse synchronization step. Both theoretical analysis and computer simulations indicate that the proposed algorithms greatly improve the performance of OFDM receivers. The results of an in-depth study show that a narrowband interference (NBI) could cause serious performance loss in multiband OFDMbased ultra-wideband (UWB) sys- tems. A novel NBI mitigation scheme, based on a digital NBI detector and adaptive analog notch filter bank, is proposed to reduce the effects of NBI in UWB systems. Simulation results show that the proposed NBI mitigation scheme improves signifi- cantly the performance of a standard UWB receiver (this improvement manifests as a signal-to-noise ratio (SNR) gain of 9 dB)

On CSI and Passive WiFi Radar for Opportunistic Physical Activity Recognition

The use of Wi-Fi signals for human sensing has gained significant interest over the past decade. Such techniques provide affordable and reliable solutions for healthcare-focused events such as vital sign detection, prevention of falls and long-term monitoring of chronic diseases, among others. Currently, there are two major approaches for Wi-Fi sensing: (1) passive Wi-Fi radar (PWR) which uses well established techniques from bistatic radar, and channel state information (CSI) based wireless sensing (SENS) which exploits human-induced variations in the communication channel between a pair of transmitter and receiver. However, there has not been a comprehensive study to understand and compare the differences in terms of effectiveness and limitations in real-world deployment. In this paper, we present the fundamentals of the two systems with associated methodologies and signal processing. A thorough measurement campaign was carried out to evaluate the human activity detection performance of both systems. Experimental results show that SENS system provides better detection performance in a line-of-sight (LoS) condition, whereas PWR system performs better in a non-LoS (NLoS) setting. Furthermore, based on our findings, we recommend that future Wi-Fi sensing applications should leverage the advantages from both PWR and SENS systems

Multi-standard context-aware cognitive radio : sensing and classification mechanisms

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