Robust, Energy-Efficient, and Scalable Indoor Localization with Ultra-Wideband Technology

Ultra-wideband (UWB) technology has been rediscovered in recent years for its potential to provide centimeter-level accuracy in GNSS-denied environments. The large-scale adoption of UWB chipsets in smartphones brings demanding needs on the energy-efficiency, robustness, scalability, and crossdevice compatibility of UWB localization systems. This thesis investigates, characterizes, and proposes several solutions for these pressing concerns. First, we investigate the impact of different UWB device architectures on the energy efficiency, accuracy, and cross-platform compatibility of UWB localization systems. The thesis provides the first comprehensive comparison between the two types of physical interfaces (PHYs) defined in the IEEE 802.15.4 standard: with low and high pulse repetition frequency (LRP and HRP, respectively). In the comparison, we focus not only on the ranging/localization accuracy but also on the energy efficiency of the PHYs. We found that the LRP PHY consumes between 6.4–100 times less energy than the HRP PHY in the evaluated devices. On the other hand, distance measurements acquired with the HRP devices had 1.23–2 times lower standard deviation than those acquired with the LRP devices. Therefore, the HRP PHY might be more suitable for applications with high-accuracy constraints than the LRP PHY. The impact of different UWB PHYs also extends to the application layer. We found that ranging or localization error-mitigation techniques are frequently trained and tested on only one device and would likely not generalize to different platforms. To this end, we identified four challenges in developing platform-independent error-mitigation techniques in UWB localization, which can guide future research in this direction. Besides the cross-platform compatibility, localization error-mitigation techniques raise another concern: most of them rely on extensive data sets for training and testing. Such data sets are difficult and expensive to collect and often representative only of the precise environment they were collected in. We propose a method to detect and mitigate non-line-of-sight (NLOS) measurements that does not require any manually-collected data sets. Instead, the proposed method automatically labels incoming distance measurements based on their distance residuals during the localization process. The proposed detection and mitigation method reduces, on average, the mean and standard deviation of localization errors by 2.2 and 5.8 times, respectively. UWB and Bluetooth Low Energy (BLE) are frequently integrated in localization solutions since they can provide complementary functionalities: BLE is more energy-efficient than UWB but it can provide location estimates with only meter-level accuracy. On the other hand, UWB can localize targets with centimeter-level accuracy albeit with higher energy consumption than BLE. In this thesis, we provide a comprehensive study of the sources of instabilities in received signal strength (RSS) measurements acquired with BLE devices. The study can be used as a starting point for future research into BLE-based ranging techniques, as well as a benchmark for hybrid UWB–BLE localization systems. Finally, we propose a flexible scheduling scheme for time-difference of arrival (TDOA) localization with UWB devices. Unlike in previous approaches, the reference anchor and the order of the responding anchors changes every time slot. The flexible anchor allocation makes the system more robust to NLOS propagation than traditional approaches. In the proposed setup, the user device is a passive listener which localizes itself using messages received from the anchors. Therefore, the system can scale with an unlimited number of devices and can preserve the location privacy of the user. The proposed method is implemented on custom hardware using a commercial UWB chipset. We evaluated the proposed method against the standard TDOA algorithm and range-based localization. In line of sight (LOS), the proposed TDOA method has a localization accuracy similar to the standard TDOA algorithm, down to a 95% localization error of 15.9 cm. In NLOS, the proposed TDOA method outperforms the classic TDOA method in all scenarios, with a reduction of up to 16.4 cm in the localization error.Cotutelle -yhteisväitöskirj

Effective Scheduling Algorithms for Cross-Interference Mitigation in Heterogeneous Wireless Networks

Wireless networks are making life easier, smarter and more convenient. However, the well-known Carrier-sense multiple access with collision avoidance (CSMA/CA) mechanism is powerless when dealing with Cross-Technology Interference (CTI) between Wi-Fi and Low-Rate Wireless Personal Area Network (LR-WPAN), because of asymmetric transmission power, incompatible Clear Channel Assessment (CCA) and different timing parameters. Plenty of studies have shown that WiFi always has a higher priority to access the wireless medium and even block LR-WPAN transmission in the worst case. Our experiments confirm this point and conclude that Wi-Fi can interrupt LR-WPAN severely even block LR-WPAN traffic, while the interference from LR-WPAN to Wi-Fi is negligible. Different from other studies, this thesis presents a novel centralized scheduling mechanism in the time domain to harmonize coexistence of Wi-Fi and LR-WPAN, also refer to as time-slot based scheduling mechanism. The mechanism is achieved by introducing a new command frame, named Access Notification (AN), into the IEEE802.15.4 Medium Access Control (MAC) layer. Based on this mechanism, a static time-slot based scheduling algorithm is designed and evaluated on both real hardware-based system and NS-3 simulator. The result shows the algorithm improves LR-WPAN Packet Loss Rate (PLR) significantly but at the cost of reducing Wi-Fi throughput. In order to maximize performance, based on slot-based congestion indicator (CI) that is proposed and defined to tell whether an allocated time slot is adequate for data transmission or not, we further design an adaptive time-slot based scheduling algorithm. The evaluation shows that the adaptive algorithm covers the shortage of the static algorithm and offers a distinct improvement on LR-WPAN Packet Transmission Rate (PTR)

Embracing interference in wireless systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2013."February 2013." Cataloged from PDF version of thesis.Includes bibliographical references (p. 169-183).The wireless medium is a shared resource. If nearby devices transmit at the same time, their signals interfere, resulting in a collision. In traditional networks, collisions cause the loss of the transmitted information. For this reason, wireless networks have been designed with the assumption that interference is intrinsically harmful and must be avoided. This dissertation takes an alternate approach: Instead of viewing interference as an inherently counterproductive phenomenon that should to be avoided, we design practical systems that transform interference into a harmless, and even a beneficial phenomenon. To achieve this goal, we consider how wireless signals interact when they interfere, and use this understanding in our system designs. Specifically, when interference occurs, the signals get mixed on the wireless medium. By understanding the parameters of this mixing, we can invert the mixing and decode the interfered packets; thus, making interference harmless. Furthermore, we can control this mixing process to create strategic interference that allow decodability at a particular receiver of interest, but prevent decodability at unintended receivers and adversaries. Hence, we can transform interference into a beneficial phenomenon that provides security. Building on this approach, we make four main contributions: We present the first WiFi receiver that can successfully reconstruct the transmitted information in the presence of packet collisions. Next, we introduce a WiFi receiver design that can decode in the presence of high-power cross-technology interference from devices like baby monitors, cordless phones, microwave ovens, or even unknown technologies. We then show how we can harness interference to improve security. In particular, we develop the first system that secures an insecure medical implant without any modification to the implant itself. Finally, we present a solution that establishes secure connections between any two WiFi devices, without having users enter passwords or use pre-shared secret keys.by Shyamnath Gollakota.Ph.D

Demo abstract: Cross-technology TDMA synchronization using energy pattern beacons

When different technologies use the same frequency bands in close proximity, the resulting interference typically results in performance degradation. Coexistence methods exist, but these are often technology specific and require technology specific interference detection methods. To remove the root cause of the performance degradation, devices should be able to negotiate medium access even when using different technologies. To this end, an architecture that allows cross-technology medium access by means of a Time Division Multiple Access (TDMA) scheme was devised. In order to achieve cross-technology synchronization, which is required for the TDMA solution, an energy pattern beacon is transmitted. The use of energy patterns is sufficiently technology agnostic to allow multiple technologies to negotiate between each other. To showcase the feasibility of cross-technology synchronization a demo set-up, using IEEE802.15.4 and IEEE802.11 devices in the w-iLab.t testbed, has been created. It demonstrates that the TDMA solution can successfully divide the medium between the different technologies in order to minimize cross-technology interference

Algorithms and Experimentation for Future Wireless Networks: From Internet-of-Things to Full-Duplex

Future and next-generation wireless networks are driven by the rapidly growing wireless traffic stemming from diverse services and applications, such as the Internet-of-Things (IoT), virtual reality, autonomous vehicles, and smart intersections. Many of these applications require massive connectivity between IoT devices as well as wireless access links with ultra-high bandwidth (Gbps or above) and ultra-low latency (10ms or less). Therefore, realizing the vision of future wireless networks requires significant research efforts across all layers of the network stack. In this thesis, we use a cross-layer approach and focus on several critical components of future wireless networks including IoT systems and full-duplex (FD) wireless, and on experimentation with advanced wireless technologies in the NSF PAWR COSMOS testbed. First, we study tracking and monitoring applications in the IoT and focus on ultra-low-power energy harvesting networks. Based on realistic hardware characteristics, we design and optimize Panda, a centralized probabilistic protocol for maximizing the neighbor discovery rate between energy harvesting nodes under a power budget. Via testbed evaluation using commercial off-the-shelf energy harvesting nodes, we show that Panda outperforms existing protocols by up to 3x in terms of the neighbor discovery rate. We further explore this problem and consider a general throughput maximization problem among a set of heterogeneous energy-constrained ultra-low-power nodes. We analytically identify the theoretical fundamental limits of the rate at which data can be exchanged between these nodes, and design the distributed probabilistic protocol, EconCast, which approaches the maximum throughput in the limiting sense. Performance evaluations of EconCast using both simulations and real-world experiments show that it achieves up to an order of magnitude higher throughput than Panda and other known protocols. We then study FD wireless - simultaneous transmission and reception at the same frequency - a key technology that can significantly improve the data rate and reduce communication latency by employing self-interference cancellation (SIC). In particular, we focus on enabling FD on small-form-factor devices leveraging the technique of frequency-domain equalization (FDE). We design, model, and optimize the FDE-based RF canceller, which can achieve >50dB RF SIC across 20MHz bandwidth, and experimentally show that our prototyped FD radios can achieve a link-level throughput gain of 1.85-1.91x. We also focus on combining FD with phased arrays, employing optimized transmit and receive beamforming, where the spatial degrees of freedom in multi-antenna systems are repurposed to achieve wideband RF SIC. Moving up in the network stack, we study heterogeneous networks with half-duplex and FD users, and develop the novel Hybrid-Greedy Maximum Scheduling (H-GMS) algorithm, which achieves throughput optimality in a distributed manner. Analytical and simulation results show that H-GMS achieves 5-10x better delay performance and improved fairness compared with state-of-the-art approaches. Finally, we described experimentation and measurements in the city-scale COSMOS testbed being deployed in West Harlem, New York City. COSMOS' key building blocks include software-defined radios, millimeter-wave radios, a programmable optical network, and edge cloud, and their convergence will enable researchers to remotely explore emerging technologies in a real world environment. We provide a brief overview of the testbed and focus on experimentation with advanced technologies, including the integrating of open-access FD radios in the testbed and a pilot study on converged optical-wireless x-haul networking for cloud radio access networks (C-RANs). We also present an extensive 28GHz channel measurements in the testbed area, which is a representative dense urban canyon environment, and study the corresponding signal-to-noise ratio (SNR) coverage and achievable data rates. The results of this part helped drive and validate the design of the COSMOS testbed, and can inform further deployment and experimentation in the testbed. In this thesis, we make several theoretical and experimental contributions to ultra-low-power energy harvesting networks and the IoT, and FD wireless. We also contribute to the experimentation and measurements in the COSMOS advanced wireless testbed. We believe that these contributions are essential to connect fundamental theory to practical systems, and ultimately to real-world applications, in future wireless networks