Cooperative Synchronization in Wireless Networks

Synchronization is a key functionality in wireless network, enabling a wide variety of services. We consider a Bayesian inference framework whereby network nodes can achieve phase and skew synchronization in a fully distributed way. In particular, under the assumption of Gaussian measurement noise, we derive two message passing methods (belief propagation and mean field), analyze their convergence behavior, and perform a qualitative and quantitative comparison with a number of competing algorithms. We also show that both methods can be applied in networks with and without master nodes. Our performance results are complemented by, and compared with, the relevant Bayesian Cram\'er-Rao bounds

Cooperative Simultaneous Localization and Synchronization in Mobile Agent Networks

Cooperative localization in agent networks based on interagent time-of-flight measurements is closely related to synchronization. To leverage this relation, we propose a Bayesian factor graph framework for cooperative simultaneous localization and synchronization (CoSLAS). This framework is suited to mobile agents and time-varying local clock parameters. Building on the CoSLAS factor graph, we develop a distributed (decentralized) belief propagation algorithm for CoSLAS in the practically important case of an affine clock model and asymmetric time stamping. Our algorithm allows for real-time operation and is suitable for a time-varying network connectivity. To achieve high accuracy at reduced complexity and communication cost, the algorithm combines particle implementations with parametric message representations and takes advantage of a conditional independence property. Simulation results demonstrate the good performance of the proposed algorithm in a challenging scenario with time-varying network connectivity.Comment: 13 pages, 6 figures, 3 tables; manuscript submitted to IEEE Transaction on Signal Processin

Synchronization and localization in wireless networks

While intended for both theoreticians and practitioners, this monograph is written to be accessible to novices while covering state-of-the-art topics of interest to advanced researchers of localization and synchronization systems

Synchronization and Localization in Wireless Networks

This review addresses the role of synchronization in the radio localization problem, and provides a comprehensive overview of recent developments suitable for current and future practical implementations. The material is intended for both, theoreticians and practitioners, and is written to be accessible to novices, while covering state-of-the-art topics, of interest to advanced researchers of localization and synchronization systems. Several widely-used radio localization systems, such as GPS and cellular localization, rely on time-of-flight measurements of data-bearing signals to determine inter-radio distances. For such measurements to be meaningful, accurate synchronization is required. While existing systems use a highly synchronous infrastructure, such as GPS where satellites are equipped with atomic clocks or cellular localization where base stations are GPS synchronized, most other wireless networks do not have an sufficiently accurate common notion of time across the nodes. Synchronization, either at link or network level, thus has a principal role in localization systems. This role is expected to become more important in view of recent trends in high-precision and distributed localization, as well as future communication standards, such as 5G indoor localization when access points can not be externally synchronized. Since synchronization is generally treated separately from localization, there is a need to harmonize these two fundamental problems, especially in the decentralized network context. In this monograph, we revisit the role of synchronization in radio localization and provide an exposition of its relation to the general network localization problem. After an introduction of basic concepts, models, and network inference methods, we contrast two-step approaches with single-step (simultaneous) synchronization and localization. These approaches are discussed in terms of their methodology and fundamental limitations. Our focus is on techniques that consider practical relevant clock, delay, and measurement models in order to guide the reader from physical observations to statistical estimation techniques. The presented methods apply to networks with asynchronous localization infrastructure and/or to cooperative ad-hoc networks

Cooperative Simultaneous Localization and Synchronization: A Distributed Hybrid Message Passing Algorithm

Cooperative sensor self-localization (CSL) in wireless networks usually requires the nodes to be equipped with specific ranging hardware including ultra-wideband or ultrasonic distance sensors. Such designs are not suitable for application in low-cost, low-power sensor networks. Here, we demonstrate how low-cost, low-power, asynchronous sensor nodes can be used to perform CSL (and, simultaneously, distributed synchronization) by means of time-stamped communication without additional ranging hardware. Our method combines a belief propagation message passing algorithm for cooperative simultaneous localization and synchronization (CoSLAS) with a MAC-layer time stamping scheme.We validate the models underlying the CoSLAS algorithm by means of measurements, and we demonstrate that the localization accuracy achieved by our hardware implementation is far better than that corresponding to the time resolution and measurement errors of the hardware

DL-Based Physical Tamper Attack Detection in OFDM Systems with Multiple Receiver Antennas: A Performance–Complexity Trade-Off

This paper proposes two deep-learning (DL)-based approaches to a physical tamper attack detection problem in orthogonal frequency division multiplexing (OFDM) systems with multiple receiver antennas based on channel state information (CSI) estimates. The physical tamper attack is considered as the unwanted change of antenna orientation at the transmitter or receiver. Approaching the tamper attack scenario as a semi-supervised anomaly detection problem, the algorithms are trained solely based on tamper-attack-free measurements, while operating in general scenarios that may include physical tamper attacks. Two major challenges in the algorithm design are environmental changes, e.g., moving persons, that are not due to an attack and evaluating the trade-off between detection performance and complexity. Our experimental results from two different environments, comprising an office and a hall, show the proper detection performances of the proposed methods with different complexity levels. The optimal proposed method achieves a 93.32% true positive rate and a 10% false positive rate with a suitable level of complexity