Clock Synchronization of Wireless Sensor Networks
TL;DR: This article illustrates that many of the proposed clock synchronization protocols can be interpreted and their performance assessed using common statistical signal processing methods, and shows that advanced signal processing techniques enable the derivation of optimal clock synchronization algorithms under challenging scenarios.
Abstract: Clock synchronization is a critical component in the operation of wireless sensor networks (WSNs), as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and coordinated sleep wake-up node scheduling mechanisms. Early studies on clock synchronization for WSNs mainly focused on protocol design. However, the clock synchronization problem is inherently related to parameter estimation, and, recently, studies on clock synchronization began to emerge by adopting a statistical signal processing framework. In this article, a survey on the latest advances in the field of clock synchronization of WSNs is provided by following a signal processing viewpoint. This article illustrates that many of the proposed clock synchronization protocols can be interpreted and their performance assessed using common statistical signal processing methods. It is also shown that advanced signal processing techniques enable the derivation of optimal clock synchronization algorithms under challenging scenarios.
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TL;DR: This survey presents various ML-based algorithms for WSNs with their advantages, drawbacks, and parameters effecting the network lifetime, covering the period from 2014–March 2018.
434 citations
TL;DR: A thorough review of the existing standards and industrial protocols is presented and a critical evaluation of potential of these standards and protocols are given along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities.
Abstract: In recent years, industrial wireless sensor networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems, and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment, and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper, a detailed discussion on design objectives, challenges, and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines, and possible hazards in industrial atmosphere are discussed. This paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. This paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs.
211 citations
15 Dec 2011
TL;DR: In this paper, an overview of applications and trends in the field of wireless acoustic sensor networks (WASNs) is given, and the core challenges that need to be tackled.
Abstract: Wireless microphone networks or so-called wireless acoustic sensor networks (WASNs) are a next-generation technology for audio acquisition and processing. As opposed to traditional microphone arrays that sample a sound field only locally, often at large distances from the relevant sound sources, WASNs allow to use many more microphones to cover a large area of interest. However, the design of such WASNs is very challenging, especially for real-time audio acquisition and signal enhancement due to the significant data traffic in the network. There is a need for scalable solutions, both on the signal processing level and on the network-communication level. In this paper, we give an overview of applications and trends in the field of WASNs, and we address the core challenges that need to be tackled. We mainly focus on the signal processing level, and we explain how advances in the area of signal processing can relax the high-demanding constraints on the network layer design. Furthermore, we address the interaction between the application layer and the network layer, and we explain why cross-layer design can be important to improve the performance of WASN applications.
185 citations
01 Jan 2011
TL;DR: An overview of applications and trends in the field of WASNs is given, and it is explained how advances in the area of signal processing can relax the high-demanding constraints on the network layer design.
184 citations
Cites background from "Clock Synchronization of Wireless S..."
...Clock synchronization protocols and algorithms [23] are crucial for the data transmission in the communication layer, but also for multi-microphone audio processing algorithms, since their...
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...In a WASN with dedicated and uniform hardware, synchronization of the sampling rates of ADCs is usually manageable [23] and sometimes even unnecessary if the oscillators are of sufficient quality(4)....
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TL;DR: In this article, an extended Kalman filter (EKF)-based solution is proposed for computationally efficient joint estimation and tracking of the time of arrival (ToA) and direction of arrival of the user nodes (UNs) using uplink reference signals.
Abstract: In this paper, we address the prospects and key enabling technologies for highly efficient and accurate device positioning and tracking in fifth generation (5G) radio access networks. Building on the premises of ultra-dense networks as well as on the adoption of multicarrier waveforms and antenna arrays in the access nodes (ANs), we first formulate extended Kalman filter (EKF)-based solutions for computationally efficient joint estimation and tracking of the time of arrival (ToA) and direction of arrival (DoA) of the user nodes (UNs) using uplink reference signals. Then, a second EKF stage is proposed in order to fuse the individual DoA and ToA estimates from one or several ANs into a UN position estimate. Since all the processing takes place at the network side, the computing complexity and energy consumption at the UN side are kept to a minimum. The cascaded EKFs proposed in this article also take into account the unavoidable relative clock offsets between UNs and ANs, such that reliable clock synchronization of the access-link is obtained as a valuable by-product. The proposed cascaded EKF scheme is then revised and extended to more general and challenging scenarios where not only the UNs have clock offsets against the network time, but also the ANs themselves are not mutually synchronized in time. Finally, comprehensive performance evaluations of the proposed solutions on a realistic 5G network setup, building on the METIS project based outdoor Madrid map model together with complete ray tracing based propagation modeling, are provided. The obtained results clearly demonstrate that by using the developed methods, sub-meter scale positioning and tracking accuracy of moving devices is indeed technically feasible in future 5G radio access networks operating at sub-6 GHz frequencies, despite the realistic assumptions related to clock offsets and potentially even under unsynchronized network elements.
179 citations
References
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TL;DR: The concept of sensor networks which has been made viable by the convergence of micro-electro-mechanical systems technology, wireless communications and digital electronics is described.
17,936 citations
"Clock Synchronization of Wireless S..." refers background in this paper
...The feasibility of WSNs keeps growing rapidly, and WSNs have been regarded as fundamental infrastructures for future ubiquitous communications due to a variety of promising potential applications: monitoring the health status of humans, animals, plants, and the environment; control and instrumentation of industrial machines and home appliances; homeland security; and detection of chemical and biological threats [1], [2]....
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TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
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TL;DR: This chapter discusses the concept of a Random Variable, the meaning of Probability, and the axioms of probability in terms of Markov Chains and Queueing Theory.
Abstract: Part 1 Probability and Random Variables 1 The Meaning of Probability 2 The Axioms of Probability 3 Repeated Trials 4 The Concept of a Random Variable 5 Functions of One Random Variable 6 Two Random Variables 7 Sequences of Random Variables 8 Statistics Part 2 Stochastic Processes 9 General Concepts 10 Random Walk and Other Applications 11 Spectral Representation 12 Spectral Estimation 13 Mean Square Estimation 14 Entropy 15 Markov Chains 16 Markov Processes and Queueing Theory
13,886 citations
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16 Mar 2001
7,058 citations
"Clock Synchronization of Wireless S..." refers background or methods in this paper
...Therefore, the one-to-one function T0 1⁄4 fPNk1⁄41 (U(k) U(1)), U(1), PN k1⁄41 (V(k) V(1)),V(1)g of T is also sufficient for estimating H because the sufficient statistics are unique within one-to-one transformations [32]....
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...Finding the MVUE necessitates the identification of the sufficient statistics and the application of the Rao-Blackwell-Lehmann-Scheff e theorem [32]....
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4,028 citations
"Clock Synchronization of Wireless S..." refers background in this paper
...Probability density function (pdf) models that have been proposed for modeling random delays in wireless networks include Gaussian, exponential, Gamma, Weibull, and log-normal [6]–[8]....
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