Noncoherent Decision Fusion over Fading Hybrid MACs in Wireless Sensor Networks

Liu, Shoujun; Wang, Kehao; Liu, Kezhong; Chen, Wei

doi:10.3390/s19010120

Cited by 5 publications

(4 citation statements)

References 39 publications

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“…Consequently, for proper information exchange, the transmitter and receiver have to be constantly synchronized into common frequencies. Therefore, it is essential to manage the distributed nodes to the correct channel [8]. There are other challenges to designing the multi-channel protocols for the MAC sub-layer of LLNs including [9]: multi-channel hidden terminal, absent receiver (no listening), broadcast support, delayed channel switch, optimum allocation of channels to nodes, connecting a new node to the network and avoiding network partitioning [10].…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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The classical Internet of things routing and wireless sensor networks can provide more precise monitoring of the covered area due to the higher number of utilized nodes. Because of the limitations in shared transfer media, many nodes in the network are prone to the collision in simultaneous transmissions. Medium access control protocols are usually more practical in networks with low traffic, which are not subjected to external noise from adjacent frequencies. There are preventive, detection and control solutions to congestion management in the network which are all the focus of this study. In the congestion prevention phase, the proposed method chooses the next step of the path using the Fuzzy decision-making system to distribute network traffic via optimal paths. In the congestion detection phase, a dynamic approach to queue management was designed to detect congestion in the least amount of time and prevent the collision. In the congestion control phase, the back-pressure method was used based on the quality of the queue to decrease the probability of linking in the pathway from the pre-congested node. The main goals of this study are to balance energy consumption in network nodes, reducing the rate of lost packets and increasing quality of service in routing. Simulation results proved the proposed Congestion Control Fuzzy Decision Making (CCFDM) method was more capable in improving routing parameters as compared to recent algorithms. INDEX TERMS Internet of Things, wireless sensor network, congestion control, fuzzy decision making, and back-pressure.

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Section: Introductionmentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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“…Communication systems perspective for the ground level WSN is discussed in [106] when dealing with radio challenges over hybrid MACs for decision fusion. The nodes transmit binary non-coherent decisions to the fusion center and the authors analyze and prove several efficient methods that implement the decision fusion rule while accounting for the limited computing available on the nodes.…”

Section: Integrated Uav–wsn System Implementationmentioning

confidence: 99%

A Survey of Collaborative UAV–WSN Systems for Efficient Monitoring

Popescu

Stoican

Stâmâtescu

et al. 2019

Sensors

110

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Integrated systems based on wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) with electric propulsion are emerging as state-of-the-art solutions for large scale monitoring. Main advances stemming both from complex system architectures as well as powerful embedded computing and communication platforms, advanced sensing and networking protocols have been leveraged to prove the viability of this concept. The design of suitable algorithms for data processing, communication and control across previously disparate domains has thus currently become an intensive area of interdisciplinary research. The paper was focused on the collaborative aspects of UAV–WSN systems and the reference papers were analyzed from this point of view, on each functional module. The paper offers a timely review of recent advances in this area of critical interest with focus on a comparative perspective across multiple recent theoretical and applied contributions. A systematic approach is carried out in order to structure a unitary from conceptual design towards key implementation aspects. Focus areas are identified and discussed such as distributed data processing algorithms, hierarchical multi-protocol networking aspects and high level WSN–constrained UAV-control. Application references are highlighted in various domains such as environmental, agriculture, emergency situations and homeland security. Finally, a research agenda is outlined to advance the field towards tangible economic and social impact.

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“…It can hence be interpreted as an example of joint source-channel coding, which is more generally receiving renewed interest for its potential spectral and power efficiency in IoT systems (see, e.g., [40]- [42]). A recent related work is [43] that introduces a novel Bayesian Message Passing technique with joint sourcechannel coding via a non-orthogonal generalization of TBMA; while in [44] a hybrid orthogonal and non-orthogonal multiple access channel based on TBMA was introduced with an optimized decision rule. Based on this review, to the best of 1536-1276 (c) 2020 IEEE.…”

Section: Related Workmentioning

confidence: 99%

Information-Centric Grant-Free Access for IoT Fog Networks: Edge vs. Cloud Detection and Learning

Kassab

Simeone

Popovski

2020

IEEE Trans. Wireless Commun.

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A multi-cell Fog-Radio Access Network (F-RAN) architecture is considered in which Internet of Things (IoT) devices periodically make noisy observations of a Quantity of Interest (QoI) and transmit using grant-free access in the uplink. The devices in each cell are connected to an Edge Node (EN), which may also have a finite-capacity fronthaul link to a central processor. In contrast to conventional informationagnostic protocols, the devices transmit using a Type-Based Multiple Access (TBMA) protocol that is tailored to enable the estimate of the field of correlated QoIs in each cell based on the measurements received from IoT devices. In this paper, this form of information-centric radio access is studied for the first time in a multi-cell F-RAN model with edge or cloud detection. Edge and cloud detection are designed and compared for a multi-cell system. Optimal model-based detectors are introduced and the resulting asymptotic behavior of the probability of error at cloud and edge is derived. Then, for the scenario in which a statistical model is not available, data-driven edge and cloud detectors are discussed and evaluated in numerical results.

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Noncoherent Decision Fusion over Fading Hybrid MACs in Wireless Sensor Networks

Cited by 5 publications

References 39 publications

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

A Survey of Collaborative UAV–WSN Systems for Efficient Monitoring

Information-Centric Grant-Free Access for IoT Fog Networks: Edge vs. Cloud Detection and Learning

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