Loose Coupling: An Invisible Thread in the History of Technology

Mämmelä, Aarne; Riekki, Jukka; Kiviranta, Markku

doi:10.1109/access.2023.3284685

Cited by 5 publications

(2 citation statements)

References 212 publications

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“…Loosely coupled [22] processing, during the state prediction process, relies solely on the sensor's output data as observation values to update the predicted values. This approach is logically straightforward and practical, allowing for the fusion of multiple sensors to enhance accuracy.…”

Section: Loosely Coupledmentioning

confidence: 99%

Research on Kalman Filter Fusion Navigation Algorithm Assisted by CNN-LSTM Neural Network

Chen,

Zhang,

You

et al. 2024

Applied Sciences

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In response to the challenge of single navigation methods failing to meet the high precision requirements for unmanned aerial vehicle (UAV) navigation in complex environments, a novel algorithm that integrates Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) navigation information is proposed to enhance the positioning accuracy and robustness of UAV navigation systems. First, the fundamental principles of Kalman filtering and its application in navigation are introduced. Second, the basic principles of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks and their applications in the navigation domain are elaborated. Subsequently, an algorithm based on a CNN and LSTM-assisted Kalman filtering fusion navigation is proposed. Finally, the feasibility and effectiveness of the proposed algorithm are validated through experiments. Experimental results demonstrate that the Kalman filtering fusion navigation algorithm assisted by a CNN and LSTM significantly improves the positioning accuracy and robustness of UAV navigation systems in highly interfered complex environments.

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Section: Loosely Coupledmentioning

confidence: 99%

Research on Kalman Filter Fusion Navigation Algorithm Assisted by CNN-LSTM Neural Network

Chen,

Zhang,

You

et al. 2024

Applied Sciences

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“…Our investigations are kept generic and within the broad range of MANETs designed to enable client-to-root connectivity, see Section 2.3. We focus on the management of the dynamic network topology (i.e., the self-organizing [37] movement of the nodes) and do so in a scalable manner. We are restricting ourselves to MANETs which are primarily concerned with connecting clients through a network with a root or data sink [13].…”

Section: Scope Of the Papermentioning

confidence: 99%

Force-Based Self-Organizing MANET/FANET with a UAV Swarm

Saffre,

Hildmann,

Anttonen

2023

Future Internet

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This paper introduces a novel distributed algorithm designed to optimize the deployment of access points within Mobile Ad Hoc Networks (MANETs) for better service quality in infrastructure-less environments. The algorithm operates based on local, independent execution by each network node, thus ensuring a high degree of scalability and adaptability to changing network conditions. The primary focus is to match the spatial distribution of access points with the distribution of client devices while maintaining strong connectivity to the network root. Using autonomous decision-making and choreographed path-planning, this algorithm bridges the gap between demand-responsive network service provision and the maintenance of crucial network connectivity links. The assessment of the performance of this approach is motivated by using numerical results generated by simulations.

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Sustainability in 6G Networks: Vision and Directions

Ahmad,

Mämmelä,

Mowla

et al. 2023

2023 IEEE Conference on Standards for Communications and Networking (CSCN)

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In this paper, we present a vision of sustainable sixth generation (6G) networks. Sustainability has become inevitable due to the strain on natural resources including materials and energy and increase in greenhouse emissions. The energy consumption and the resulting carbon emissions into the environment will be a serious concern. We cannot expect that the present exponential development will continue because of fundamental limits of nature. We first present a brief summary of system-level principles for future networks. Intelligence will be implemented using feedback loops that should be almost isolated from each other implying loose coupling and fast convergence. We next focus on sustainability challenges, including network management, network security, and network hardware. Several approaches and algorithms are highlighted for the goal-directed distributed network management perspectives of 6G sustainability. Resource consumption in network security can be minimized with enabling sleep mode in idle times, moving towards software-based security functions instead of hardware-based systems, and rethinking of encryption techniques in view of sustainability through code optimization and load fragmentation. High-efficiency antennas can incorporate biodegradable materials to build sustainable network hardware. We also introduce a new research thrust for total control of electromagnetic waves by the modular metasurface antennas making sustainable 6G radio coverage possible in various communication scenarios, e.g., small cell base stations and holographic radio coverage areas.

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Loose Coupling: An Invisible Thread in the History of Technology

Cited by 5 publications

References 212 publications

Research on Kalman Filter Fusion Navigation Algorithm Assisted by CNN-LSTM Neural Network

Research on Kalman Filter Fusion Navigation Algorithm Assisted by CNN-LSTM Neural Network

Force-Based Self-Organizing MANET/FANET with a UAV Swarm

Sustainability in 6G Networks: Vision and Directions

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