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Found 12 papers, 1 papers with code
Improved Soft-k-Means Clustering Algorithm for Balancing Energy Consumption in Wireless Sensor Networks
Energy load balancing is an essential issue in designing wireless sensor networks (WSNs).
UAV Trajectory Planning for AoI-Minimal Data Collection in UAV-Aided IoT Networks by Transformer
Maintaining freshness of data collection in Internet-of-Things (IoT) networks has attracted increasing attention.
A Tutorial on Chirp Spread Spectrum for LoRaWAN: Basics and Key Advances
Chirps spread spectrum (CSS) modulation is the heart of long-range (LoRa) modulation used in the context of long-range wide area network (LoRaWAN) in internet of things (IoT) scenarios.
Sample-Driven Federated Learning for Energy-Efficient and Real-Time IoT Sensing
In particular, We first formulate an optimization problem that harnesses the sampling process to concurrently reduce overfitting while maximizing accuracy.
D2D-aided LoRaWAN LR-FHSS in Direct-to-Satellite IoT Networks
In this paper, we present a device-to-device (D2D) transmission scheme for aiding long-range frequency hopping spread spectrum (LR-FHSS) LoRaWAN protocol with application in direct-to-satellite IoT networks.
Low Complexity Classification Approach for Faster-than-Nyquist (FTN) Signalling Detection
In particular, we view the FTN signaling detection problem as a classification task, where the received signal is considered as an unlabeled class sample that belongs to a set of all possible classes samples.
Deep Learning-based List Sphere Decoding for Faster-than-Nyquist (FTN) Signaling Detection
At the testing phase, if the hypersphere has more than $N_{\text{L}}$ lattice points, we keep the $N_{\text{L}}$ closest points to the point corresponding to the received FTN signal; however, if the hypersphere has less than $N_{\text{L}}$ points, we increase the approximate initial radius by a value that depends on the standard deviation of the distribution of the output radii from the training phase.
Joint Cluster Head Selection and Trajectory Planning in UAV-Aided IoT Networks by Reinforcement Learning with Sequential Model
Employing unmanned aerial vehicles (UAVs) has attracted growing interests and emerged as the state-of-the-art technology for data collection in Internet-of-Things (IoT) networks.
Concurrent Transmission and Multiuser Detection of LoRa Signals
In the second stage, we determine the EDs that transmit the specific chirps identified from the first stage.
UAV Trajectory Planning in Wireless Sensor Networks for Energy Consumption Minimization by Deep Reinforcement Learning
Toward this end, we formulate the energy consumption minimization problem as a constrained combinatorial optimization problem by jointly selecting CHs from nodes within clusters and planning the UAV's visiting order to the selected CHs.
Performance Improvement of LoRa Modulation with Signal Combining and Semi-Coherent Detection
In this paper, we investigate performance improvements of low-power long-range (LoRa) modulation when a gateway is equipped with multiple antennas.
Low Complexity Soft-Output Faster-than-Nyquist Detector Based on Semidefinite Relaxation
The effectiveness of the proposed soSDR algorithm is evaluated using polar codes with successive cancellation decoding (SCD) through simulations, and its performance is compared against the state-of-the-art techniques from the literature.
