Abstract: Embodiments of the present disclosure disclose a method and a system for tracking the position of the one or more moving objects. The method includes collecting GNSS measurement data of satellite signals transmitted from multiple satellites. The method further includes extracting values of a plurality of features from the GNSS measurement data. The method includes mapping the extracted values of the plurality of features to a source domain. The method includes classifying the mapped transformed plurality of features using a neural network. The neural network is trained over simulated data sampled from a source domain. The method includes identifying multipath measurements of the GNSS measurement data based on classification of the corresponding mapped transformed plurality of features. The method includes tracking the position of the one or more moving objects by processing identification of GNSS measurement data affected by multipath.

Abstract: A computer-executed method is provided for IEEE 802.15.4 devices based on a suspendable carrier-sense multiple access with collision avoidance (CSMA/CA) control program and standard CSMA/CA control program for an IEEE 802.15.4 network composing of IEEE 802.15.4 devices. The computer-executed method is provided on an IEEE 802.15.4 device, and causes a processor of the IEEE 802.15.4 device to perform steps that include determining the permission of backoff suspension and the intention of IEEE 802.15.4 device to perform backoff suspension, selecting the suspendable CSMA/CA control program if the backoff suspension is permitted and IEEE 802.15.4 device intends to perform backoff suspension.

Abstract: A computer-executed method is provided for IEEE 802.15.4 devices based on a suspendable carrier-sense multiple access with collision avoidance (CSMA/CA) control program and standard CSMA/CA control program for an IEEE 802.15.4 network composing of IEEE 802.15.4 devices. The computer-executed method is provided on an IEEE 802.15.4 device, and causes a processor of the IEEE 802.15.4 device to perform steps that include determining the permission of backoff suspension and the intention of IEEE 802.15.4 device to perform backoff suspension, selecting the suspendable CSMA/CA control program if the backoff suspension is permitted and IEEE 802.15.4 device intends to perform backoff suspension.

Abstract: A method for a target image reconstruction is provided. The method includes emitting stepped frequency waveforms having different constant frequencies at different periods of time, modulating the stepped frequency waveforms into frequency ranges each having a first frequency and a second frequency, wherein each of the stepped frequency waveforms are increased from the first frequency to the second frequency based on a range function, wherein the modulated stepped frequency waveforms are arranged with some sparsity factor.

Abstract: A computer-executed method is provided for IEEE 802.15.4 devices based on a suspendable carrier-sense multiple access with collision avoidance (CSMA/CA) control program and standard CSMA/CA control program for an IEEE 802.15.4 network composing of IEEE 802.15.4 devices. The computer-executed method is provided on an IEEE 802.15.4 device, and causes a processor of the IEEE 802.15.4 device to perform steps that include determining the permission of backoff suspension and the intention of IEEE 802.15.4 device to perform backoff suspension, selecting the suspendable CSMA/CA control program if the backoff suspension is permitted and IEEE 802.15.4 device intends to perform backoff suspension.

Abstract: A computer-executed method is provided for IEEE 802.15.4 devices based on a suspendable carrier-sense multiple access with collision avoidance (CSMA/CA) control program and standard CSMA/CA control program for an IEEE 802.15.4 network composing of IEEE 802.15.4 devices. The computer-executed method is provided on an IEEE 802.15.4 device, and causes a processor of the IEEE 802.15.4 device to perform steps that include determining the permission of backoff suspension and the intention of IEEE 802.15.4 device to perform backoff suspension, selecting the suspendable CSMA/CA control program if the backoff suspension is permitted and IEEE 802.15.4 device intends to perform backoff suspension.

Abstract: A distance estimation method comprises transmitting a wave of radiation modulated in frequency domain by an emitter to a scene, receiving a reflection of the transmitted wave from the scene, and interfering a copy of the transmitted wave with the received reflection to generate a sequence of samples of the beat signal with wrapped phases in a time domain. The method also comprises estimating a frequency of the beat signal in the time domain in an iterative manner until a termination condition is met. The iterative estimation of the frequency of the beat signal is based on phase unwrapping of the samples of the beat signal subject to correlated phase error derived from phase noise statistics of the emitter and a linear regression fitting the frequency of the beat signal into the unwrapped phases of the beat signal.

Abstract: A network manager is provided for delivering a firmware/software program to multi-mode nodes and single-mode nodes arranged in a multi-hop wireless IoT network. The network manager includes a transceiver configured to perform wireless communication by transmitting the encoded packets of the firmware/software program to the first-hop nodes. The network manager divides firmware/software program into source blocks, encodes the source blocks into encoded blocks based on coding scheme, packs the encoded blocks into encoded packets, transmits the encoded packets to the first-hop nodes. In this case, the first-hop nodes are configured to receive, decode, re-encode and re-transmit the encoded packets to propagate firmware/software distribution to the other-hop nodes. The network manager keeps broadcasting the encoded packets to the first-hop nodes until a predetermined percent of the first-hop nodes receive the firmware/software program.

Abstract: A distributed machine learning based traffic prediction method is provided for predicting traffic of roads. In this case, the distributed machine learning based traffic prediction method includes distributing global multi-task traffic models by a learning server to learning agents to locally train the traffic models, uploading locally trained traffic models by learning agents to the learning server, updating global multi-task traffic models by the learning server using locally trained traffic model parameters acquired from learning agents, generating a time-dependent global traffic map by the learning server using the well trained global multi-task traffic models, distributing the time-dependent global traffic map to vehicles traveling on the roads, and computing an optimal travel route with the least travel time by a vehicle using the time-dependent global traffic map based on a driving plan.

Abstract: A computer-implemented method is provided for discovering heterogenous neighbors in coexisting IoT networks including at least one Wi-Fi device and at least one of Zigbee coordinators, ZigBee routers and ZigBee end devices. The method includes generating a broadcast packet such that the broadcast packet emulates a ZigBee broadcast frame, transmitting the emulated broadcast packet using a transceiver of the at least one Wi-Fi device according to cross-technology communication (CTC) method, wherein the emulated broadcast packet is configured to trigger the at least one of the Zigbee coordinators and ZigBee routers having received the emulated broadcast packet to rebroadcast the received packet.

Abstract: Data communications and storage systems require error control techniques and digital modulation schemes to be transferred efficiently and successfully. Constellation shaping based on probabilistic amplitude shaping (PAS) offers an energy-efficient transmission in particular for long shaping blocks. However, longer shaping blocks can cause burst errors and enhancement of bit error rates besides longer latency to complete distribution matcher and dematcher operations. Methods and systems are disclosed that provide a way to resolve the issues by introducing a dual concatenation of pre-shaping and post-shaping error correction codes to mitigate burst errors of shaping. This enables low-complexity, high-performance and parallel architecture with a balanced overhead of dual-concatenation codes for shaping systems.

Abstract: A method for semi-persistent scheduling (SPS) based resource allocation in a private 5G network comprises receiving location data of a plurality of user equipment (UEs) in the private 5G network in a last subframe of respective current communication periods of the UEs and determining distance distribution of the UEs in a subsequent communication period of a candidate UE of the plurality of UEs, based on the respective location data of the UEs. The method further comprises determining signal to noise ratio expectation of the UEs for the subsequent communication period, solving an optimization problem optimizing an expectation of data to be carried by each of the one or more SPS channels in the subsequent communication period, to obtain scheduling result for each of the one or more SPS channels and generating resource allocation data for the candidate UE based on the scheduling result.

Abstract: The present disclosure provides an anomaly detector. The anomaly detector comprises an input interface configured to accept input data, a first neural network having an autoencoder architecture including an encoder trained to encode the input data and a decoder trained to decode the encoded input data to reconstruct the input data, and a loss estimator configured to compare a plurality of parts of the input data with corresponding plurality of parts of the reconstructed input data to determine a sequence of losses for different components of a reconstruction error. The anomaly detector further comprises a second neural network trained in a supervised manner to classify the sequence of losses to detect an anomaly to produce a result of anomaly detection including one or a combination of a type of the anomaly and a severity of the anomaly, and an output interface to render the result of anomaly detection.

Abstract: A computer-implemented pre-processed time-delay autoencoder based anomaly detection method are provided for detecting anomalous states of machines arranged in a factory automation (FA) system or a manufacturing production line.

Abstract: A method for communication between a communication device and a base station in a private 5G network where the communication device and the base station have a base period of transmission defined there between as a minimal scheduling period, comprises transmitting location data of the communication device in a last subframe of a current communication period of the communication device. The method further comprises receiving resource allocation data including a transmission period widening factor for one or more subsequent communication periods of the communication device and computing a semi-persistent scheduling (SPS) period as a subsequent communication period of the one or more subsequent communication periods, based on the transmission period widening factor and the base period of transmission. Uplink communication is performed in the one or more subsequent periods, based on the resource allocation data and the SPS period.

Abstract: A computer-executed method is provided for IEEE 802.15.4 devices based on an active carrier sense based carrier-sense multiple access with collision avoidance (ACS-CSMA/CA) control program and standard CSMA/CA control program for coexistence of an IEEE 802.15.4 network composing of IEEE 802.15.4 devices and IEEE 802.11 network composing of IEEE 802.11 devices sharing frequency spectra between the networks. The computer-executed method is provided on an IEEE 802.15.4 device, and causes a processor of the IEEE 802.15.4 device to perform steps that include estimating a severity of IEEE 802.11 interference based on a severity estimation metric, selecting the ACS-CSMA/CA control program based on the estimated severity.

Abstract: An optical coherence tomography (OCT) system comprises an interferometer configured to split incident light into a reference beam and a test beam, and to interfere the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern. The OCT system also comprises a spectrometer configured to analyze spectral components of the interference pattern at non-uniformly sampled wavenumbers. A computer-readable memory of the OCT system is configured to store a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers. The OCT system further comprises a processor configured to determine the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model.

Abstract: Embodiments of the present disclosure disclose a method and a system for tracking the position of the one or more moving objects. The method includes collecting GNSS measurement data of satellite signals transmitted from multiple satellites. The method further includes extracting values of a plurality of features from the GNSS measurement data. The method includes mapping the extracted values of the plurality of features to a source domain. The method includes classifying the mapped transformed plurality of features using a neural network. The neural network is trained over simulated data sampled from a source domain. The method includes identifying multipath measurements of the GNSS measurement data based on classification of the corresponding mapped transformed plurality of features. The method includes tracking the position of the one or more moving objects by processing identification of GNSS measurement data affected by multipath.

Abstract: A system and a computer-implemented method using physics-informed neural network (PINN) are provided for data communications. At a transmitter, the method is configured to acquire source data to be transmitted, encode the source data to codewords based on forward error correction (FEC) codes, map the codewords to amplitude symbols, modify the mapped amplitude symbols to pre-equalized symbols including pre-distort channel impairments symbols based on a predetermined physical model, and transmit digital data of the pre-equalized symbols over a channel as channel data.

Abstract: A computer-implemented method is provided for discovering heterogenous neighbors in coexisting IoT networks including at least one Wi-Fi device and at least one of Zigbee coordinators, ZigBee routers and ZigBee end devices. The method includes generating a broadcast packet such that the broadcast packet emulates a ZigBee broadcast frame, transmitting the emulated broadcast packet using a transceiver of the at least one Wi-Fi device according to cross-technology communication (CTC) method, wherein the emulated broadcast packet is configured to trigger the at least one of the Zigbee coordinators and ZigBee routers having received the emulated broadcast packet to rebroadcast the received packet.