Abstract: A sample to be measured is placed in a medium solution between two circular magnets to ensure that the sample to be measured is levitated in a set circular area between the two circular magnets, and a levitation position of the sample to be measured in the magnetic field is measured. The density of the sample is calculated according to formula (I): ? s = ? m + ? m - ? s g ? ? 0 ? ( B r ? ? B z ? r + B z ? ? B z ? z ) . Compared to the prior art, the method of the present disclosure provides a novel method for measuring a density of a substance, in which the involved device is easy to operate and has low cost, and the measurement results are easy to observe and have high accuracy.

Abstract: An indoor positioning method includes scanning for registered Wi-Fi nodes with known coordinates to generate a list of the registered Wi-Fi nodes. The method also includes performing a ranging operation by (i) selecting nodes to range with from the list of the registered Wi-Fi nodes, and (ii) processing ranging responses from the selected nodes to generate a series of distance measurements. The method further includes obtaining a series of sensor readings generated by one or more inertial measurement units (IMUs) of a device. The method also includes estimating a position of the device based on the series of distance measurements and the series of sensor readings using first and second filtering operations that are performed in parallel.

Abstract: A method for positioning based system design for smart repeaters with adaptive beamforming capabilities is implemented by an electronic device. In certain embodiments, the electronic device is a smart repeater. The method includes obtaining user equipment (UE) location information indicating a location of a UE. The method includes translating, based on a prediction engine, the UE location information to a beam index associated with a beam to serve the UE at the location of the UE. The method includes receiving, from an external communication device via a first wireless communication channel, traffic intended for the UE. The method includes forward-transmitting, via a second wireless communication channel, the traffic via the beam formed at a transmit (TX) antenna of the electronic device.

Abstract: A smart repeater includes a transceiver configured to receive a reference signal, receive, from a base station (BS), a subcarrier allocation for a plurality of user equipments (UEs), receive, from the BS, a downlink (DL) beam associated with the plurality of UEs, and retransmit the DL beam. The smart repeater further includes a processor, operatively coupled to the transceiver, the processor configured to determine a beam split configuration for the DL beam based on the subcarrier allocation, and cause the transceiver to retransmit the DL beam according to the beam split configuration. To retransmit the DL beam according to the beam split configuration the transceiver is further configured to generate a frequency dependent beam for each of the plurality of UEs, and direct the frequency dependent beam for each of the plurality of UEs to a UE associated with the frequency dependent beam.

Abstract: An electronic device includes a first set of sensors configured to generate motion information. The electronic device also includes a second set of sensors configured to receive information from multiple anchors. The electronic device further includes a processor configured to generate a path to drive the electronic device within an area. The processor is configured to receive the motion information. The processor is configured to generate ranging information based on the information that is received. While the electronic device is driven along the path, the processor is configured to identify a location and heading direction within the area of the electronic device based on the motion information. The processor is configured to modify the estimate of location and the heading direction of the electronic device based on the ranging information. The processor is configured to drive within the area according to the path, based on the location and heading direction.

Abstract: A self-calibration detection device and a temperature demodulation method oriented to a fiber Raman temperature sensing system. The self-calibration detection device comprises a fiber Raman thermodetector, thermostatic baths, a multi-mode sensing fiber, and a multi-mode reflector. The fiber Raman thermodetector comprises a pulsed laser whose output end is connected to the input end of a WDM. Two output ends of the WDM are respectively connected to input ends of a first and second APDs. Output ends of the first and second APDs are respectively connected to input ends of a first and second LNAs. Output ends of the first and second LNAs are connected to the input end of a data acquisition card whose output end is connected with the input end of a computer. The temperature demodulation method can solve the problems of low temperature measuring accuracy, lower temperature measurement stability and low temperature measurement efficiency.

Abstract: A method includes obtaining, by a transmit-receive point (TRP), a set of power metrics for multiple UEs including a served UE and one or more helped UEs, wherein each power metric is estimated from multiple channel quality and performance indicators of one of the multiple UEs. The method also includes calculating a performance metric as a function of at least one of the multiple channel quality and performance indicators of the served UE. The method also includes calculating an interference metric as a function of the set of power metrics. The method also includes determining whether to perform coordinated beamforming based on the performance metric and the interference metric. The method also includes determining one or more precoders based on the determination of whether to perform the coordinated beamforming.

Abstract: Methods and apparatuses for canonical model (CM) based channel status information enhancement. A base station includes a transceiver configured to receive a reference signal from a user equipment (UE) and a processor operably coupled to the transceiver. The processor is configured to perform a linear transformation based on the received reference signal, select a basis set based on the linear transformation, select a set of kernels based on the selected basis set and the linear transformation, and reconstruct a channel based on the selected set of kernels.

Abstract: Provided are a lane line recognition method, an electronic device and a storage medium, relating to a technical field of artificial intelligence, in particular to technical fields of intelligent transportation, automatic driving and deep learning. The lane line recognition method includes: extracting a basic feature of an original image; recognizing at least one lane line node in the original image by using the basic feature of the original image; extracting a local feature from the basic feature of the original image by using the at least one lane line node; fusing the basic feature and the local feature; and recognizing a lane line in the original image based on a fused result.

Abstract: A method includes identifying ACF information by: obtaining channel information including multiple channels of expected operation scenarios; and based on the channel information for each of the channels, determining MMSE channel estimation (CE) weights expressed in a form of ACFs and an SNR, and covariance matrices. The method includes clustering the MMSE CE weights into K clusters. A center ACF weight of each of the K clusters represents a codeword. The method includes determining a distance metric based on a cluster distance after a re-clustering. The method includes, in response to a determination that cluster distances before and after the clustering differ from each other by a non-negligibly, iteratively re-clustering the ACF information thereby updating the center ACF weights and cluster distances. The method includes generating the codebook to include an index k of each of the K clusters and the center ACF weight of each of the K clusters.

Abstract: Calibration in distributed multiple input multiple output (MIMO) networks. A method performed by a first base station (BS) includes receiving a first uplink (UL) reference signal (RS) and determining, based on the first UL RS and a second UL RS, a first phase offset for transmission of a first downlink (DL) RS to a user equipment (UE). The second UL RS is associated with a second BS. The first phase offset of the first DL RS is relative to a second DL RS associated with the second BS. The method further includes transmitting the first DL RS with the first phase offset; receiving UE feedback associated with the first DL RS and the second DL RS; and determining, based on the first phase offset and the received feedback, for a DL data transmission to the UE, a second phase offset between transmissions of the first BS and the second BS.

Abstract: Methods and apparatuses for modular MIMO system and CSI feedback in a wireless communication system. The methods and apparatuses include: identifying configuration information of an antenna system including antenna modules for a MIMO operation; identifying, based on the configuration information, a number of collocated antenna groups that each includes one or more of the antenna modules; identifying, based on the configuration information, a number of the antenna modules for each type of the antenna modules in each of the collocated antenna groups, wherein each of the collocated antenna groups includes one or more types of the antenna modules; generating a CSI report for one or more of the collocated antenna groups in the antenna system; and transmitting, to a BS, the CSI report.

Abstract: A method includes receiving a pilot signal or a measurement report from a user equipment (UE) or a base station (BS). The method also includes updating a CSI buffer with channel state information (CSI) obtained from the pilot signal or the measurement report, the CSI buffer configured to store previous uplink or downlink channel estimates. The method also includes providing at least a portion of the CSI buffer to a CSI predictor comprising an artificial intelligence (AI) model that utilizes one or more weight sharing mechanisms, the AI model comprising a sequence of layers. The method also includes predicting temporal CSI using the CSI predictor. Depending on the configured output, the method can also include and/or be used for denoising and frequency extrapolation.

Abstract: A method and apparatus provide a user equipment (UE) configured to communicate with a plurality of carrier aggregation (CA) groups with at least a first CA group (CG1) and a second CA group (CG2). The UE includes processing circuitry. The processing circuitry is configured to determine whether the UE is power-limited. The UE is scheduled to transmit acknowledged information in a physical uplink shared channel (PUSCH) to a cell of the CG1 and uplink control information (UCI), other than the acknowledgement information, in a physical uplink control channel (PUCCH) to a cell of the CG2. The processing circuitry is also configured to, responsive to the UE being power-limited, prioritize the PUSCH for power allocation. The processing circuitry is also configured to transmit the PUSCH to the cell of the CG1.