Abstract: The present disclosure provides a beam domain based localization system, and the beam domain based localization system includes a wireless transceiver and a computer device. The computer device electrically connected to the wireless transceiver, and the computer device configured for: obtaining a beam selection result associated with a mobile device through the wireless transceiver; locating the mobile device according to the beam selection result.

Abstract: A Quality of Experience (QoE) optimization system and method are provided. An electronic device inputs key performance indicators (KPIs) and system control parameters collected from a core network, a base station and a user equipment (UE) into a QoE optimization model. The QoE optimization model then optimizes the system control parameters based on the KPIs and a user QoE fed back from the UE to output optimized system control parameters. Furthermore, a strategy emulator controls at least one of a base station emulator and a UE emulator, so as to emulate the QoE optimization model using the at least one of the base station emulator and the UE emulator. Non-real-time optimization adjustments to the QoE optimization model are made based on the result of the emulation performed by the at least one of the base station emulator and the UE emulator.

Abstract: A method for fault diagnosis in a communication network is to be implemented by a processor. The method includes obtaining key performance indicator (KPI) data related to the communication network, performing a deep-learning-based classification algorithm by using the KPI data as input to a deep neural network model, and determining, based on output of the deep neural network model after performing the deep-learning-based classification algorithm, at least one type of network condition the communication network currently satisfies, and a severity level of the at least one type of network condition when the output of the deep neural network model contains information related to severity levels of the at least one type of network condition.

Abstract: A Quality of Experience (QoE) optimization system and method are provided. An electronic device inputs key performance indicators (KPIs) and system control parameters collected from a core network, a base station and a user equipment (UE) into a QoE optimization model. The QoE optimization model then optimizes the system control parameters based on the KPIs and a user QoE fed back from the UE to output optimized system control parameters. Furthermore, a strategy emulator controls at least one of a base station emulator and a UE emulator, so as to emulate the QoE optimization model using the at least one of the base station emulator and the UE emulator. Non-real-time optimization adjustments to the QoE optimization model are made based on the result of the emulation performed by the at least one of the base station emulator and the UE emulator.

Abstract: The present invention provides a detection device and a method with simplified computing manner A transmitter transmits detection signals to an environment to detect a target. At least a portion of the detection signals are reflected by the target to generate a plurality of reflection signals. A receiver comprises a plurality of receiving units. Each of the receiving units receives the reflection signals to generate a receiving signal. A processing module connected to the receiver includes a conversion unit, an integration unit and a computing unit. The conversion unit converts the receiving signals into transformation signals by a time-domain to frequency-domain transformation. The integration unit integrates the transformation signals into a first integration signal and a second integration signal. The computing unit decomposes the first integration signal and the second integration signal to 1D arrays.

Abstract: A system for synthesizing signal of user equipment and a method thereof are provided. The system includes a physical channel modeler and a physical channel training module. The physical channel modeler receives geo information of a field under test of and a sparse real physical field channel feature to build a physical channel model. The physical channel modeler estimates a plurality of predefined positions of the geo information to obtain a plurality of simulated physical field channel features corresponding to the predefined positions. The physical channel training module receives and performs training on the geo information, the sparse real physical field channel feature and the simulated physical field channel features by using an AI algorithm to perform an inference of a fully real physical field channel feature.

Abstract: A signal processing method is provided. First, at least one transmitted signal is output to at least one target, and the target reflects at least one reflected signal to receiving antennas, which then generate receiving signals upon receipt of the reflected signal. Next, the transmitted signal and each receiving signal are processed to generate processing signals. The processing signals are arranged in a form of matrix, to generate a channel coefficient matrix having M×N channel coefficient matrix blocks. Next, the channel coefficient matrix is divided into Ndivide×Mdivide secondary channel coefficient matrices, which are then substituted into a snapshot vector matrix equation to generate a snapshot vector matrix for calculating an angle of the target. The signal processing method can establish an optimal secondary channel coefficient matrix arrangement by using a special signal preprocessing manner, to improve the resolution and accuracy of the estimated angle parameter of the target.

Abstract: An AI decision based multiple telecommunication endpoints system is provided, including a telecommunication endpoint device and an artificial intelligence decision controller. The telecommunication endpoint device performs a communication test with the radio frequency communication device under test. The artificial intelligence decision controller is electrically connected to the telecommunication terminal device to control the communication test, and performs an efficiency analysis on the result of the communication test, and generates a decision instruction according to the result of the efficiency analysis.

Abstract: A system for synthesizing signal of user equipment and a method thereof are provided. The system includes a physical channel modeler and a physical channel training module. The physical channel modeler receives geo information of a field under test of and a sparse real physical field channel feature to build a physical channel model. The physical channel modeler estimates a plurality of predefined positions of the geo information to obtain a plurality of simulated physical field channel features corresponding to the predefined positions. The physical channel training module receives and performs training on the geo information, the sparse real physical field channel feature and the simulated physical field channel features by using an AI algorithm to perform an inference of a fully real physical field channel feature.

Abstract: A system and method of emulating radio device includes a multi-radio unit, a multi-radio unit controller and an under-test radio system. The multi-radio unit includes multiple radio circuits, in which the radio circuits are configured to generate multiple radio emulated signals. The multi-radio unit controller coupled to the multi-radio unit is configured to generate multiple control signals to the multi-radio unit, in which the control signals are configured to control the radio emulated signals sent by the multi-radio unit. The under-test radio system is configured to receive the radio emulated signals generated by the multi-radio unit, and configured to generate multiple data corresponding to the radio emulated signals.

Abstract: The present invention provides a detection device and a method with simplified computing manner A transmitter transmits detection signals to an environment to detect a target. At least a portion of the detection signals are reflected by the target to generate a plurality of reflection signals. A receiver comprises a plurality of receiving units. Each of the receiving units receives the reflection signals to generate a receiving signal. A processing module connected to the receiver includes a conversion unit, an integration unit and a computing unit. The conversion unit converts the receiving signals into transformation signals by a time-domain to frequency-domain transformation. The integration unit integrates the transformation signals into a first integration signal and a second integration signal. The computing unit decomposes the first integration signal and the second integration signal to 1D arrays.

Abstract: A method of cell placement includes choosing the ray-tracing channel matrices for the Nth iteration according to candidate cell locations of the Nth iteration and the user distributions, calculating fitness values for the Nth iteration based on the ray-tracing channel matrices, substituting the fitness values for the Nth iteration and corresponding candidate cell locations for the best fitness and best candidate cell locations in a total iterative process respectively if the fitness values for the Nth iteration are greater than or equal to multiple thresholds and the best fitness in a total iterative process, storing candidate cell locations of the Nth iteration, and verifies termination criteria, if termination criteria are not satisfied at the Nth iteration, generating the candidate cell locations of the N+1th iteration.

Abstract: An antenna performance evaluation method is disclosed. The method includes the following steps: measuring plurality of throughput values of the to-be-tested antenna at the first angle under different average radiation signal-to-interference ratio (SIR). The average radiation SIR and throughput values are fitted to output the first fitted curve. The second throughput value is measured at a certain average radiation SIR of the second angle of the to-be-tested antenna. Calculating a difference value between the first throughput value and the second throughput value corresponding to the same average radiation SIR, and the difference value and the first fitting curve constitute the transition second fitting curve. Selecting different average radiation SIR is repeatedly, and measure the corresponding second throughput value, and the corresponding difference value is calculated to update the transition second fitting curve.

Abstract: A signal processing method is provided. First, at least one transmitted signal is output to at least one target, and the target reflects at least one reflected signal to receiving antennas, which then generate receiving signals upon receipt of the reflected signal. Next, the transmitted signal and each receiving signal are processed to generate processing signals. The processing signals are arranged in a form of matrix, to generate a channel coefficient matrix having M×N channel coefficient matrix blocks. Next, the channel coefficient matrix is divided into Ndivide×Mdivide secondary channel coefficient matrices, which are then substituted into a snapshot vector matrix equation to generate a snapshot vector matrix for calculating an angle of the target. The signal processing method can establish an optimal secondary channel coefficient matrix arrangement by using a special signal preprocessing manner, to improve the resolution and accuracy of the estimated angle parameter of the target.

Abstract: A reduced-overhead channel estimation method and system thereof for massive MIMO systems is provided in present application. The method is applied in a base station device, and includes following steps: first, enabling the base station device to acquire a plurality of channel matrixes between the base station device and one or a plurality of external user devices, then enabling the base station device to label the positions of a non-zero coefficient and a common support coefficient in a plurality of fields of the channel matrixes, and then enabling the base station device to configure the non-zero coefficient and the common support coefficient to have the weights different from the weights of the coefficients in the other fields in the channel matrixes so as to provide estimating channel matrixes.

Abstract: A reduced-overhead channel estimation method and system thereof for massive MIMO systems is provided in present application. The method is applied in a base station device, and includes following steps: first, enabling the base station device to acquire a plurality of channel matrixes between the base station device and one or a plurality of external user devices, then enabling the base station device to label the positions of a non-zero coefficient and a common support coefficient in a plurality of fields of the channel matrixes, and then enabling the base station device to configure the non-zero coefficient and the common support coefficient to have the weights different from the weights of the coefficients in the other fields in the channel matrixes so as to provide estimating channel matrixes.

Abstract: A method for angle estimation verification, adapted for verifying an estimated angle calculated by an electronic apparatus having an angle estimator and at least three antennas, is provided. The estimated angle is extracted from the angle estimator. An autocorrelation matrix is generated according to a signal vector formed by a plurality of measurements of a received signal received by each of the antennas so as to obtain a plurality of eigenvalues. Among phase difference data generated by a plurality of antenna groups formed by all different combinations of two of the antennas, a plurality of possible estimated angles corresponding to the phase difference data not caused by a coterminal angle effect are calculated. According to the eigenvalues and the possible estimated angles, whether the received signal corresponds to a single target or multiple targets is determined so as to verify the reliability of the estimated angle.

Abstract: A motion parameter estimating method, an angle estimating method and a determination method are provided. The methods are adapted for an electronic device. In the angle estimating method, a first frequency modulation continuous wave signal is first transmitted, and at least one antenna receives a second frequency modulation continuous wave signal resulted by a target reflecting the first frequency modulation continuous wave signal. Multiple motion parameters associated with the target are then obtained according to the first frequency modulation continuous wave signal and the second frequency modulation continuous wave signal. Multiple measured values corresponding to the at least one antenna are obtained according to the motion parameters and configuration parameters of the at least one antenna, respectively. Afterwards, the measured values are substituted into a formula to obtain an estimated angle between a preset direction of the electronic device and the target.

Abstract: A method for angle estimation verification, adapted for verifying an estimated angle calculated by an electronic apparatus having an angle estimator and at least three antennas, is provided. The estimated angle is extracted from the angle estimator. An autocorrelation matrix is generated according to a signal vector formed by a plurality of measurements of a received signal received by each of the antennas so as to obtain a plurality of eigenvalues. Among phase difference data generated by a plurality of antenna groups formed by all different combinations of two of the antennas, a plurality of possible estimated angles corresponding to the phase difference data not caused by a coterminal angle effect are calculated. According to the eigenvalues and the possible estimated angles, whether the received signal corresponds to a single target or multiple targets is determined so as to verify the reliability of the estimated angle.

Abstract: The present invention provides a method for identifying a specific number of communicating points having relatively smallest accumulated path values from a plurality of transmitting points for a receiving point in a communication system. The method includes steps of: (a) defining a first coordination of each of the plurality of transmitting points and the receiving point on a complex plane; (b) transferring the first coordination of the receiving point to a second coordination thereof, in which the second coordination of the receiving point is near an origin of the complex plane; and (c) identifying the specific number of transmitting points having relatively smallest accumulated path values based on the second coordination of the receiving point.