Beijing University of Posts and Telecommunications

Zhiqing Wei

Zhiyong Feng

Qixun Zhang

Ping Zhang

Sai Huang

Yifan Zhang

Hao Ma

Fan Ning

Che Ji

Zixi Fang

Kezhong Zhang

Li Xu

Yifan Zhao

Rui Dai

Wangjun Jiang

Mengyuan Liu

Huan Sun

Yibo Huan

Xiaoqi Qin

A cooperative precoding method and device. The method includes: obtaining a first sensing and communication signal sent by a first node; obtaining a second sensing and communication signal sent by a second node; updating the first sensing and communication signal; updating the second sensing and communication signal; returning to the step of obtaining a first sensing and communication signal when the signal-to-noise ratio of a signal received by a user and the signal-to-noise ratio of a radar echo signal received by the first node do not meet a preset condition. The solutions enhance sensing performance of nodes while at the same time improve the communication performance of a target user.

Cooperative precoding method and apparatus

A broadband millimeter wave beam tracking method based on vehicle movement trajectory recognition, which relates to the field of wireless communication. First, a rough estimate of the beam angle is obtained according to the position and attitude of two vehicles in a communication scenario at an initial moment, and a state of the vehicle is judged according to the sudden change rate of the transmitting beam angle starting from a next moment: if it is in the sudden change mode, the observation value ŷof the received signal is calculated; if it is in the smooth change mode, the observation value I is calculated; the observation values in different modes are input into an improved particle filter algorithm for fine beam estimation, to obtain optimal values xand u; and the beam optimal values at the current moment are used to re-estimate a pair of the forming vector of the transmitting beam and the forming vector of the receiving beam to adjust the vehicle and the pilot signal at the next moment is transmitted; by continuously adjusting the beam forming vector at each moment, a beam tracking within an error range is obtained. The present application improves the accuracy and reliability of beam tracking in case of sudden angle change.

Broadband millimeter wave beam tracking method based on vehicle motion trajectory cognition

The invention relates to an integrated sensing and communication system based on a mobile communication signal, belonging to the field of wireless communication. In this system, a synchronization sequence embedding module is added at a sending end of a node, which is configured for embedding a primary synchronization sequence and a secondary synchronization sequence into a radio frequency signal to be sent and then outputting the radio frequency signal to a digital modulation module; a primary synchronization sequence-assisted ranging accuracy improvement algorithm module and a secondary synchronization sequence-assisted speed measurement accuracy improvement algorithm module is newly added at a receiving end of a node; a target node range and a target node speed output by a two-dimensional range-Doppler radar processing algorithm module are compensated by using the autocorrelation characteristics of the primary/secondary synchronization sequences in a synchronization broadcast block to obtain more accurate target node range and target node speed. The invention effectively improves the sensing accuracy of the existing OFDM integrated system based on fixed frame structure, improves the accuracy of identifying the target node's motion information, and maximizes the sensing ability through flexible deployment of subcarriers to improve the node's own environmental adaptability.

Sensing and communication integrated system based on mobile communication signal

Embodiments of the present invention provide a signal processing method and apparatus, a first device determines a target insertion position of a pilot sequence in a first frequency-domain signal based on the data bits in a first sub-data signal obtained by dividing data bits in a data signal, combines the pilot sequences with a second sub-data signal obtained by dividing the data signal according to the determined target insertion positions, to obtain the first frequency-domain signal; sends the pulse signal corresponding to the first frequency-domain signal to the second device. The second device determines the pilot sequences in the first frequency-domain signal corresponding to the pulse signal and determines the data bits corresponding to the insertion position of each of the pilot sequences in the first frequency-domain signal, to obtain the first sub-data signal; demodulates subcarriers in the first frequency-domain signal other than the pilot sequences, to obtain the second sub-data signal; splices the first sub-data signal and the second sub-data signal, to obtain the corresponding data signal. Based on the above processing, spectrum resource utilization rate can be improved.

Signal processing method and apparatus

The embodiments of the present application provide a radar-sensing detection method and device based on radar-sensing communication integration. Said method comprises: when being applied to a sending end, determining a position of a receiving end, then sending a beam control signal to the receiving end through a preset beam control request channel, receiving a beam control response signal sent by the receiving end, and sending a first detection result signal to the receiving end in a preset reservation channel. The embodiments of the present application can expand the detection range of an autonomous vehicle.

Detection method and device based on sensing-communication integration

The embodiments of the present application provide a method and apparatus for modulation recognition of signals based on cyclic residual network, the method comprises: obtaining a signal matrix of a to-be-recognized signal, and extracting real part information and imaginary part information of the signal matrix; generating, according to extracted real part information and imaginary part information, a real-and-imaginary-part feature matrix of the to-be-recognized signal; converting, according to a preset matrix conversion method, the real-and-imaginary-part feature matrix into an amplitude-and-phase feature matrix; and inputting the amplitude-and-phase feature matrix into a pre-trained cyclic residual network to obtain a modulation mode corresponding to the to-be-recognized signal. In the embodiments of the present application, the processing of the to-be-recognized signal is simple and easy to operate, in which neither complex algorithms nor manual processing is required, the flexibility of recognition is high, and the result of modulation recognition of the to-be-recognized signal can be accurately obtained.

Method and apparatus for modulation recognition of signals based on cyclic residual network

Disclosed is a method for classifying mixed signals, comprising: receiving mixed signals; performing calculation on a matrix corresponding to the mixed signals by means of a preset Principal Component Analysis method to obtain to-be-classified mixed signals and to determine the number of types of signals contained in the to-be-classified mixed signals; determining a separation matrix based on the number of types of signals contained in the to-be-classified mixed signals; separating individual signals in the to-be-classified mixed signals by means of the separation matrix to obtain to-be-identified signals; calculating a preset number of high-order cumulants corresponding to each to-be-identified signal in the to-be-identified signals respectively; taking the calculated high-order cumulants as characteristics of the to-be-identified signal corresponding to the high-order cumulants respectively; inputting the characteristics of the to-be-identified signal into a preset classification model; and obtaining a modulation mode of the to-be-identified signal. The method according to the embodiment of the present application imposes no requirements on the classification environment, which is different from the prior arts in which the mixed signals can be classified only when certain conditions are met. Therefore, the method has universal applicability.

Method and apparatus for classifying mixed signals, and electronic device

Provided are a radar communication integrated cooperative detection method and apparatus based on beam power distribution. The method comprises: determining a farthest detection distance and a detection volume of a single radar in a radar communication integrated system during transmitting of a detection beam when the radar has a preset transmit power; determining a communication success probability of each pair of radars during transmitting communication beams; determining a detection area volume of each pair of radars under different power distribution coefficients based on the farthest detection distance, the detection volume, a different power distribution coefficient of the single radar, and the communication success probability of each pair of radars; determining a power distribution coefficient corresponding to a largest detection area volume from different detection area volumes as a current power distribution coefficient; and determining total detection volume of the radar communication integrated system based on the detection area volume of each pair of radars and the current power distribution coefficient.

Radar and communication integrated cooperative detection method and apparatus based on beam power distribution

Disclosed are a method and an apparatus for handover between heterogeneous networks. The method comprises: obtaining, for each of a plurality of candidate networks, parameters of the candidate network including a packet loss rate and a network load, and taking the obtained parameters as decision parameters of the candidate network; obtaining each of preset service types and a preset weight factor for at least one user preference corresponding to the preset service type; calculating weights of decision parameters for each preset service type by using the decision parameters of the candidate network and through an Analytic Hierarchy Process, and determining a weight vector for the preset service type; adjusting the weight vector for each preset service type by using the preset weight factor; calculating, using the weight vector and through an intuitionistic trapezoidal fuzzy multi-attribute decision-making algorithm, a score for each of the candidate networks, determining the candidate network with the highest score as a target network, and triggering a handover.

Method and apparatus for handover between heterogeneous networks

Clustering-based methods, apparatuses for frequency offset determination and elimination and electronic devices are disclosed. The clustering-based method for frequency offset determination includes: determining a constellation diagram for a received signal; determining N different values within a preset frequency interval, as N frequency offset estimates for a frequency offset of the received signal; for each of the frequency offset estimates, correcting the constellation diagram based on the frequency offset estimate to obtain a corrected constellation diagram, clustering signal points on the corrected constellation diagram, and calculating an area of a signal region in the corrected constellation diagram after clustering; and determining a frequency offset estimate corresponding to a signal region with a minimum area as a value of the frequency offset. The embodiments of the present invention can improve the accuracy and stability of the calculated value of the frequency offset.

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Beijing, China

Zhiqing Wei