3067 results about "Beamforming" patented technology

The invention relates to a multi-microphone array beam forming signal enhancement method and device, and the method comprises the steps: obtaining a multi-channel time domain signal collected by a multi-microphone array, and carrying out the time-frequency conversion, and obtaining a plurality of time-frequency domain signals; acquiring a spatial distribution vector of the multi-microphone array, and performing deformation compensation processing on the complex number of time-frequency domain signals to obtain sound field consistency signals; performing sound source direction feature extraction on the sound field consistency signal, and performing complex time-space attention beam forming network processing to obtain a beam forming signal; performing beam direction and gain parameter optimization on the beam forming signal through a preset adversarial environment simulator to obtain a dynamic frequency band enhanced signal; and performing inverse time-frequency conversion on the dynamic frequency band enhanced signal, and performing low-delay optimization to obtain a target quality voice output signal. According to the invention, signal deformation compensation can be carried out more accurately.

The invention discloses a precise interference avoidance method and device in a radio system, and relates to the field of signal processing, and the method comprises the steps: constructing a sensing matrix through sensing node data, and capturing a transient interference signal through aperiodic scanning; performing tensor decomposition on the signal data to extract time domain, frequency domain, space domain and modulation domain features, constructing a dual-mode spectrum analysis model, reconstructing an instantaneous spectrogram by using compressed sensing, and predicting an interference mode through LSTM; after the instantaneous spectrogram and the predicted interference graph are fused, threat assessment is carried out through a multi-stage interference classification model; according to the interference category and the threat level, beam forming is optimized, adaptive null is generated, a power density optimization model is constructed, and the transmitting power is dynamically adjusted; an anti-interference frequency hopping sequence is generated based on a chaotic mapping algorithm, and spectrum camouflage and tracking interference resistance are realized. The method has the advantages that accurate identification and dynamic avoidance of interference are realized through multi-dimensional perception, intelligent prediction and adaptive beam forming, and the interference avoidance capability of a wireless system is improved.

According to the 5G portable WiFi signal enhancement method and system provided by the invention, surrounding environment data are collected through an environment sensing sensor, and a device placement scheme is optimized in combination with a deep learning algorithm, so that the signal coverage range is expanded; the strategy of dynamically adjusting the transmitting power, the signal frequency and the modulation mode can optimize the signal strength according to the environmental change; interference signals are analyzed through quantum calculation, null is formed through the beam forming technology, interference signal receiving is effectively restrained, and the signal strength in the target direction is enhanced. In combination with the Internet of Things technology, uploading equipment state data to an edge server in real time for big data analysis, and pushing a personalized signal enhancement scheme according to different user use environments; through precise placement guidance and a dynamic frequency band switching strategy, a user can enjoy smoother network connection in a use process, and good signal quality is ensured to be kept in a complex environment. According to the invention, not only can the signal quality of 5G portable WiFi be improved, but also more intelligent and personalized network experience can be provided for users.

The invention discloses an intelligent sound effect processing system for an automobile DSP (Digital Signal Processor) power amplifier, particularly relates to the field of optimization of a vehicle-mounted sound system, is used for solving the problem of insufficient sound effect consistency and intelligent adaptation in a dynamic sound field, and is characterized in that acoustic data are acquired in real time through a microphone array, and a three-dimensional acoustic geometric model is constructed by combining ray tracing and an image source method; sound wave propagation paths and dynamic changes are accurately captured; frequency bands of low-frequency, intermediate-frequency and high-frequency signals are divided, spectrum distribution differences and gain fluctuation centers of all seats are evaluated, and a sound field consistency adjustment coefficient is generated and used for guiding design and optimization of a directional beam forming filter, adjusting amplitudes and phases of all sound channels, forming directional sound beams and suppressing noise interference; therefore, the method can dynamically adapt to the acoustic environment change in the vehicle, improves the sound effect balance and high fidelity, and enhances the auditory experience and satisfaction of passengers.

A device capable of using image data for purposes of determining a location of a user and audio beam selection to isolate audio in the direction of the user. The beamforming / beam-steering may occur after determining the user's location in order to conserve computing resources that would otherwise have been spent determining beams for non-desired directions. The beamformed audio may be used for speech processing, a communication session involving the device, or other purposes.

The invention relates to the field of intelligent warehousing, and discloses an intelligent clothing inventory real-time monitoring and automatic checking system based on RFID, which aims at solving the problems of poor environmental adaptability, high dynamic sensing delay, high cross-scene deployment cost and the like in the prior art, and comprises a reconfigurable RFID tag, an integrated spiral-dipole composite antenna and a temperature compensation circuit, dual-band switching of 860 to 960 MHz and self calibration are supported; a heterogeneous read-write network is formed by a fixed reader-writer and AGV mobile nodes, and signal coverage is enhanced through beam forming; the edge calculation module adopts an LSTM trajectory prediction and hybrid filtering algorithm to realize millisecond-level processing; the cloud platform maps the inventory in real time based on the digital twin model and traces the source of the block chain, the dynamic time slot distribution protocol optimizes the cooperation of the reader-writer, and the transfer learning model realizes cross-scene rapid adaptation. According to the invention, the tag reading rate is 99.7%, the inventory efficiency is improved by 300%, the deployment period is shortened by 80%, and the problems of accurate inventory management and dynamic tracking in a complex environment are solved.

The method focuses on the technical field of communication, and the communication connection problem under the cooperative operation scene of the unmanned vehicle and the unmanned aerial vehicle is accurately positioned. In practical application, communication connection is troubled by a complex environment, signals are prone to strong interference, the transmission distance is obviously limited, and double requirements of real-time performance and accuracy are difficult to consider in the aspect of data transmission characteristics during cooperative operation of the two. According to the invention, ZigBee, 5G, satellite communication modules and multi-mode communication modules are integrated, an adaptive protocol is optimized, channels are sensed in real time, the channels are selected and switched through an intelligent algorithm, signals are enhanced through directional antennas and beam forming, interference resistance is realized through adaptive filtering and error correction coding, and stability is guaranteed by means of link monitoring and a self-healing mechanism. According to the method, reliable interaction of data between the unmanned vehicle and the unmanned aerial vehicle in a complex environment can be ensured, and real-time and accurate transmission of monitoring data can be ensured even in case of strong electromagnetic interference or severe weather.

A system and method of targeting spatialized audio to ears of a listener, comprising sensing characteristics of an environment comprising at least one human by receiving radio frequency signals with a radio receiver; using the sensed characteristics in at least one automated processor to analyze at least one human dynamic physiological pattern of each human and estimate a body pose and head position within the environment of each human based on the sensed characteristics and the at least one human dynamic physiological pattern; and using an estimated position of the ears of each human in conjunction with a head-related transfer function in a spatial audio system to generate spatialized audio.

The invention provides an unmanned aerial vehicle (UAV)-based flux-inductance integrated beam forming and trajectory optimization method, on one hand, an FP-AROS method is proposed based on fractional programming and semi-definite relaxation technologies in combination with approximate rank-one solution construction to carry out optimization design on ISAC beams, the Cramer-Rao bound of AoD is adopted as a sensing performance evaluation index, and the FP-AROS method is adopted to carry out optimization design on the ISAC beams; target estimation performance can be reflected more directly, so that a collaborative optimization effect of communication and sensing performance is realized; on the other hand, the invention provides an improved continuous convex approximation method based on a trust domain, and the method is used for optimization design of a UAV track. The ITRSCA method obtains a local trend approximate solution of an original objective function by calculating a second derivative, and introduces a dynamic trust domain mechanism to control approximate precision, so as to ensure global convergence of an output solution; in addition, the method is combined with a penalty function method to process non-convex constraints, and the limitation of a trust domain method in a constrained optimization problem is effectively overcome.

Various embodiments of the present disclosure provide a method performed by an electronic device in a wireless communication system. The method may comprise receiving, from a base station (BS), a radio resource control (RRC) signal including information related to a number of bits in a downlink control information (DCI) field required to represent indicatable beams, receiving, from the base station, DCI including the DCI field for a beam indication of a beam used in an access link between the electronic device and at least one user equipment (UE) among the indicatable beams, and transmitting or receiving a signal with the at least one UE based on the beam indication.

The invention relates to the technical field of artificial intelligence, and discloses a Bluetooth communication intelligent speech translation method and system based on multi-mode enhancement, and the method comprises the steps: collecting a multi-channel audio signal through a built-in multi-microphone array of a Bluetooth device, carrying out the dynamic direction self-adaptive beam forming of the multi-channel audio signal, and carrying out the self-adaptive beam forming of the multi-channel audio signal; extracting a Mel spectrogram feature of the direction enhancement signal, identifying lip regions of a plurality of candidate speakers in each frame of real-time speaking video captured by a camera, performing time sequence convolution on the lip regions to obtain a lip movement time sequence embedded vector, calculating a correlation score with the Mel spectrogram feature, separating the direction enhancement signal, and obtaining a lip movement time sequence embedded vector; and performing text transcription and conversion on the high-confidence separation voice to obtain a translation language text, and sending the synthesized target translation voice to a preset mobile terminal through the Bluetooth device to obtain a target translation result. According to the method, the real-time performance and accuracy of speech translation are improved in a multi-person scene, far-field speech, noise interference and accent difference.

The invention relates to a beam forming design method of an active RIS-assisted ISAC system, and belongs to the field of communication perception integration. A multi-user large-scale multiple-input single-output system model assisted by communication and perception integration and a system model based on an ISAC system assisted by an active RIS are constructed, and a beam forming vector and a reflection coefficient of the active RIS are respectively optimized by adopting an alternating optimization algorithm. According to the method, the propagation blockage problem is solved, the system performance is further improved, the multiplicative fading effect problem of the passive RIS is solved by using the active RIS, the weighted minimum mean square error algorithm, the continuous convex approximation algorithm and the positive semidefinite relaxation algorithm are combined, the system effectiveness is improved to the maximum extent, and the system performance is improved to the maximum extent. The system utility is the sum of the weighted sum rate of the system and the target detection power, the target detection capability is remarkably enhanced while the weighted sum rate of the user is improved, and a new solution is provided for performance optimization of the ISAC system.

The invention belongs to the technical field of radar signal processing, and discloses a radar scattering rapid test method based on polarization decomposition. Comprising the following steps: scanning a target 3D model, simulating scattered field distribution in different incident angles and polarization modes, calculating polarization contrast, and identifying a polarization sensitive area; establishing a dynamic coordinate system conversion model, fusing RTK data, IMU data and laser tracking data, and correcting the position of the trolley and the model in combination with a Doppler frequency shift model and a least square method; calculating an optimal test path of the trolley according to the sensitive area by adopting a natural heuristic optimization algorithm; establishing a geometric environment model, obtaining a back scattering signal through beam forming, analyzing a polarization coherence matrix, obtaining a high-entropy region, and decomposing scattering components; according to the method, closed-loop optimization is formed from a data acquisition source to a scattering component analysis tail end, and the test efficiency and the real-time performance are remarkably improved.

An adaptive modular multimodal communication and computing panel includes a multilayer stack with a protective layer transmissive in selected bands, a reconfigurable communication layer operable in phased array, reflectarray, hybrid phased reflector, free space optical, or quantum modes, and electronics with heterogeneous processors. A multi scale interconnect and input and output fabric couples electrical, radio frequency, guided optical, and free space optical domains through interfaces including electro optic transduction and RF or baseband conversion. The fabric may implement programmable true time delay, resonators, and comb referenced timing. A management system coordinates beamforming, sensing, routing, calibration, workload placement, and security. Panels tessellate and connect by electrical, radio frequency, and fiber optic interfaces, supporting hot swappable modules, blind mate connectors, robotic servicing, and anti tamper features. Power and thermal subsystems harvest, store, regulate, and dissipate energy. The architecture scales from chip level modules to vehicle, airborne, maritime, orbital, and deployable systems.

The invention provides a directional pickup method, system and device and a storage medium, and relates to the field of pickup. The method comprises the following steps: performing MVDR beam forming processing on an initial voice signal input by a microphone array, and then extracting a BFCC feature and a fundamental tone frequency feature of the voice signal; and processing the BFCC features by using a pre-trained voice / noise separation DNN to obtain a time-frequency mask. And according to the fundamental tone frequency characteristics, adaptively designing comb filter parameters, and carrying out comb filtering on the initial voice signal. And taking the time-frequency mask as a weighting coefficient, respectively multiplying the weighting coefficient with the voice signal after comb filtering and the initial voice signal, and estimating target voice energy and noise energy. And calculating a Bark gain coefficient related to the frequency on the Bark frequency scale, wherein the Bark gain coefficient is used for enhancing the voice signal in the time-frequency domain. And finally, converting the enhanced voice signal into a time domain signal through inverse BFCC conversion to obtain a target enhanced voice pointing to the target direction. Through the scheme, the directional pickup effect is improved.

The invention provides a dual-unmanned aerial vehicle cooperative obstacle avoidance and communication link reconstruction system and method, and belongs to the technical field of wireless communication and unmanned aerial vehicle cooperative control. The system is composed of two unmanned aerial vehicles, serves as a mobile base station to provide relay communication for users, and cooperatively perceives an aerial target. The method comprises the following steps: establishing an integrated model integrating tracks, NOMA signals and layered continuous interference cancellation; calculating communication and sensing key indexes; constructing an optimization problem which takes maximization of the minimum average interaction rate between the unmanned aerial vehicles as a target and takes power, QoS, perception and security constraints into consideration; a distributed architecture is adopted to decompose problems, and a Dual-TD3 algorithm is proposed to collaboratively optimize beam forming and a flight path. According to the dual-unmanned aerial vehicle cooperative obstacle avoidance and communication link reconstruction system and method, dynamic intelligent distribution of communication and sensing resources is realized, and the interaction rate, the robustness and the resource utilization rate of the system in a dynamic scene are remarkably improved.

An electronic device may be mounted to a main body of a removable case. The case includes a cover that rotates between open and closed positions. The device may convey wireless data and / or a control signal with the removable case over radio-frequency connectors, near-field communications (NFC) coils, connector electrodes, and / or wired data connectors. The removable case may relay the wireless data between the electronic device and a communications satellite in space. The case may include a phased antenna array in the cover. In the open position, the cover may point the phased antenna array towards the sky. The removable case may include beamforming circuitry in the cover and coupled to the phased antenna array. The control signal may control the beamforming circuitry to produce, using the phased antenna array, a signal beam oriented towards the communications satellite.

The invention discloses a directional broadcast multi-band interference suppression method based on dynamic beam forming, and relates to the technical field of computer processing, and the method comprises the steps: S01, synchronously capturing electromagnetic signals of at least two working bands through a heterogeneous band receiving array synchronized by a hardware-level clock; s02, analyzing space parameters of a target signal and an interference source in the electromagnetic signal in real time; s03, constructing a layered adaptive codebook based on the interference dynamic parameters; s04, fusing the target signal parameter and the interference dynamic parameter by adopting a block matrix acceleration algorithm and an orthogonal decomposition technology, and calculating a beam forming weight; s05, executing operation through the multi-band coprocessor; and S06, establishing an interference source azimuth drift prediction model, and setting a trigger threshold as the coverage tolerance angle theta. According to the method, the anti-interference real-time performance is improved by utilizing layered adaptive wave beams, frequency band isolation, super-resolution multi-path identification and block decomposition.

The invention relates to the technical field of wireless communication, in particular to an intelligent beam forming system and method for millimeter wave communication, and the system comprises a sensing module which is used for collecting multi-direction signal data in a millimeter wave communication environment and extracting environment feature information, and an intelligent decision module which generates a beam direction control strategy based on a deep reinforcement learning algorithm, the sub-region management module divides a communication region into a plurality of sub-regions according to a beam direction control strategy and allocates communication resources to each sub-region, and the beam control module adjusts the beam direction and power allocation of the antenna array according to the beam direction control strategy and the communication resource allocation result of the sub-regions. The feedback evaluation module obtains communication quality data after beam adjustment and generates a performance evaluation result, and the learning optimization module updates network parameters of a deep reinforcement learning algorithm according to the performance evaluation result and improves the environment adaptive capability.

Techniques for environment-based positioning and communication are disclosed. In some aspects, techniques include performing one or more positioning operations with respect to a user device in a wireless communication network, which may include obtaining first environmental information using one or more sensors of a wireless-enabled device; sending the first environmental information to a network entity of the wireless communication network; receiving first enhanced assistance data from the network entity, the first enhanced assistance data generated based at least on the first environmental information sent to the network entity; and performing the one or more positioning operations using the first enhanced assistance data received from the network entity, wherein the wireless-enabled device comprises the user device or a base station. In some aspects, techniques include improving communication in the wireless communication network, which may include receiving enhanced beamforming information from a network entity; and performing wireless communication using enhanced beamforming information.

The invention discloses an air federated learning realization method for collaborative optimization of client scheduling and model compression. The invention realizes the air federated learning realization method for collaborative optimization of client scheduling and model compression. Along with rapid development of federated learning in a wireless network, air computing based on a multiple-input-multiple-output technology is widely concerned due to high communication efficiency of the air computing. However, in a resource-limited large-scale device scene, channel interference, device heterogeneity and limited spectrum resources significantly restrict the convergence rate and model performance of federated learning. In order to deal with the challenges, the invention provides an air federated learning framework combining compressed sensing and client scheduling, and by collaborative design of model parameter compression, multi-antenna beam forming and dynamic equipment selection strategies, the total communication overhead of each round of training is minimized, and meanwhile, the convergence of a global model is guaranteed. In order to balance training cost and model quality, a joint optimization problem based on calculation-communication cost and model precision loss is provided. In order to solve the non-convex optimization problem, an original problem is decoupled into two sub-problems. Firstly, an optimization problem of a pre-coding and post-processing matrix is designed for a given user scheduling result to minimize a gradient aggregation error. Then, a novel user scheduling algorithm based on channels and data is provided to obtain an air aggregation result.

The invention relates to the technical field of intelligent signal processing, in particular to an unmanned aerial vehicle cluster intelligent beamforming method and system, and the method comprises the following steps: obtaining unmanned aerial vehicle node positions, antenna deviation and synchronization errors, analyzing the influence of quantization precision on beamforming, extracting low-precision waveform features, recognizing the amplitude-phase error compensation amount, and optimizing the anti-interference performance. Phase constraints are extracted and optimized, the consistency of the beam and the expected direction is compared, parameters are adjusted to obtain an adjustment instruction set, and a beam forming maintaining state label is output. According to the method, position information, pointing deviation and synchronization errors are analyzed through joint modeling, amplitude-phase feature extraction precision is improved, interference and echo separation capability is enhanced, control robustness is improved, discrete phase constraint and alternating direction optimization are introduced, control vector solution and convergence are accelerated, and direction errors are dynamically adjusted. A retention label is generated through convergence trend analysis, beam consistency and anti-interference performance are enhanced, and high-precision stable control is realized in a complex change scene.

The present invention provides a method for optimization of active and passive beamforming and signal reception configuration of a dual IRSs-assisted ISAC system. By jointly optimizing active beamforming at a base station, the reception of a sensing signal by the base station, and passive beamforming at an IRS, the achievable rate of communication users is maximized while ensuring that the signal-to-noise ratio of the sensing signal meets the minimum requirement. In the present invention, to solve the complex nonconvex problem generated, first, fractional programming is used to decouple an optimization problem, then, a successive convex approximation algorithm and an alternating direction method of multipliers are used to transform an intractable nonconvex problem into multiple tractable subproblems, and finally, an alternative optimization method is used to efficiently solve for a high-quality sub-optimal solution. Simulation results show that the provided solution has good convergence and effectiveness, and the solution can effectively improve the performance of IRS-assisted ISAC systems.

A disaster relief system using AI-powered intelligent antennas in drone swarms, consisting of: a plurality of drones configured to collect environmental data in real time, with the drones being deployed in a disaster area environment; a smart antenna system mounted on each drone, each smart antenna system configured to perform adaptive beamforming to maintain communication links between drones; an artificial intelligence (AI) processing unit configured to receive real-time signal data, including obstacle information, drone positions, and interference patterns from the disaster environment, analyze the received signal data using reinforcement learning algorithms, generate optimized beamforming parameters based on the analysis, and transmit the optimized beamforming parameters to the intelligent antenna systems; a swarm communication protocol module configured to establish communication links between the plurality of drones using the optimized beamforming parameters, coordinate task assignments within the drone swarm, and maintain network integrity during operation; and a central control system configured to monitor all swarm operations, process environmental data, and adapt swarm behavior based on disaster relief requirements.

The invention relates to a broadband planar array antenna light-operated beam forming method based on multi-task sparse learning, and the method comprises the steps: deducing an array factor expression of a broadband array as priori knowledge through employing a rectangular planar array antenna; constructing a multi-frequency-point beam joint optimization model of the planar array antenna based on the neural network; based on the priori knowledge, calculating a total loss function of the model by using expected broadband array pattern data and a group inhaul cable regularization method, and training a multi-frequency-spot beam joint optimization model; and based on the trained model, obtaining the optimal array layout and the amplitude and delay distribution of each array element, and calculating to obtain a low-sidelobe directional diagram in which the deflection angle is irrelevant to the frequency. According to the invention, the deflection angle of the array radiation beam is kept constant in a broadband range, and the problem of'beam squint 'of a traditional phased array is solved; and meanwhile, the beam sidelobe level of each frequency point is effectively suppressed, and the grating lobe problem of the uniform array on the broadband is avoided.

The invention relates to the technical field of high-frequency multichannel synchronous transmission, in particular to a time domain reflection compensation design method for high-frequency signal transmission loss, which comprises the following steps of: 1, responding to a synchronous trigger signal to generate an active reflection reference signal with a determined time domain position; 2, aligning time marks between channels through cross-correlation operation; 3, extracting a reflection feature template of the channel from the alignment signal, and recognizing and eliminating crosstalk components through convolution operation with an adjacent channel template; 4, constructing a time-varying transfer function model according to the amplitude envelope attenuation characteristic and the carrier phase jump characteristic of the reflection characteristic template; and 5, generating a compensation filter based on the time-varying transfer function model, and verifying the compensation effect through secondary reflection. Through cross-correlation operation, accurate alignment of multi-channel signal time scales is realized, the time delay difference between different transmission channels is overcome, signal synchronization of each channel is ensured, and the beam forming precision is improved.

The invention discloses a non-contact electrocardio detection method which comprises the following steps: transmitting a frequency modulation continuous wave signal to the heart part of a human body by using an MIMO millimeter wave radar so as to obtain an echo signal reflected by the human body and pre-process the echo signal to obtain a discrete three-dimensional radar signal; enhancing the discrete three-dimensional radar signal by using a 2D beam forming technology to obtain a 2D signal; extracting a target area signal from the 2D signal, and performing phase extraction on the extracted target area signal to obtain phase data; the method comprises the following steps: constructing a WaveGRU-Net network comprising an MODWT module, a CNN module and a Bi-GRU module; and training the WaveGRU-Net network by using the phase data so as to output a reconstructed electrocardiogram by using the trained WaveGRU-Net network, thereby realizing non-contact electrocardiogram detection. According to the method, accurate extraction of the electrocardiosignal is realized, and meanwhile, the signal reconstruction precision is improved.

The invention relates to the technical field of sound beam control, and provides a sound beam forming pointing control method based on crowd recognition and related equipment thereof. The method comprises the following steps: performing time-space synchronous acquisition and calibration on multi-modal sensor data to obtain a time-space aligned original data set, and performing layered signal enhancement on the original data set to obtain a visual feature tensor and an audio feature tensor; dense crowd detection and tracking are carried out according to the visual feature tensor to obtain a target crowd space-time trajectory matrix, and sound source localization and beam weight calculation are carried out in combination with the audio feature tensor to obtain a beam forming weight vector; performing multi-constraint dynamic optimization in combination with environmental parameters in the multi-modal sensor data to obtain an adaptive control parameter set, and finally performing real-time beam forming in combination with a loudspeaker sequence to obtain a directional sound field output signal. According to the invention, target detection, sound source localization and dynamic adaptive control are combined on the multi-source data, so that the beam direction is dynamically adjusted.

A wireless communication network method and system that includes a central server, cellular base stations, edge computing devices, and client devices. The client devices send uplink pilot sequences, which are collected and aggregated by the base stations. The base stations then relay this aggregated pilot data to the central server. The central server deploys network weights for a global deep learning neural network model to the base stations for incorporation into respective local deep learning models, trained to predict optimal beamforming vectors, to the base stations for incorporation into respective local deep learning model. During training the central server integrates adaptive noise into weights received for each of the local deep learning models.

A network entity configures a synchronization signal block (SSB) using SSB resources that convey a primary synchronization signal (PSS), a secondary synchronization signal (SSS), and a physical broadcast channel (PBCH) within an SSB resource area of a resource grid bounded in time by a first configured integer number of time units and bounded in frequency by a second configured integer number of physical channels. A product of the first configured integer number and the second configured integer number is a predetermined constant value, each symbol of the SSB has an equal number of resource elements (REs), and all REs in the each symbol of the SSB, except REs within a frequency guard band between any two of the PSS, the SSS, and the PBCH in the each symbol of the SSB, have non-zero values. A user equipment receives the SSB in the SSB resources as a beamformed SSB.