11 results about "Downlink beamforming" patented technology

Systems, methods, apparatuses, and computer program products for interference reduction. One method may include calculating at least one downlink beamforming coefficients vector, and estimating at least one channel coefficient. Interference may be calculated, and a configuration may be selected based upon a determination of interference power. The transformed beamforming coefficients vector may be calculated by at least one of minimizing maximum interference power over one or more uplink antenna elements, minimizing mean interference power over one or more uplink antenna elements, or minimizing interference power based on uplink beamforming.

The disclosure provides a method for beam footprint handover, a method for receiving information, a method for transmitting information, a terminal and a base station. The method for beam footprint handover performed by a terminal comprises the following steps: receiving a first signaling, wherein the first signaling is used for instructing the terminal to hand over from a first beam footprint to a second beam footprint; handing over from the first beam footprint to the second beam footprint in response to the first signaling; wherein a beam footprint is a coverage range of the downlink beamforming signals, the first beam footprint and the second beam footprint belong to a same cell, and downlink signals in the first beam footprint are transmitted with the first beam, while downlink signals in the second beam footprint are transmitted with the second beam.

The invention belongs to the technical field of edge computing, and discloses a beam forming and computing unloading method for a wireless energy supply symbiotic edge computing network, which optimizes the downlink beam forming design of a base station and the sub-problem of wireless energy supply duration optimization through a centralized deep reinforcement learning algorithm. An unloading decision and energy consumption optimization sub-problem of the mobile equipment is optimized through a mixed action multi-agent deep reinforcement learning algorithm, and an uplink beam forming design optimization sub-problem of a base station is optimized by using a convex optimization method, so that the problem solving complexity is reduced; mixed action multi-agent deep reinforcement learning is designed, each mobile device serves as an independent agent to carry out distributed decision making, and the problems of too low algorithm training speed and poor performance caused by a huge action space are avoided.

This invention belongs to the field of edge computing technology and discloses a beamforming and computation offloading method for a wireless power-co-located edge computing network. It optimizes the downlink beamforming design and wireless power supply duration optimization sub-problems of the base station using a centralized deep reinforcement learning algorithm, optimizes the offloading decision and energy consumption optimization sub-problems of mobile devices using a hybrid action multi-agent deep reinforcement learning algorithm, and optimizes the uplink beamforming design optimization sub-problem of the base station using a convex optimization method, thus reducing the complexity of problem solving. The hybrid action multi-agent deep reinforcement learning algorithm, where each mobile device acts as an independent agent for distributed decision-making, avoids the slow training speed and poor performance issues caused by a large action space.

Aspects include obtaining a call request, determining that the call request is placed from an environment that suffers from location inaccuracy, resulting in a first determination, based on the first determination, determining, that a serving cell is operating at a low or mid frequency band and at least one high frequency band neighbor is available, resulting in a second determination, based on the second determination, initiating carrier aggregation in a downlink direction using the low or mid frequency band and a high frequency band included in the at least one high frequency band neighbor, enabling downlink beamforming operations in respect of the high frequency band, initiating observed time difference of arrival (OTDOA) positioning operations, and determining a location of a mobile communication device that initiated the call request based on the enabling of the downlink beamforming operations and the initiating of the OTDOA positioning operations. Other embodiments are disclosed.

This invention relates to the field of wireless communication technology, specifically to a method and system for cooperative precoding of uplink and downlink in full-duplex multi-user communication. The method includes: establishing a full-duplex multi-user MIMO communication system; constructing uplink and downlink signal models for the communication system; constructing a cooperative precoding uplink and downlink cooperative beamforming optimization model, and establishing a model for maximizing total spectral efficiency under uplink and downlink transmit power constraints; based on the weighted minimum mean square error criterion, introducing auxiliary variables to transform the total spectral efficiency maximization model into an equivalent outer-layer iterative total spectral efficiency maximization problem, and iteratively solving it; establishing an alternating iterative framework for uplink and downlink beamforming matrices, and solving to obtain the uplink and downlink beam matrices. This invention improves the total spectral efficiency of multi-user communication systems in full-duplex communication mode.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit a set of sounding reference signals (SRSs) in an uplink direction. The UE may receive a plurality of downlink reference signals in accordance with a downlink beamforming, wherein the plurality of downlink reference signals are precoded using a precoder based at least in part on the set of SRSs. The UE may perform, via one or more discrete antennas, an analog beamforming communication based at least in part on an analog downlink beam weight or an analog uplink beam weight, wherein the analog downlink beam weight is for the downlink beamforming and is based at least in part on a channel impulse response (CIR), and wherein the analog uplink beam weight is derived based at least in part on the analog downlink beam weight. Numerous other aspects are described.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit a set of sounding reference signals (SRSs) in an uplink direction. The UE may receive a plurality of downlink reference signals in accordance with a downlink beamforming, wherein the plurality of downlink reference signals are precoded using a precoder based at least in part on the set of SRSs. The UE may perform, via one or more discrete antennas, an analog beamforming communication based at least in part on an analog downlink beam weight or an analog uplink beam weight, wherein the analog downlink beam weight is for the downlink beamforming and is based at least in part on a channel impulse response (CIR), and wherein the analog uplink beam weight is derived based at least in part on the analog downlink beam weight. Numerous other aspects are described.

A communication apparatus selects one of a plurality of channel estimates for use in downlink beamforming for downlink transmission to another communication apparatus, or uplink beamforming for uplink reception from the another communication apparatus, at a given frequency and time resource. The plurality of channel estimates includes at least two of: a first channel estimate based on a first type of uplink reference signal transmitted by the other communication apparatus; a second channel estimate based on a second type of uplink reference signal transmitted by the other communication apparatus; and a third channel estimate calculated from both the first channel estimate and the second channel estimate.

The application discloses a precoding matrix indication selection method based on a neural network. In the method, a user end first acquires a channel matrix of a downlink; then, the channel matrix is preprocessed by downsampling, segmented discrete Fourier transform and number domain conversion, so that input features suitable for neural network processing are obtained; then, the neural network is used for feature extraction and code word mapping on the preprocessed channel features, corresponding code word numbers are output for each subband, and the code word numbers are converted into precoding matrix indication (PMI) parameters; subsequently, the user end feeds back the PMI to a base station; and the base station maps corresponding precoding matrices according to the same predefined codebook and the received PMI, and the precoding matrices are used for downlink beamforming transmission. The application uses the neural network to replace a conventional traversal search type PMI selection process, reduces the calculation complexity of the user end under the premise of keeping compatibility with an existing codebook feedback mechanism, and improves the PMI selection efficiency.

The application discloses a kind of robust security beamforming and target tracking method and equipment of full duplex sensing integration system, by dual-function radar communication base station is executed.Step includes: base station receives radar echo signal, with extended Kalman filter real-time tracking estimation downlink mobile user motion state, obtain predicted channel state information;Based on this information, design downlink beamforming matrix, construct uplink receive beamforming vector, optimize artificial noise signal covariance matrix;With Cramer-Rao bound quantification potential eavesdropper angle estimation error, construct uncertainty set;Under the requirements such as satisfying secrecy rate, angle estimation error, beam tracking mean square error, construct the joint optimization problem of minimizing system total transmit power;Non-convex semi-infinite constraint is converted into linear matrix inequality and is solved iteratively, and optimal parameter is obtained;Accordingly control base station, realize robust security beamforming and target tracking, solve the problem of safe communication under dynamic environment.