Patent classifications
H04B7/04013
Automatic signal deployer, signal deployment system, automatic signal path deployment method, and behavior control signal generation method of deployment agent
The present invention discloses an automatic signal deployer, a signal deployment system, an automatic signal path deployment method, and a behavior control signal generation method of a deployment agent. The signal deployment system includes an automatic signal deployer, a deployment agent and a base station. The deployment agent receives signal quality data, generates a behavior control signal according to the signal quality data, and sends out the behavior control signal to the automatic signal deployer. The automatic signal deployer receives the behavior control signal and a source signal coming from the base station, performs deployment according to the behavior control signal, whereby the automatic signal deployer can transmit the source signal toward a signal path allocation direction and complete automatic deployment of signal paths.
Multipath angle estimation and reporting for NR positioning
Multipath angle estimation and reporting for positioning is described. An apparatus is configured to receive a set of multipath signals for a set of VAs. Each VA in the set of VAs is associated with a corresponding reflecting surface in a UE communication environment. Reflection of the set of multipath signals occurs via the corresponding reflecting surface. The apparatus is configured to estimate at least one AoA associated with the set of multipath signals based on at least one of a set of ToF values associated with the set of multipath signals, a UE location, or a VA location. The apparatus is configured to provide, to a network entity, an indication of multipath information associated with the set of multipath signals for the set of VAs. The multipath information includes the at least one AoA associated with at least one multipath signal in the set of multipath signals.
Control information for smart repeater in wireless communication system
Systems and method for using control information to control the relay of signaling between a base station and a user equipment (UE) using a smart repeater (SMR) and/or reconfigurable intelligent surface (RIS) are disclosed herein. In embodiments, a first phase is used by the SMR with a first SS burst from a base station to identify a trained Rx beam to use with the base station, and a second phase receives a second SS burst from the base station and forwards it to a UE using a beam sweep such that the UE is enabled to provide feedback of one SSB of the second SS burst. In other embodiments, an SMR or an RIS is controlled to enable the use of an SS burst to perform a full check of all beam-wise routes between the base station and the UE, enabling feedback of a corresponding SSB selection by the UE.
Assisting node radar assistance
Methods, systems, and devices for wireless communications are described. A user equipment (UE) in a vehicle-to-everything (V2X) system may receive configuration information from an assisting node, such as a roadside unit (RSU), for calculating location information for a target UE in the V2X system. The assisting node may reflect one or more radar signals from the UE towards the target, and from the target back towards the UE according to the configuration information. That is, the assisting node may modify one or more waveform parameters of the reflection according to the configuration information. The UE may calculate location information for the target based on the reflection, such as by classifying the target as non-line-of-sight (NLOS) based on modified waveform parameters, location information of the assisting node, or both.
Channel estimation for configurable surfaces
The present disclosure relates to channel estimation, at a receiving device of a communication system employing a (re)configurable surface. The channel estimation includes beamforming search to obtain trained reflection coefficients of the configurable surface and an angle of arrival, AoA, of the signals at the receiving device. Then, based on the configurable surface and the obtained AoA at the receiving device, reflection coefficients of the configurable surface are derived for an ideal channel portion between the transmitting device and the configurable surface. According to a relation between the trained reflection coefficients and the estimated reflection coefficients, the estimation of the characteristics of a channel between the transmitting device and the configurable surface is performed. The channel estimation may be employed in user mobility tracking.
BEAM SQUINT AND LOCATION-UNCERTAINTY AWARE DESIGNS
Methods, systems, and devices for wireless communications are described. A network entity may output an array configuration to a configurable reflective device (CRD), wherein the array configuration defines a first angle of reflection or refraction at a first frequency and a second angle of reflection or refraction at a second frequency for a reflective array of the CRD. The network entity may output a first transmission, to a first user equipment (UE) via the CRD, at the first frequency according to the array configuration, the first frequency selected based on the first angle of reflection or refraction and a first location of the first UE. The network entity may output a second transmission, to a second UE via the CRD, at the second frequency according to the array configuration, the second frequency selected based on the second angle of reflection or refraction and a second location of the second UE.
RADIO COVERAGE ENHANCEMENT UTILIZING SMART SURFACES ASSISTED UNMANNED AERIAL VEHICLE WITH BEAMFORMING MECHANISM
A communication system includes a drone and a panel with a reconfigurable intelligent surface. The panel is connected to the drone using flexures that allow the orientation of the panel to be controlled. Changing the orientation of the panel, by controlling or configuring the flexures, allows an incident signal to be reflected in a reflection direction to a target location.
Wireless communication system, wireless communication method, transmitter, and receiver
A wireless communication method according to an embodiment includes converting n+1 signals into n predetermined power signals obtained by setting a C/N to a predetermined value and into n divided signals obtained by setting the C/N to 1/n of a predetermined value and performing division into n, superimposing the n predetermined power signals and the n divided signals that have been converted, non-orthogonally so as to be n multiplexed signals for the n frequency channels, transmitting the n multiplexed signals, receiving n multiplexed signals, demodulating n predetermined power signals from the n multiplexed signals that have been received, creating replica signals of each of the n predetermined power signals, subtracting each of the n replica signals that have been created from each of the n multiplexed signals, and combining the n subtracted signals.
SYSTEM AND METHOD FOR INTELLIGENT JOINT SLEEP, POWER AND RECONFIGURABLE INTELLIGENT SURFACE (RIS) CONTROL
A method and network nodes for intelligent joint sleep, power and reconfigurable intelligent surface (RIS) control are disclosed. According to one aspect, a method in a network node configured to communicate with a plurality of small base stations (SBSs) includes jointly determining sleep control, transmission power control and reconfigurable intelligent surface, RIS, control for the plurality of SBSs based at least in part on a fractional programming (FP) algorithm, the FP algorithm configured to maximize a data rate for a plurality of wireless devices (WDs).
METHOD AND APPARATUSES FOR ACQUIRING PILOT POSITION DETERMINATION MODEL, METHOD AND APPARATUSES FOR DETERMINING PILOT POSITION INFORMATION
A method, device for acquiring a pilot position determination mode and computer readable storage medium in a wireless communication system. The pilot position determination model is obtained by: acquiring a training sample set, where the training sample set includes a plurality of sample groups; outputting first pilot position information by inputting the sample groups into an initial pilot position determination model; obtaining predicted channel state information based on the first pilot position information; and adjusting a model parameter of the initial pilot position determination model based on label channel state information and the predicted channel state information, and obtaining a target pilot position determination model by continuing training an adjusted initial pilot position determination model based on a next sample group until training ends.