Abstract:
A method, an apparatus, and a computer program product for wireless communication are provided. The apparatus reduces inference in a received signal. The apparatus receives a signal including transmissions from a plurality of cells. The apparatus determines transmission parameter hypotheses associated with the plurality of cells. Each transmission parameter hypothesis from the transmission parameter hypotheses includes a set of transmission parameters associated with all the cells from the plurality cells. The apparatus selects at least one transmission parameter hypothesis based on a first metric applied to each hypothesis. The apparatus refines transmission parameters associated with at least one cell from the plurality of cells. The refining includes improving an accuracy of the transmission parameters associated with the at least one cell based on a second metric associated with each cell individually.
Abstract:
For an enhanced physical downlink control channel (EPDCCH), unlimited traffic-to-pilot ratio (TPR) variations across resource elements of a physical resource block (PRB) pair is problematic because of the detrimental affect the variations will have on the ability of a user equipment (UE) to perform inter-cell/intra-cell interference suppression (IS) and/or interference cancellation (IC) on EPDCCH of an interfering cell. A TPR limitation is placed on EPDCCH to facilitate IS/IC without causing practical limitations on EPDCCH management by an eNB. Accordingly, a method, an apparatus, and a computer program product for wireless communication are provided. The apparatus identifies a plurality of resource elements of at least one PRB pair for transmitting one or more control channels, divides the plurality of identified resource elements into one or more groups, and restricts a plurality of resource elements in a respective group to a TPR.
Abstract:
A method, an apparatus, and a computer program product for wireless communication are provided. In one configuration, the apparatus may be a UE. The UE determines an MCS that would facilitate interference suppression of an interfering first cell transmission from a first cell when decoding a second cell transmission from a second cell at the UE. The interfering first cell transmission is a transmission unintended for the UE. The second cell transmission is a transmission intended for the UE. The UE transmits information indicating the determined MCS for the first cell. The UE receives a transmission including the second cell transmission from the second cell and the interfering first cell transmission from the first cell. The UE demodulates and/or decodes the second cell transmission from the received transmission based on the determined MCS.
Abstract:
A method, an apparatus, and a computer program product for wireless communication are provided. The apparatus may be a UE that acquires information regarding an interfering non-serving cell and uses the information to improve decoding of serving cell signals. The method includes receiving, from a serving evolved Node B (eNB), information that includes one or more transmission characteristics of at least one non-serving cell and performing at least one of interference cancellation, demodulation, or provides an improved channel quality indicator (CQI) based on the received information.
Abstract:
Disclosed are techniques for environment sensing. In an aspect, a transmitter base station determines a configuration for a radio frequency (RF) sensing signal, the configuration determined based at least in part on coordination among a plurality of base stations, and transmits the RF sensing signal to at least one receiver base station based on the configuration. In an aspect, a receiver base station receives a configuration for an RF sensing signal, the configuration determined based at least in part on coordination among a plurality of base stations, receives, from at least one transmitter base station, the RF sensing signal, and detects at least one target object based, at least in part, on reception of the RF sensing signal.
Abstract:
Methods, systems, and devices for wireless communications are described. A first wireless device may be configured to communicate signaling with a second wireless device, an additional wireless device, or both, and perform, based on the signaling, one or more inferences using a machine learning model. The first wireless device may transmit, to the second wireless device, an indication that the machine learning model was applicable for performing the one or more inferences, and receive, from the second wireless device, control signaling indicating that the machine learning model is applicable for communications that are associated with a first set of conditions associated with the communication of the signaling, where the control signaling indicates a model identifier (ID) associated with the machine learning model, that the first set of conditions is associated with the machine learning model, or both.
Abstract:
Certain aspects of the present disclosure provide techniques for wireless communications by an apparatus. A method includes sending signaling indicative of one or more power ratios, wherein each of the one or more power ratios is based on a transmit power for transmitting sounding reference signal (SRS) using a corresponding antenna and a receive power for receiving channel state information reference signal (CSI-RS) using the corresponding antenna, and wherein the one or more power ratios are associated with one or more antennas; sending a first CSI-RS; receiving a first SRS; receiving first channel state feedback (CSF) corresponding to the CSI-RS; and performing channel estimation based on the first CSF and the first SRS.
Abstract:
A user equipment (UE) may receive a configuration for collecting measurements to at least one of train or verify a positioning model. The UE may receive a set of positioning signals. The UE may measure the set of positioning signals. The UE may output a subset of the measured set of positioning signals to at least one of train or verify the positioning model based on the configuration. The UE may output the subset of the measured set of positioning signals by training verifying the positioning model at the UE based on the subset of the measured set of positioning signals, or by transmitting the subset of the measured set of positioning signals to at least one of train or verify the positioning model.
Abstract:
Certain aspects of the present disclosure provide techniques for wireless communications by a user equipment (UE), including receiving, from a network entity, one or more parameters for performing interference prediction at the UE; predicting, for each of at least one communications resource, a predicted interference at the UE, wherein the predicted interference comprises a plurality of probability values, each probability value of the plurality of probability values being associated with a different class of a plurality of classes, each class of the plurality of classes associated with a corresponding range of interference power; and sending, to the network entity, a report based on the predicted interference.
Abstract:
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a network node, a transformer configuration that includes a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more channel state information (CSI) feedback tasks of a plurality of CSI feedback tasks associated with a transformer-based cross-node machine learning system, and transmit the at least one latent vector based at least in part on instantiating the transmitter neural network. Numerous other aspects are described.