Method and apparatus for beam management
AssigneeLenovo (Beijing) Limited
InventorsHongtao Zhang, Yao Chen, Haiming Wang, Haipeng Lei
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Abstract
Embodiments of the present disclosure relate to a method and apparatus for beam management. According to some embodiments of the disclosure, a method performed by a UE may include: receiving a pilot signal from a plurality of base stations (BSs); measuring channel state information (CSI) between the UE and each of the plurality of BSs; generating a CSI matrix based on the measured CSI between the UE and the plurality of BSs; encoding the CSI matrix; and transmitting the encoded CSI matrix to one of the plurality of BSs.
Claims20
A network apparatus for wireless communication, comprising:
- at least one memory;
- and
- at least one processor coupled with the at least one memory and configured to cause the network apparatus to:
- receive first information associated with channel state information (CSI) between a plurality of user equipment (UEs) and a plurality of base stations (BSs), wherein the network apparatus is configured to manage the plurality of BSs and each of the plurality of UEs is associated with a corresponding BS of the plurality of BSs;
- generate a beamforming matrix based on the first information by a beamforming model deployed on a cloud apparatus, wherein the beamforming model comprises an inception structure block comprising at least two branches and at most one pooling layer for filtering input data which is included in one branch of the at least two branches, each branch including at least one convolutional layer;
- and
- transmit the beamforming matrix to the plurality of BSs.
A user equipment (UE) for wireless communication, comprising:
- at least one memory;
- and
- at least one processor coupled with the at least one memory and configured to cause the UE to:
- receive pilot signals from a plurality of base stations (BSs);
- measure channel state information (CSI) between the UE and each of the plurality of BSs;
- generate a CSI matrix based on the measured CSI between the UE and the plurality of BSs;
- encode the CSI matrix;
- and
- transmit the encoded CSI matrix to at least one of the plurality of BSs for a beamforming matrix generation by a beamforming model, wherein the beamforming model comprises an inception structure block comprising at least two branches and at most one pooling layer for filtering input data which is included in one branch of the at least two branches, each branch including at least one convolutional layer.
A processor for wireless communication, comprising:
- at least one controller coupled with at least one memory and configured to cause the processor to:
- receive pilot signals from a plurality of base stations (BSs);
- measure channel state information (CSI) between a user equipment (UE) and each of the plurality of BSs;
- generate a CSI matrix based on the measured CSI between the UE and the plurality of BSs;
- encode the CSI matrix;
- and
- transmit the encoded CSI matrix to at least one of the plurality of BSs for a beamforming matrix generation by a beamforming model, wherein the beamforming model comprises an inception structure block comprising at least two branches and at most one pooling layer for filtering input data which is included in one branch of the at least two branches, each branch including at least one convolutional layer.
A method performed by a user equipment (UE), the method comprising:
- receiving pilot signals from a plurality of base stations (BSs);
- measuring channel state information (CSI) between the UE and each of the plurality of BSs;
- generating a CSI matrix based on the measured CSI between the UE and the plurality of BSs;
- encoding the CSI matrix;
- and
- transmitting the encoded CSI matrix to at least one of the plurality of BSs for a beamforming matrix generation by a beamforming model, wherein the beamforming model comprises an inception structure block comprising at least two branches and at most one pooling layer for filtering input data which is included in one branch of the at least two branches, each branch including at least one convolutional layer.
Dependencies are inferred from the claim text.