US Patent Application 18245675. SCHEDULING ENERGY AUTOENCODER BASED NONCOHERENT TRANSMISSION simplified abstract
Contents
SCHEDULING ENERGY AUTOENCODER BASED NONCOHERENT TRANSMISSION
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SCHEDULING ENERGY AUTOENCODER BASED NONCOHERENT TRANSMISSION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18245675 titled 'SCHEDULING ENERGY AUTOENCODER BASED NONCOHERENT TRANSMISSION
Simplified Explanation
- The patent application relates to wireless communication and specifically focuses on a user equipment (UE) identifying multiple resource element (RE) segments associated with a scheduled communication. - Each RE segment includes one or more REs in one or more scheduled physical resource blocks associated with the scheduled communication. - The UE communicates with a device based on the energies of the REs included in the multiple RE segments associated with the scheduled communication. - The communication with the device involves transmitting or detecting a sub-sequence associated with an RE segment using a neural network. - The neural network modulates the sub-sequence associated with the RE segment to the one or more REs in the RE segment. - The patent application introduces a novel approach to wireless communication that utilizes neural networks and RE segments to enhance communication efficiency and reliability.
Original Abstract Submitted
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may identify multiple resource element (RE) segments associated with a scheduled communication that includes a source bit sequence, each RE segment including one or more REs in one or more scheduled physical resource blocks associated with the scheduled communication. The UE may communicate with a device based at least in part on respective energies on the one or more REs included in the multiple RE segments associated with the scheduled communication. For example, communicating with the device may include transmitting or detecting a sub-sequence associated with an RE segment using a neural network that modulates the sub-sequence associated with the RE segment to the one or more REs in the RE segment. Numerous other aspects are provided.
