Abstract

Multicasting is a mode of transmission in which the same information is relayed to a subset of users. Delivering the same information to multiple users of the subset via a series of one-to-one (unicast) transmissions quickly exhausts bandwidth. Delivering information in a series of one-to-all (broadcast) transmissions such that each subset receives its information in a round-robin manner causes latency, or equivalently, a reduction in bandwidth.

The techniques of this disclosure estimate the angular locations of each multicast subset using channel state information received across an antenna array. The locations are clustered using machine learning models. The available transmit power is allocated amongst clusters via spatially directed beams. The power allocation is designed to optimize the aggregate multicast bit rate while guaranteeing a minimum per-user bit-rate. Relevant information is beamed in a focused manner to each multicast subset, thus increasing the throughput to a subset while reducing interference to other subsets.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Share

COinS