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Found 3 papers, 0 papers with code
Federated Learning Using Three-Operator ADMM
We propose FedTOP-ADMM, which generalizes FedADMM and is based on a three-operator ADMM-type technique that exploits a smooth cost function on the edge server to learn a global model parallel to the edge devices.
EVM Mitigation with PAPR and ACLR Constraints in Large-Scale MIMO-OFDM Using TOP-ADMM
Although signal distortion-based peak-to-average power ratio (PAPR) reduction is a feasible candidate for orthogonal frequency division multiplexing (OFDM) to meet standard/regulatory requirements, the error vector magnitude (EVM) stemming from the PAPR reduction has a deleterious impact on the performance of high data-rate achieving multiple-input multiple-output (MIMO) systems.
EVM-Constrained and Mask-Compliant MIMO-OFDM Spectral Precoding
In this paper we propose a novel spectral precoding approach which constrains the EVM while complying with the mask requirements.
