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Found 8 papers, 4 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.
A Learning-Based Approach to Address Complexity-Reliability Tradeoff in OS Decoders
We show that using artificial neural networks to predict the required order of an ordered statistics based decoder helps in reducing the average complexity and hence the latency of the decoder.
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.
Deep unfolding of the weighted MMSE beamforming algorithm
Motivated by the recent success of deep unfolding in the trade-off between complexity and performance, we propose the novel application of deep unfolding to the WMMSE algorithm for a MISO downlink channel.
Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure
A high signal power is achieved by transmitting the same data signal from all antennas, but with different amplitudes and phases, such that the signal components add coherently at the user.
Information Theory Information Theory
Capacity Limits and Multiplexing Gains of MIMO Channels with Transceiver Impairments
The capacity of ideal MIMO channels has a high-SNR slope that equals the minimum of the number of transmit and receive antennas.
Information Theory Information Theory
Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users
Analytic results are derived to show how user selection, spatial correlation, heterogeneous user conditions, and imperfect channel acquisition (quantization or estimation errors) affect the performance when sending the maximal number of streams or one stream per scheduled user---the two extremes in data stream allocation.
Information Theory Information Theory
