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Found 11 papers, 1 papers with code
Nonlinear Self-Interference Cancellation With Learnable Orthonormal Polynomials for Full-Duplex Wireless Systems
In this paper, we propose a novel algorithm for nonlinear digital SIC that adaptively constructs orthonormal polynomial basis functions according to the non-stationary moments of the transmit signal.
Joint and Robust Beamforming Framework for Integrated Sensing and Communication Systems
In this paper, we present a joint communication and radar beamforming framework for maximizing a sum spectral efficiency (SE) while guaranteeing desired radar performance with imperfect channel state information (CSI) in multi-user and multi-target ISAC systems.
On the Learning of Digital Self-Interference Cancellation in Full-Duplex Radios
The experimental results demonstrate the robustness of the model-based SIC methods, providing practical evidence of their effectiveness.
Learning-Based One-Bit Maximum Likelihood Detection for Massive MIMO Systems: Dithering-Aided Adaptive Approach
First, we add a dithering signal to artificially decrease the SNR and then infer the likelihood function from the quantized dithered signals by using an SNR estimate derived from a deep neural network-based estimator which is trained offline.
Adaptive Learning-Based Detection for One-Bit Quantized Massive MIMO Systems
At low SNR, observations vary frequently in value but the high noise power makes capturing the effect of the channel difficult.
Coordinated Per-Antenna Power Minimization for Multicell Massive MIMO Systems with Low-Resolution Data Converters
We show that strong duality holds between the primal DL formulation and its manageable Lagrangian dual problem which can be interpreted as the virtual uplink (UL) problem with adjustable noise covariance matrices.
Coordinated Beamforming in Quantized Massive MIMO Systems with Per-Antenna Constraints
In this work, we present a solution for coordinated beamforming for large-scale downlink (DL) communication systems with low-resolution data converters when employing a per-antenna power constraint that limits the maximum antenna power to alleviate hardware cost.
Secure Transmission for Hierarchical Information Accessibility in Downlink MU-MIMO
In this paper, we consider a generalized model of conventional physical layer security, referred to as hierarchical information accessibility (HIA).
Rate-Splitting Multiple Access for Downlink MIMO: A Generalized Power Iteration Approach
Rate-splitting multiple access (RSMA) is a general multiple access scheme for downlink multi-antenna systems embracing both classical spatial division multiple access and more recent non-orthogonal multiple access.
Energy Efficiency Maximization Precoding for Quantized Massive MIMO Systems
For maximizing EE in quantized downlink massive MIMO systems, this paper formulates a precoding optimization problem with antenna selection; yet acquiring the optimal joint precoding and antenna selection solution is challenging due to the intricate EE characterization.
A Framework for Automated Cellular Network Tuning with Reinforcement Learning
In this paper, we formulate cellular network performance tuning as a reinforcement learning (RL) problem and provide a solution to improve the performance for indoor and outdoor environments.
