4 papers
Graph Neural Network-Enhanced Expectation Propagation Algorithm for MIMO Turbo Receivers
Xingyu Zhou, Jing Zhang, Chao-Kai Wen +2
Deep neural networks (NNs) are considered a powerful tool for balancing the performance and complexity of multiple-input multiple-output (MIMO) receivers due to their accurate feat…
Gradient-Based Markov Chain Monte Carlo for MIMO Detection
Xingyu Zhou, Le Liang, Jing Zhang +2
Accurately detecting symbols transmitted over multiple-input multiple-output (MIMO) wireless channels is crucial in realizing the benefits of MIMO techniques. However, optimal MIMO…
Interference Constrained Beam Alignment for Time-Varying Channels via Kernelized Bandits
Yuntian Deng, Xingyu Zhou, Arnob Ghosh +2
To fully utilize the abundant spectrum resources in millimeter wave (mmWave), Beam Alignment (BA) is necessary for large antenna arrays to achieve large array gains. In practical d…
Model-Driven Deep Learning-Based MIMO-OFDM Detector: Design, Simulation, and Experimental Results
Xingyu Zhou, Jing Zhang, Chen-Wei Syu +3
Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM), a fundamental transmission scheme, promises high throughput and robustness against multipath…