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Found 7 papers, 0 papers with code
Deep Learning for Joint Design of Pilot, Channel Feedback, and Hybrid Beamforming in FDD Massive MIMO-OFDM Systems
This letter considers the transceiver design in frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems for high-quality data transmission.
Optimization of RIS Placement for Satellite-to-Ground Coverage Enhancement
In satellite-to-ground communication, ensuring reliable and efficient connectivity poses significant challenges.
How to Differentiate between Near Field and Far Field: Revisiting the Rayleigh Distance
Future wireless communication systems are likely to adopt extremely large aperture arrays and millimeter-wave/sub-THz frequency bands to achieve higher throughput, lower latency, and higher energy efficiency.
Hierarchical Beam Alignment for Millimeter-Wave Communication Systems: A Deep Learning Approach
Fast and precise beam alignment is crucial for high-quality data transmission in millimeter-wave (mmWave) communication systems, where large-scale antenna arrays are utilized to overcome the severe propagation loss.
Channel Sparsity Variation and Model-Based Analysis on 6, 26, and 132 GHz Measurements
In addition, a new intra-cluster power allocation model based on measurements is proposed to characterize the effects of sparsity in the delay domain of the 3GPP channel model.
Channel Type Recognition in Wireless Communications: A Deep Learning Approach
In this paper, we propose two novel and practical deep-learning-based algorithms to solve the wireless channel type (WCT) recognition problem.
Deep-Reinforcement-Learning-Based Scheduling with Contiguous Resource Allocation for Next-Generation Cellular Systems
Scheduling plays a pivotal role in multi-user wireless communications, since the quality of service of various users largely depends upon the allocated radio resources.
