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Max-Min Fair Energy-Efficient Beam Design for Quantized ISAC LEO Satellite Systems: A Rate-Splitting Approach
Currently, two fundamental challenges, namely, inter-beam interference among users and power limitation at the LEO satellites, limit the full potential of the joint design of sensing and communication.
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.
Sum-Rate Maximization of RSMA-based Aerial Communications with Energy Harvesting: A Reinforcement Learning Approach
In this letter, we investigate a joint power and beamforming design problem for rate-splitting multiple access (RSMA)-based aerial communications with energy harvesting, where a self-sustainable aerial base station serves multiple users by utilizing the harvested energy.
Flexible Hybrid Beamforming for Spectrally Efficient 6G Joint Radar-Communications
The joint-SE based proposed method optimally selects the number of RF chains with flexible hynrid beamforming design.
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.
Rate-Splitting Multiple Access for Multi-Antenna Broadcast Channel with Imperfect CSIT and CSIR
Rate-splitting multiple access (RSMA) has appeared as a powerful transmission and multiple access strategy for multi-user multi-antenna communications.
Robust Design
Information Theory
Information Theory
Power Allocation in Cache-Aided NOMA Systems: Optimization and Deep Reinforcement Learning Approaches
To address the power allocation problem, two novel methods are proposed.
