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Found 11 papers, 0 papers with code
Joint User Scheduling, Power Allocation, and Rate Control for MC-RSMA in URLLC Services
Specifically, for a given user grouping scheme, an iteration-based concave-convex programming (CCCP) method and an iteration-free lower-bound approximation (LBA) method are proposed for power allocation and rate control.
Integer-Based Pattern Synthesis for Asymmetric Multi-Reflection RIS
This study delves into the radiation pattern synthesis of reconfigurable intelligent surfaces (RIS) / reflection metasurfaces.
DRL-Based Sidelobe Suppression for Multi-focus Reconfigurable Intelligent Surface
Reconfigurable intelligent surface (RIS) technology is receiving significant attention as a key enabling technology for 6G communications, with much attention given to coverage infill and wireless power transfer.
A DRL-based Reflection Enhancement Method for RIS-assisted Multi-receiver Communications
In reconfigurable intelligent surface (RIS)-assisted wireless communication systems, the pointing accuracy and intensity of reflections depend crucially on the 'profile,' representing the amplitude/phase state information of all elements in a RIS array.
Transmit Power Control for Indoor Small Cells: A Method Based on Federated Reinforcement Learning
The model will also be used as the base model for adaptive training in the new environment.
Variational Autoencoder Assisted Neural Network Likelihood RSRP Prediction Model
Measuring customer experience on mobile data is of utmost importance for global mobile operators.
Sim2real for Reinforcement Learning Driven Next Generation Networks
One of the main reasons is the modelling gap between the simulation and the real environment, which could make the RL agent trained by simulation ill-equipped for the real environment.
RLOps: Development Life-cycle of Reinforcement Learning Aided Open RAN
We provide a taxonomy for the challenges faced by ML/RL models throughout the development life-cycle: from the system specification to production deployment (data acquisition, model design, testing and management, etc.).
Deep Transfer Learning for WiFi Localization
Finally, an ablation study of the training dataset shows that, in both office and sport hall scenarios, after reusing the feature extraction layers of the base model, only 55% of the training data is required to obtain the models' accuracy similar to the base models.
Non-Asymptotic Converse Bounds Via Auxiliary Channels
This paper presents a new derivation method of converse bounds on the non-asymptotic achievable rate of discrete weakly symmetric memoryless channels.
Information Theory Information Theory
Wireless Localisation in WiFi using Novel Deep Architectures
Meanwhile, using a well-organised architecture, the neural network models can be trained directly with raw data from the CSI and localisation features can be automatically extracted to achieve accurate position estimates.
