Forecaster-Aided User Association and Load Balancing in Multi-Band Mobile Networks
Cellular networks are becoming increasingly heterogeneous with higher base station (BS)
densities and ever more frequency bands, making BS selection and band assignment key …
densities and ever more frequency bands, making BS selection and band assignment key …
Learning-based model predictive control for user association in multi-band mobile networks
As cellular networks embrace heterogeneity with higher base station (BS) densities and ever
more frequency bands, BS selection and band assignment become increasingly key …
more frequency bands, BS selection and band assignment become increasingly key …
Smooth Handovers via Smoothed Online Learning
With users demanding seamless connectivity, handovers (HOs) have become a
fundamental element of cellular networks. However, optimizing HOs is a challenging …
fundamental element of cellular networks. However, optimizing HOs is a challenging …
Parallel Digital Twin-driven Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks
Optimization of user association in a densely deployed heterogeneous cellular network is
usually challenging and even more complicated due to the dynamic nature of user mobility …
usually challenging and even more complicated due to the dynamic nature of user mobility …
A Differentiable Throughput Model for Load-Aware Cellular Network Optimization Through Gradient Descent
The efficient operation of cellular networks requires careful tuning of configuration
parameters, such as the transmit power or antenna tilts, to adequately balance interference …
parameters, such as the transmit power or antenna tilts, to adequately balance interference …
Map2Traj: Street Map Piloted Zero-shot Trajectory Generation with Diffusion Model
User mobility modeling serves a crucial role in analysis and optimization of contemporary
wireless networks. Typical stochastic mobility models, eg, random waypoint model and …
wireless networks. Typical stochastic mobility models, eg, random waypoint model and …
Communication Load Balancing via Efficient Inverse Reinforcement Learning
Communication load balancing aims to balance the load between different available
resources, and thus improve the quality of service for network systems. After formulating the …
resources, and thus improve the quality of service for network systems. After formulating the …
Data-driven design for multihop and multi-band cellular networks
M Gupta - 2023 - repositories.lib.utexas.edu
Millimeter wave (mmWave) integrated access and backhaul (IAB) and multiband
heterogeneous networks allow operators to avail more spectral resources and keep up with …
heterogeneous networks allow operators to avail more spectral resources and keep up with …