A Reinforcement Learning-Based Configuring Approach in Next-Generation Wireless Networks Using Software-Defined Metasurface

Table 1

Summary of the main adaptive configuration approaches for PWE tiles.

Reference	Approach	Discussion
Liaskos et al. [16]	Genetic algorithm (GA)	This approach cannot adaptively reconfigure the tiles functionality as soon as the environment changes.
Liaskos et al. [9]	Neural network	This approach considered a problem with only one user.
Liaskos et al. [17]	Graph model	This approach is time-consuming to reconfigure the states of the tiles when the environment changes.
This work	RL	This approach can adaptively reconfigure the states of the tiles when the environment changes in presence of multiple users.