Abstract:   In today’s fast technological advancements, the efficient wireless communication systems has efficient utilisation of available spectrum and minimization of interference in the spectrum.This paper involvesthe analysis and applicability of reinforcement learning (RL) algorithms, namely Q-learning, Deep Q-learning (DQL), and Policy Gradient Methods, in improving spectrum allocation to enhance efficiency and minimizing the interference of the signals in spectrum. Through simulation based evaluation,a comparative study of these Reinforcement Learning techniquesto demonstrate their effectiveness in enhancing spectrum efficiency and reducing interference in wireless networks.