Deep Reinforcement Learning For Distributed Uncoordinated Cognitive Radios Resource Allocation

Abstract

This paper presents a novel deep reinforcement learning-based resource allocation technique for the multi-agent environment presented by a cognitive radio network that coexists through underlay dynamic spectrum access (DSA) with a primary network. The resource allocation technique presented in this work is distributed, not requiring coordination with other agents. The presented algorithm is the first deep reinforcement learning technique for which convergence to equilibrium policies can be shown in the non-stationary multi-agent environment that results from the uncoordinated dynamic interaction between radios through the shared wireless environment. Moreover, simulation results show that in a finite learning time the presented technique is able to find policies that yield performance within 3 % of an exhaustive search solution, finding the optimal policy in nearly 70 % of cases. Moreover, it is shown that standard single-agent deep reinforcement learning may not achieve convergence wh

Stats

• citations0
• S2 citations—
• github stars0
• HF likes0
• heat score0.00
• arxiv keytondwalkar2019deep

Related papers

• Deep Reinforcement Learning For Distributed And Uncoordinated Cognitive Radios Resource Allocation (2022)0.00
• Resource Management In Wireless Networks Via Multi-agent Deep Reinforcement Learning (2020)16.43
• Deep Reinforcement Learning For Joint Spectrum And Power Allocation In Cellular Networks (2020)0.00
• Cooperative Multi-agent Reinforcement Learning For Low-level Wireless Communication (2018)0.00
• Offline And Distributional Reinforcement Learning For Radio Resource Management (2024)0.00
• Dynamics Of Resource Allocation In O-rans: An In-depth Exploration Of On-policy And Off-policy Deep Reinforcement Learning For Real-time Applications (2024)2.26
• A Multi-task Approach To Robust Deep Reinforcement Learning For Resource Allocation (2023)0.00
• Implications Of Decentralized Q-learning Resource Allocation In Wireless Networks (2017)0.00