Multi-Agent Deep Stochastic Policy Gradient for Event Based Dynamic Spectrum Access

04/06/2020
by   Rahif Kassab, et al.
0

We consider the dynamic spectrum access (DSA) problem where K Internet of Things (IoT) devices compete for T time slots constituting a frame. Devices collectively monitor M events where each event could be monitored by multiple IoT devices. Each device, when at least one of its monitored events is active, picks an event and a time slot to transmit the corresponding active event information. In the case where multiple devices select the same time slot, a collision occurs and all transmitted packets are discarded. In order to capture the fact that devices observing the same event may transmit redundant information, we consider the maximization of the average sum event rate of the system instead of the classical frame throughput. We propose a multi-agent reinforcement learning approach based on a stochastic version of Multi-Agent Deep Deterministic Policy Gradient (MADDPG) to access the frame by exploiting device-level correlation and time correlation of events. Through numerical simulations, we show that the proposed approach is able to efficiently exploit the aforementioned correlations and outperforms benchmark solutions such as standard multiple access protocols and the widely used Independent Deep Q-Network (IDQN) algorithm.

READ FULL TEXT
research
09/14/2022

Joint User and Data Detection in Grant-Free NOMA with Attention-based BiLSTM Network

We consider the multi-user detection (MUD) problem in uplink grant-free ...
research
01/08/2021

Hermes: Decentralized Dynamic Spectrum Access System for Massive Devices Deployment in 5G

With the incoming 5G network, the ubiquitous Internet of Things (IoT) de...
research
03/29/2021

Deep reinforcement learning of event-triggered communication and control for multi-agent cooperative transport

In this paper, we explore a multi-agent reinforcement learning approach ...
research
03/29/2021

Lifelong Learning for Minimizing Age of Information in Internet of Things Networks

In this paper, a lifelong learning problem is studied for an Internet of...
research
09/17/2021

Coordinated Random Access for Industrial IoT With Correlated Traffic By Reinforcement-Learning

We propose a coordinated random access scheme for industrial internet-of...
research
01/27/2021

Joint Source-Channel Coding for Semantics-Aware Grant-Free Radio Access in IoT Fog Networks

A fog-radio access network (F-RAN) architecture is studied for an Intern...
research
10/07/2021

Distributed Proximal Policy Optimization for Contention-Based Spectrum Access

The increasing number of wireless devices operating in unlicensed spectr...

Please sign up or login with your details

Forgot password? Click here to reset