Two-Sided Learning for NOMA-Based Random Access in IoT Networks

Jinho Choi

doi:10.1109/access.2021.3076771

Abstract

In the Internet-of-Things (IoT), different types of devices can co-exist within a network. For example, there can be cheap but inflexible devices and flexible devices in terms of radio frequency (RF) capabilities. Thus, in order to support different types of devices in different ways and improve throughput, we propose a multichannel random access scheme based on power-domain non-orthogonal multiple access (NOMA), where each flexible or dynamic device (DD) can dynamically choose one of multiple channels when it has a packet to send. In addition, since DDs need to learn the channel selection probabilities to maximize the throughput of DDs, we consider two-sided learning based on a multi-armed bandit (MAB) formulation where rewards are decided by learning outcomes at a base station (BS) to improve learning speed at DDs. Simulation results confirm that two-sided learning can help improve learning speed at DDs and allows the proposed NOMA-based random access approach to achieve near maximum throughput.

Highlights

In the Internet-of-Things (IoT), a large number of devices including sensors and actuators are to be connected to networks for a number of applications including smart cities and factories [1], [2]
We assume that L = 10 and the static devices (SD) are distributed over L = 10 channels as follows: (S1, . . . , SL ) = (0.3, 0.2, 0.1, 0.1, 0.05, 0.05, 0.02, 0.08, 0.01, 0.09) × M1, where the total number of SDs is set to M1 = 1000
Recall that the multi-armed bandit (MAB) approaches in Subsections IV-B and IV-C are referred to as MABs 1 and 2, respectively

Summary

Introduction

In the Internet-of-Things (IoT), a large number of devices including sensors and actuators are to be connected to networks for a number of applications including smart cities and factories [1], [2]. To allow devices to be connected, IoT connectivity plays a crucial role in the IoT and a number of solutions are studied including WiFi, cellular IoT, low-power wide area networking (LPWAN), and so on [3]. Within a certain geographical area, a number of devices can be deployed to form an IoT network with a base station (BS). In this IoT network, for wireless communications, dedicated licensed bands or unlicensed bands can be used [3], [4] to form multiple channels in order to support a number of devices that can transmit their packets simultaneously. A SD is a low-cost device that only transmits through a pre-determined channel due to limited radio frequency (RF) capability.

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Results

Conclusion