Hybrid NOMA Protocol with Relay Adaptive AF/DF Collaboration and Its Modeling Analysis in NB-IoT

Author:

Li Suoping12,Gao Ruiman1,Jia Tongtong1,Yang Hailing1,Yang Sa2

Affiliation:

1. School of Sciences, Lanzhou University of Technology, Lanzhou 730050, China

2. School of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China

Abstract

In order to meet the demand for large-scale device access in Narrowband Internet of Things (NB-IoT) and to overcome the problem that some resources are wasted due to the use of single decode-and-forward (DF) or amplify-and-forward (AF) collaboration in traditional collaborative communication, this paper introduces a non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) hybrid access method into the NB-IoT and proposes a new Hybrid NOMA transmission protocol with relay adaptively selectable collaboration, which is represented as an algorithm. Based on this protocol, we classify the whole transmission process into five states after deriving the outage probability of each link. We then consider the system as a discrete-time Markov model, the closed expressions of the system outage probability and throughput are derived based on the system steady-state probability. In order to improve the system’s reliability, we further optimize the above protocol by allowing the source node to retransmit the unsuccessful received superimposed signals a limited number of times. Numerical results and simulations show that the outage probability is lower when multiple retransmissions are possible. The proposed relay adaptive collaborative hybrid NOMA transmission protocol has advantages over the pure OMA transmission mode.

Funder

National Natural Science Foundation of China

Lanzhou University of Technology

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3