Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach

Overview

Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach

Thanh Luan Nguyen, Tri Nhu Do, Georges Kaddoum

Abstract

In this paper, we aim to improve the connectivity, scalability, and energy efficiency of machine-type communication (MTC) networks with different types of MTC devices (MTCDs), namely Type-I and Type-II MTCDs, which have different communication purposes. To this end, we propose two transmission schemes called connectivityoriented machine-type communication (CoM) and quality-oriented machine-type communication (QoM), which take into account the stochastic geometry-based deployment and the random active/inactive status of MTCDs. Specifically, in the proposed schemes, the active Type-I MTCDs operate using a novel Bernoulli random process-based simultaneous wireless information and power transfer (SWIPT) architecture. Next, utilizing multi-user power-domain non-orthogonal multiple access (PD-NOMA), each active Type-I MTCD can simultaneously communicate with another Type-I MTCD and a scalable number of Type-II MTCDs. In the performance analysis of the proposed schemes, we prove that the true distribution of the received power at a Type-II MTCD in the QoM scheme can be approximated by the Singh-Maddala distribution. Exploiting this unique statistical finding, we derive approximate closed-form expressions for the outage probability (OP) and sum-throughput of massive MTC (mMTC) networks. Through numerical results, we show that the proposed schemes provide a considerable sum-throughput gain over conventional mMTC networks.

Paper

Bibtex

If you find that our research is interesting and our code is helpful, please cite our paper. Thank you!

@article{DoTCOM2021,
	author = {Nguyen, Thanh Luan and Do, Tri Nhu and Kaddoum, Georges.},
	title = {Performance {A}nalysis of {M}ulti-user {NOMA} {W}ireless-{P}owered m{MTC} {N}etworks: {A} {S}tochastic {G}eometry {A}pproach},
	journal = {IEEE Transactions on Communications},
	year = {2022},
}
Owner
Thanh Luan Nguyen
Thanh Luan Nguyen
Code for the ACL2021 paper "Lexicon Enhanced Chinese Sequence Labelling Using BERT Adapter"

Lexicon Enhanced Chinese Sequence Labeling Using BERT Adapter Code and checkpoints for the ACL2021 paper "Lexicon Enhanced Chinese Sequence Labelling

274 Dec 06, 2022
This is a package for LiDARTag, described in paper: LiDARTag: A Real-Time Fiducial Tag System for Point Clouds

LiDARTag Overview This is a package for LiDARTag, described in paper: LiDARTag: A Real-Time Fiducial Tag System for Point Clouds (PDF)(arXiv). This wo

University of Michigan Dynamic Legged Locomotion Robotics Lab 159 Dec 21, 2022
classification task on dataset-CIFAR10,by using Tensorflow/keras

CIFAR10-Tensorflow classification task on dataset-CIFAR10,by using Tensorflow/keras 在这一个库中,我使用Tensorflow与keras框架搭建了几个卷积神经网络模型,针对CIFAR10数据集进行了训练与测试。分别使

3 Oct 17, 2021
A time series processing library

Timeseria Timeseria is a time series processing library which aims at making it easy to handle time series data and to build statistical and machine l

Stefano Alberto Russo 11 Aug 08, 2022
"Exploring Vision Transformers for Fine-grained Classification" at CVPRW FGVC8

FGVC8 Exploring Vision Transformers for Fine-grained Classification paper presented at the CVPR 2021, The Eight Workshop on Fine-Grained Visual Catego

Marcos V. Conde 19 Dec 06, 2022
Fine-grained Post-training for Improving Retrieval-based Dialogue Systems - NAACL 2021

Fine-grained Post-training for Multi-turn Response Selection Implements the model described in the following paper Fine-grained Post-training for Impr

Janghoon Han 83 Dec 20, 2022
Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks.

Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks. Generally, we intergrete different kind of functional

28 Jan 08, 2023
Neural networks applied in recognizing guitar chords using python, AutoML.NET with C# and .NET Core

Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows

Andres Mauricio Rondon Patiño 24 Oct 22, 2022
SSD: Single Shot MultiBox Detector pytorch implementation focusing on simplicity

SSD: Single Shot MultiBox Detector Introduction Here is my pytorch implementation of 2 models: SSD-Resnet50 and SSDLite-MobilenetV2.

Viet Nguyen 149 Jan 07, 2023
Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding

2D-TAN (Optimized) Introduction This is an optimized re-implementation repository for AAAI'2020 paper: Learning 2D Temporal Localization Networks for

Joya Chen 112 Dec 31, 2022
Python binding for Khiva library.

Khiva-Python Build Documentation Build Linux and Mac OS Build Windows Code Coverage README This is the Khiva Python binding, it allows the usage of Kh

Shapelets 46 Oct 16, 2022
ExCon: Explanation-driven Supervised Contrastive Learning

ExCon: Explanation-driven Supervised Contrastive Learning Link to the paper: https://arxiv.org/pdf/2111.14271.pdf Contributors of this repo: Zhibo Zha

Zhibo (Darren) Zhang 18 Nov 01, 2022
Oscar and VinVL

Oscar: Object-Semantics Aligned Pre-training for Vision-and-Language Tasks VinVL: Revisiting Visual Representations in Vision-Language Models Updates

Microsoft 938 Dec 26, 2022
Python implementation of cover trees, near-drop-in replacement for scipy.spatial.kdtree

This is a Python implementation of cover trees, a data structure for finding nearest neighbors in a general metric space (e.g., a 3D box with periodic

Patrick Varilly 28 Nov 25, 2022
General Assembly Capstone: NBA Game Predictor

Project 6: Predicting NBA Games Problem Statement Can I predict the results of NBA games from the back-half of a season from the opening half of the s

Adam Muhammad Klesc 1 Jan 14, 2022
MVP Benchmark for Multi-View Partial Point Cloud Completion and Registration

MVP Benchmark: Multi-View Partial Point Clouds for Completion and Registration [NEWS] 2021-07-12 [NEW 🎉 ] The submission on Codalab starts! 2021-07-1

PL 93 Dec 21, 2022
'Aligned mixture of latent dynamical systems' (amLDS) for stimulus decoding probabilistic manifold alignment across animals. P. Herrero-Vidal et al. NeurIPS 2021 code.

Across-animal odor decoding by probabilistic manifold alignment (NeurIPS 2021) This repository is the official implementation of aligned mixture of la

Pedro Herrero-Vidal 3 Jul 12, 2022
OpenLT: An open-source project for long-tail classification

OpenLT: An open-source project for long-tail classification Supported Methods for Long-tailed Recognition: Cross-Entropy Loss Focal Loss (ICCV'17) Cla

Ming Li 37 Sep 15, 2022
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

Meta Research 283 Dec 30, 2022
NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch

NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch, train it, collect statistics, and share it among the members of the community. It is not just a visual

HTM Community 93 Sep 30, 2022