A Study of Throughput-Drop Estimation Model for Concurrently Communicating Two Links without Channel Bonding in IEEE 802.11n Wireless Local-Area Network

Ismael Munene Kwenga, Nobuo Funabiki, Rahardhita Widyatra Sudibyo, Hendy Briantoro, Md Mahbubur Rahman, Wen Chung Kao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Nowadays, IEEE802.11n wireless local-area networks (WLANs) have been widely deployed due to its high-speed data transmission. The channel bonding is one of the key technologies to realize it. However, the data transmission throughput can be dropped when nearby multiple links are concurrently communicating, caused by interference. Previously, we have studied the throughput-drop estimation model for the links using the channel bonding, which considers the channel distance and the received signal strength (RSS) of the interfered links. In this paper, we further explore the throughput-drop estimation model for concurrently communicating two links without the channel bonding by extending the previous model. The effectiveness of the proposal is confirmed through experiments where the estimated throughput well matches the measured throughput.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728173993
DOIs
Publication statusPublished - Sep 28 2020
Event7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 - Taoyuan, Taiwan, Province of China
Duration: Sep 28 2020Sep 30 2020

Publication series

Name2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

Conference

Conference7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
Country/TerritoryTaiwan, Province of China
CityTaoyuan
Period9/28/209/30/20

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Artificial Intelligence
  • Computer Science Applications
  • Signal Processing
  • Electrical and Electronic Engineering
  • Instrumentation

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