Robotic Mobile System's Performance-Based MIMO-OFDM Technology
Dublin Core
Title
Robotic Mobile System's Performance-Based MIMO-OFDM Technology
Subject
Neural Network
LDPC codes
Robot
MIMO
and OFDM
Description
In this paper, a predistortion neural network (PDNN) architecture has been imposed to the Sniffer Mobile Robot (SNFRbot) that is based on spatial multiplexed wireless Orthogonal Frequency Division Multiplexing (OFDM) transmission technology. This proposal is used to improve the system performance by combating one of the main drawbacks that is encountered by OFDM technology; Peak-to-Average Power Ratio (PAPR). Simulation results show that using PDNN resulted in better PAPR performance than the previously published work that is based on linear coding, such as Low Density Parity Check (LDPC) codes and turbo encoding whether using flat fading channel or a Doppler spread channel.
Creator
Daoud, Omar
Alani, Omar
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 3 (2009): Special Issue: Technical Basics; pp. 12-17
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2009-10-27
Rights
Copyright (c) 2017 Omar Daoud, Omar Alani
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Identifier
Citation
Omar Daoud and Omar Alani, Robotic Mobile System's Performance-Based MIMO-OFDM Technology, International Association of Online Engineering (IAOE), Vienna, Austria, 2009, accessed November 6, 2024, https://igi.indrastra.com/items/show/916