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

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