Multi-Antenna Communication Receivers Using Metaheuristics and Machine Learning Algorithms

Multi-Antenna Communication Receivers Using Metaheuristics and Machine Learning Algorithms

In this thesis, our focus is on low-complexity, high-performance detection algorithms for multi-antenna communication receivers. A key contribution in this thesis is the demonstration that efficient algorithms from metaheuristics and machine learning can be gainfully adapted for signal detection in...

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Bibliographic Details
Main Author: Nagaraja, Srinidhi
Other Authors: Chockalingam, A
Language:en_US
Published: 2018
Subjects:
Multi Antenna Communication Receivers
Machine Learning Algorithms
Wireless Communication Systems
Multiple-Input Multiple-Output (MIMO) Systems
Reactive Tabu Search (RTS)
Linear Regression MMSE Residual Recivers (LRR)
Metaheuristics
Tabu Search Algorithm
Multi Antenna Communication Systems
MIMO Systems
MMSE Residual
MMSE Recivers
Minimum Mean Square Error
Communication Engineering
Online Access:http://etd.iisc.ernet.in/2005/3442
http://etd.iisc.ernet.in/abstracts/4309/G25963-Abs.pdf

Internet

http://etd.iisc.ernet.in/2005/3442
http://etd.iisc.ernet.in/abstracts/4309/G25963-Abs.pdf

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