A Simulation Model for Nakagmi-m Fading Channel with m>1
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2015, Vol 6, Issue 10
Abstract
In this paper, we propose a model to simulate a wireless fading channel based on Nakagami-m distribution with m>1. The Nakagami-m fading channel is the most generalized distribution as it can generate one-sided Gaussian distribution, Rayleigh distribution and Rician distribution for m equals to 0.5, 1 and >1 respectively. In this work we have proposed a method to generate a wireless fading channel based on Nakagami-m distribution as this distribution fits to a wide class of fading channel conditions. Simulation results were obtained using Matlab R2013a and compared with the analytical results.
Authors and Affiliations
Sandeep Sharma, Rajesh Mishra
Keywords
Related Articles
- EP ID EP143465
- DOI 10.14569/IJACSA.2015.061040
- Views 123
- Downloads 0
SmartFit: A Step Count Based Mobile Application for Engagement in Physical Activities
Research has found that relatively few people en-gage in regular exercise or other physical activities. Despite the availability of numerous mobile applications and specialized devices for self-tracking, people mostly la...
A multi-scale method for automatically extracting the dominant features of cervical vertebrae in CT images
Localization of the dominant points of cervical spines in medical images is important for improving the medical automation in clinical head and neck applications. In order to automatically identify the dominant points of...
Forecasting Feature Selection based on Single Exponential Smoothing using Wrapper Method
Feature selection is one way to simplify classification process. The purpose is only the selected features are used for classification process and without decreasing its performance when compared without feature selectio...
Intrusion Detection System with Correlation Engine and Vulnerability Assessment
The proposed Intrusion Detection System (IDS) which is implemented with modern technologies to address certain prevailing problems in existing intrusion detection systems’ is capable of giving an advanced output to the s...
Efficient MRI Segmentation and Detection of Brain Tumor using Convolutional Neural Network
Brain tumor is one of the most life-threatening diseases at its advance stages. Hence, detection at early stages is very crucial in treatment for improvement of the life expectancy of the patients. magnetic resonance ima...