DeepAI
Log In Sign Up

An Intelligent Future Mobile Terminal Architecture

01/06/2018
by   Muhammad Bilal, et al.
1

In this paper, a novel Extended Cognitive Mobile Terminal (ExCogNet-MT) scheme is presented. In this scheme, a "test bench" at receiver's Mobile Terminal (MT) can estimate the channel Signal to Noise Ratio (SNR) and can detect the jamming signal. The estimation scheme compares the Standard Deviation (SD) of received signal and processed signal, and on the bases of this comparison the "test bench" can determine the BER and corresponding SNR value of the channel. Simulation results demonstrated that under certain scenarios estimated SNR value can be helpful for tuning the parameters of protocol stack of 802.11a and WiMaxm.

READ FULL TEXT

page 1

page 2

page 3

page 4

01/30/2021

SNR-adaptive deep joint source-channel coding for wireless image transmission

Considering the problem of joint source-channel coding (JSCC) for multi-...
04/21/2018

Capacity of Multiple One-Bit Transceivers in a Rayleigh Environment

We analyze the channel capacity of a system with a large number of one-b...
03/20/2020

A Blind Signal Separation Algorithm for Energy Detection of Dynamic PU Signals

Energy detection process for enabling opportunistic spectrum access in d...
12/26/2019

Efficient Training of Deep Classifiers for Wireless Source Identification using Test SNR Estimates

We investigate the potential of training time reduction for deep learnin...
05/24/2022

GMM-based Codebook Construction and Feedback Encoding in FDD Systems

We propose a precoder codebook construction and feedback encoding scheme...
03/07/2018

An iALM-ICA-based Anti-Jamming DS-CDMA Receiver for LMS Systems

We consider a land mobile satellite communication system using spread sp...
04/13/2022

Estimation of stellar atmospheric parameters from LAMOST DR8 low-resolution spectra with 20≤SNR<30

The accuracy of the estimated stellar atmospheric parameter decreases ev...