IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 12, No 2: June 2023

Spectrum sensing using 16-QAM and 32-QAM modulation techniques at different signal-to-noise ratio: a performance analysis

Neha Chaudhary (Manav Rachna International Institute of Research and Studies)
Rashima Mahajan (Manav Rachna International Institute of Research and Studies)



Article Info

Publish Date
01 Jun 2023

Abstract

Spectrum sensing techniques are implemented for effective use of spectrum resources in the cognitive-radio. In this research work attempt has been made for the performance of energy detector with cooperative spectrum sensing using double dynamic threshold on the MATLAB software. Additive white gaussian noise is used and the frequency range between 54 MHz to 862 MHz is considered with wideband. Findings in receiver operative curve have been observed to analyze probability-of-detection (????????) under different values of probability-of-false alarm (????????) condition and diverse ranges of signal to noise ratio with different number of samples of input signal. Presence and absence of primary user has been marked by using a hypothetical model based on Neyman pearson approach. From the results, it has been observed that more the number of sample values, better is the probability-of-detection (????????) value as achieved for 32-QAM signal as compared to 16-QAM signal. Also, better results have been witnessed at -9db signal to noise ratio value as compared to -15db and -20db. This work provides almost 10% of enhancement in the probability of detection at -9db signal to noise ratio for 16-QAM modulated signal as compared to the existing model where the implementation of energy detector spectrum sensing technique through simulink model.

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Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...