• Anuska Gayen
• Aman Singh
• Sandhya Pattanayak
• Nimish Adarsh
• Rajdip Sen, Ratul Singha

Automatic Modulation Classification (AMC) is an important stage in the intelligent wireless communications receiver; it is a necessary process after signal detection and before the demodulation. It plays a vital role in various applications. Blind modulation classification is a very difficult task with no information of the transmitted signal and receiver parameters like carrier frequency, signal power, timing information, phase offsets, and so on. Along with existing of frequency-selective, multipath fading, and time-varying channels in real-world applications. The Automatic Modulation Classification (AMC) techniques are divided into traditional methods and advanced methods. Traditional methods including Likelihood-Based (LB) and Feature-Based (FB). The advanced methods such as Deep Learning (DL). Automatic modulation classification plays a crucial role in the field of telemedicine, where reliable and real-time communication between healthcare providers and patients is essential. With the advancement of wireless communication technologies, telemedicine has become more accessible, allowing patients to receive medical care remotely. Automatic modulation classification enables the identification of different modulation schemes used in wireless communication systems, ensuring efficient and accurate data transmission in telemedicine applications. This paper focused on summarizing the role of automatic modulation classification techniques, compares these techniques, surveys the commercial software packages for the AMC process, and finally considers the new challenges in practice.

Automatic Modulation Classification (AMC), Deep Learning (DL), Feature-Based (FB) method, Likelihood-Based (LB) method, Telemedicine.

"Automatic Modulation Classification: An Optimal Approach For Telemedicine", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.h467-h471, June-2024, Available :http://www.jetir.org/papers/JETIR2406752.pdf

"Automatic Modulation Classification: An Optimal Approach For Telemedicine", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pph467-h471, June-2024, Available at : http://www.jetir.org/papers/JETIR2406752.pdf