Penentuan Batas Gain Kanal Modulasi Adaptif V2V dengan Doppler Shift yang Bervariasi Menggunakan Machine Learning

Abstract

Doppler shift is a phenomenon that occurs when the vehicle is moving. The effect of Doppler shift is a degradation in performance of Vehicle to Vehicle (V2V) communication. Adaptive modulation is a technique to improve the performance. It is done by adjusting the modulation scheme used according to noise conditions while keeping the Bit Error Rate (BER) value not exceeding 10-3. In this research, three Doppler shift values are used. The shift is derived from speed limit determined by The Government of Indonesia. Then machine learning algorithm is used to predict channel gain threshold that can optimize the use of Signal to Noise Ratio (SNR) with a BER limit of 10-3. From the prediction results, it is found that by implementing the predicted channel gain threshold, the SNR required by adaptive modulation has the lowest value compared to non-adaptive modulation schemes. The lower the required SNR value, the communication is more resistant to noise interference.