Prediksi Channel Gain Threshold untuk Modulasi Adaptif V2V menggunakan Algoritma Random Forest Regression

NAZMIA KURNIAWATI, AISYAH NOVFITRI, YULI KURNIA NINGSIH

Sari


ABSTRAK

Kondisi kendaraan yang saling bergerak pada sistem komunikasi Vehicle-to-Vehicle (V2V) menyebabkan daya sinyal yang diterima berfluktuasi. Selain itu, dengan adanya pergeseran frekuensi Doppler mengakibatkan semakin sulitnya menjaga level Bit Error Rate (BER) kurang dari 0,001. Mengubah threshold channel gain pada modulasi adaptif adalah salah satu metode yang dapat diterapkan untuk menjaga level performansi tanpa mengorbankan nilai Signal to Noise Ratio (SNR). Sayangnya threshold yang memberikan SNR optimal belum diketahui. Pada penelitian ini digunakan algoritma random forest regression untuk mencari nilai threshold channel gain demi didapatkannya nilai SNR terbaik. Dari hasil prediksi dengan jumlah estimator sebanyak 7, didapatkan threshold 0.1 dan 0.3 hanya membutuhkan SNR sebesar 25.59 dB untuk menjaga BER di level
< 0.001.

Kata kunci: Modulasi Adaptif, Pergeseran Doppler, Random Forest Regression

 

ABSTRACT

The condition of the moving vehicles in the Vehicle-to-Vehicle (V2V) communication system leads to fluctuating received signal power. In addition, the Doppler shift increases the difficulty to maintain the Bit Error Rate (BER) less than 0.001. Changing the channel gain threshold in adaptive modulation is one method that can be applied to maintain the performance level without sacrificing the Signal to Noise Ratio (SNR) value. Unfortunately, the threshold that provides the optimal SNR is not yet known. In this research, a random forest regression algorithm is used to determine the channel gain threshold in order to obtain the best SNR value. Based on the prediction results the number of estimators of 7, it is obtained that the thresholds of 0.1 and 0.3 only require an SNR of 25.59 dB to keep the BER at the level < 0.001.

Keywords: Adaptive Modulation, Doppler Shift, Random Forest Regression


Kata Kunci


Modulasi Adaptif; Pergeseran Doppler; Random Forest Regression

Teks Lengkap:

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Referensi


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DOI: https://doi.org/10.26760/elkomika.v10i3.544

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