Automatic Modulation Detection Using Non-Linear Transformation Data Extraction And Neural Network Classification

Adaptive Modulation and Coding (AMC) is a system that performed adaptive modulation scheme in which sets of modulation used by the same system adapted to the conditions of the transmission channel. This research want to make an AMC system that can distinguish Amplitude Modulation (AM), Lower Sideband (LSB), Upper Sideband (USB), Binary Phase-shift Keying (BPSK), Quartenary Phase-shift Keying (QPSK), and 8-Phase-shift Keying (8PSK) modulation automatically. AMC has an important role in the military. Modern electronic warfare, called the Electronic Warfare (EW) consists of three main components, these are Electronic Support (ES), Electronic Attack (EA) and Electronic Protect (EP). In electronic support, the main purpose is to collect the information of the received radio signal, so the AMC system can be used for this. With the AMC system, the modulation type is known to do the demodulation process, so the overlapped information can be known. The feature extraction process is one of the most important processes in AMC System. In this research, feature extraction performed is a high-order statistical feature in the time domain. The statistical order used is order 4. Information signals are passed on the transmission channel in the presence of AWGN noise interference with variable signal quality of 0 dB to 40 dB. Artificial neural network algorithm is used to classify modulation with a learning rate of 0.5 and the maximum number of epochs is 1000. By using the 4th order statistical feature, the AMC system on this research can distinguish AM, LSB, USB, BPSK, QPSK, and 8PSK modulation. This research focus on modulation that is used in HF military radio. The accuracy rate of this system in performing modulation classification without using non-linear transformations is 65.5% on 10 dB signal quality. Then, the accuracy of AMC by using non-linear transformations on the received signal reaches 88.8% on the 10 dB signal quality.