Automatic modulation classification (AMC) involves extracting a set of unique features from the received signal. Accuracy and uniqueness of the features along with the appropriate classification algorithm determine the overall performance of AMC systems. Accuracy of any modulation feature is usually limited by the blindness of the signal information such as carrier frequency, symbol rate etc. Most papers do not sufficiently consider these impairments and so do not directly target practical applications. The AMC system proposed herein is trained with probable input signals, and the appropriate decision tree should be chosen to achieve robust classification. Six unique features are used to classify eight analog and digital modulation schemes which are widely used by low frequency mobile emergency radios around the globe. The Proposed algorithm improves the classification performance of AMC especially for the low SNR regime.

With a view toward the improvement of life-saving rate, the advancement of emergency radio system was attempted. The telemetry technique was introduced to the mobile communication from a running ambulance. A system was newly developed which enables us to transmit the information of an emergency patient from an ambulance to an emergency room of a hospital. This system can transmit an audio signal, physiological signals such as an ECG and a blood oxygen level, as well as a color image. In the experiment, the feasibility of this technique was verified. In the test of its practical usefulness, the following points were evaluated using a mobile telephone line and an emergency radio link. With the regular condition of the communication link, the stability of signal transmission was reasonably well. The fidelity of the transmitted signal was satisfactory for the use of an emergency medicine.