AUTOMATIC MODULATION CLASSIFICATION BASED ON STATISTICAL FEATURES AND SUPPORT VECTOR MACHINE| Session Chair: | Yves Louët |
Cognitive radio has emerged as one of the most promising paradigms for efficient utilization of the radio spectrum. Still, a number of functions that any cognitive radio terminal has to accomplish are the subject of intense research. We think of spectrum sensing, of signal feature recognition, of the different criteria to authorize the use of the available bandwidth, and of the (dynamic) signal design criteria to optimize the exploitation of the spectrum resources. The session will also discuss particular criteria to design cognitive terminals, like software-defined or flexible radio.
8:00 C01.1 AUTOMATIC MODULATION CLASSIFICATION BASED ON STATISTICAL FEATURES AND SUPPORT VECTOR MACHINE
W. Zhang
Science and Technology on Communication Information Security Control Laboratory, Zhejiang, China
8:20 C01.2 EARLY RESULTS ON THE DESIGN OF ADAPTIVE EQUALIZER FOR HF COMMUNICATIONS SYSTEM ON EQUATORIAL REGION
D. Brilyantarto, I. Kurniawati, G. Hendrantoro
Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, East Java, Indonesia
8:40 C01.3 EFFECTIVE CAPACITY ANALYSIS IN UNDERLAY COOPERATIVE COGNITIVE RADIO NETWORK
R. Li1, J. Li2
1Dept. Beijing Monitoring Station, The State Radio Monitoring Center, Beijing, China
2Dept. Research and development, The State Radio_monitoring_center Testing Center, Beijing, China
9:00 C01.4 TACTICAL DATA LINK SIMULATOR WITH COGNITIVE ANTI-JAMMING CAPABILITY
S. Choe, E. Ko, J. Lee
Department of Information, Communications & Electronics Engineering, The Catholic University of Korea, Bucheon, South Korea