Detection Of Modulation Signals Using Cyclostationary Spectral Analysis On Wireless Network

Cyclostationary spectral analysis is widely used in many systems such as Communications, Remote-sensing, Radar, Sonar and so on. As the cyclic statistics can restrain any stationary colored noise, and different modulation signals sometimes have different cyclic spectral correlation functions, this technology has been growing concern in the area of signal detection.The development of wireless communication technologies brings new challenges to the monitoring and management of wireless signals. The realization of the wireless signal detection and identification has two tasks to complete: one is to detect and identify the PSK signals which are widely used in many wireless systems; the other one is to estimate the parameters of DSSS signal without prior knowledge.This paper will use cyclostationary spectral analysis as a research tool to do a number of useful exploratory works on this challenging subject.At first, we introduce the theory of cycle spectrum, discuss the computer simulation method and present some typical signals' spectral correlation functions. Then by analyzing the spectral correlation characteristics of OQPSK signal, we conclude that the cyclostationary spectral analysis can be used to detect and identify OQPSK signal. After the research and the simulation of DS-OQPSK signal, we prove the feasibility of using cyclostationary spectral analysis to estimate the parameters of DS-OQPSK signal without prior knowledge. We use Simulink to simulate IS-95 Reverse Access Channel and cdma2000 Reverse Channel and compare the cyclic spectral correlation functions of the signals generated by these two channels. Results show that cyclostationary spectral analysis can also be used to detect and identify these two signals. At last, we set IEEE 802．11a WLAN wireless signal, which uses OFDM technology, as the study object and the conclusion is of further significance.The results note that cyclostationary spectral analysis can be used to detect and identify several kinds of wireless signals without prior knowledge, and can estimate the signals' parameters.