Research On Spectrum Detection Methods Of The Active Anti-interference Receiver

The next generation wireless communications systems require transmission at higher data rates in order to meet the higher demand of quality services. Wireless technology makes a variety of applications and services extensive and developed rapidly, in order to cope with the growing demand and a growing scarcity of wireless spectrum, requiring the radio device has to share and re-use the spectrum resources. Cognitive radio is such a technology, it can intellisenses spectrum environment, and continuously adjusts the system parameters based on the requirements of the network performance, to improves the spectral efficiency of the communication systems. Therefore, this thesis was researched about the active anti-interference mobile receivers based on cognitive radio. The receivers can receive a variety of signals from different communication systems or different types of business,and select the appropriate multi-user detection method according to the different types of the received signals. The spectrum detections of cognitive radio in this thesis studied.This thesis introduced the system model of active anti-interference receivers and the working principles firstly, secondly, the basic principles and the key technology of cognitive radio was studied, especially the spectrum efficiency of the cognitive radio was researched systematicly. Nowdays, spectrum detection methods includes single node and multi-nodes spectrum detection, the single node spectrum detections include the transmitter spectrum sensing of main users,and the receivers spectrum sensing of main users, multi-nodes spectrum sensing is the cooperative spectrum detection. The transmitter spectrum sensing of main users includes matched filtering detection, energy detection and cyclostationary feature detection. Primary user receivers detections include the detection of the LO leakage power and the detection based on interference temperature. They have their different advantages and disadvantages, matched filter detection is the best method of signal detection, but it needs the known types of modulation, pulse shaping, and prior knowledge of the frame formats of main users; energy detection does not require the known information of primary users, and it is not only applied to any signal, but also the easiest measure, it can only detect whether the signal,but can not detect the type of signals, cyclostationary feature detection method has the advantage of high detection accuracy, but the complexity is high; the detection range for the LO leakage power detection algorithm is relatively small and requires relatively long testing time; spectrum detection algorithm based on interference temperature dependes on power spectrum estimation, the computational complexity is too high. Under the existing method of spectrum detection of defects and shortcomings, we studied the signal noise subspace theory, the spectrum detection based on subspace tracking method can not only detect the primary user signals and the signals can be restored. Finally, on MATLAB simulation platform, several different signals are used in subspace tracking-based detection method of spectrum simulation, the simulation results are obtained and the detection performance is analyzed. The simulation results show that the spectrum detection based on subspace tracking is an excellent spectrum detection method.