有关认知无线电频谱感知算法的入门教程-简单易懂-配合其中提到的论文可以掌握频谱感知算法的基础.pptVIP

CHAPTER 5. SPECTRUM SENSING What is Spectrum Sensing ? Spectrum Sensing EFFICIENT WAY TO DETECT SPECTRUM HOLES !! Detect primary users that are receiving data within the communication range of a CR user. In reality ? Difficult for a CR to detect primary user activity in the absence of interaction between primary users and itself. RECENT RESEARCH ? How to detect primary users based on “local observation” of CR users (from its environment) Classification of Spectrum Sensing Techniques Transmitter Detection CR should distinguish between Used and Unused spectrum bands. CR should have the capability to determine if a signal from primary user (transmitter) is locally present in a certain spectrum. Transmitter Detection Approach ? Detection of the signal (weak signal as the worst case) from a primary user through local observations of CR users. Basic Hypothesis Model for Transmitter Detection The signal r(t) received (detected) by the CR (secondary) user is Transmitter Detection Three schemes are generally used for the transmitter detection according to the hypothesis model. Matched Filter Detection Energy Detection and Cyclostationary Feature Detection Techniques Matched Filter Detection Matched Filter Detection Matched Filter Detection When the shape of the primary user signal is known to the CR user, the optimal detector in an AWGN channel is the matched filter since it maximizes the received SNR. Advantage of Matched Filter: Requires less time to achieve high processing gain due to coherency Matched Filter Detection But it requires a priori knowledge of the primary user signal such as the modulation type and order, the pulse shape, and the packet format Hence, if this information is not accurate, then the matched filter performs poorly. However, since most wireless network systems have pilot, preambles, synchronization word or spreading codes, these can be used for the coherent de