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.本文由惩戒之疾风贡献 ppt文档可能在WAP端浏览体验不佳。建议您优先选择TXT，或下载源文件到本机查看。 CHAPTER 5. SPECTRUM SENSING IFA2007 COGNITIVE CLASS 1 What is Spectrum Sensing ? How to detect spectrum holes by the COGNITIVE RADIO so that it can adapt itself to its environment ! IFA2007 COGNITIVE CLASS 2 Spectrum Sensing Transmitted Signal Radio Environment RF Stimuli Spectrum Mobility Primary User Detection Decision Request Spectrum Sensing Spectrum Hole Spectrum Sharing Channel Capacity Spectrum Decision IFA2007 COGNITIVE CLASS 3 EFFICIENT WAY TO DETECT SPECTRUM HOLES A general CR based communication scenario CR User 2 No interaction between CR user and Primary Tx/Rx CR user must rely on locally sensed signals to infer primary user activity Licensed band 2 CR User 1 Licensed band 1 Primary Tx Primary Rx Channels found occupied by CR user (Licensed bands 1 and 2) are now avoided during communication between CRs IFA2007 COGNITIVE CLASS 4 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) IFA2007 COGNITIVE CLASS 5 Classification of Spectrum Sensing Techniques Spectrum Sensing Transmitter Detection Receiver Detection Interference Temperature Management Matched Filter Detection Energy Detection Cyclostationary Feature Detection IFA2007 COGNITIVE CLASS 6 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. COGNITIVE CLASS 7 IFA2007 Basic Hypothesis Model for Transmitter Detection The signal r(t) received (detected) by the CR (secondary) user is H0 n(t) r(t) = hs(t) + n(t) H1 where n(t) s(t) AWGN (Additive White Gaussian Noise) Transmitted signal of the primary user Amplitude gain of the channel Null hypothesis No licensed user signal in a certain spectrum band. Alternative hypothesis There exists some licensed user signal. COGNITIVE CLASS h H0 H1 IFA2007 8 Transmitter Detection Sensing for Cognitive Radios, in Proc. 38th Asilomar Conference on Signals, Systems and Computers, pp. 772-776, Nov. 2004. D. Cabric, S. M. Mishra, and R. W. Brodersen, Implementation Issues in Spectrum Three schemes are generally used for the transmitter detection according to the hypothesis model. Matched Filter Detection Energy Detection and Cyclostationary Feature Detection Techniques IFA2007 COGNITIVE CLASS 9 Matched Filter Detection Spectrum Sensing Transmitter Detection Receiver Detection Interference Temperature Management Matched Filter Energy Detection Detection Cyclostationary Feature Detection IFA2007 COGNITIVE CLASS 10 Matched Filter Detection Matched Filter Received Signal r(t) = s(t) + n(t) Sample at t = T Threshold Device t 0 r( )s(T t + )d Y Y H o H1 Decide H0 or H1 (t) 0 T r(t) 0 T 0 T 2T 0 T maximum at T 2T s(t): the transmitted signal of the primary user n(t): AWGN T: Symbol interval : Threshold Need Transmitted signal information s(t) Synchronization for sampling timing (t=T 11 IFA2007 COGNITIVE CLASS Matched Filter Detection A. Sahai, N. Hoven and R. Tandra, Some Fundamental Limits in Cognitive Radio, in Proc. Allerton Conf. on Comm., Control and Computing 2004 llerton 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 IFA2007 COGNITIVE CLASS 12 Matched Filter Detection it requires a priori knowledge of the primary user signal such as the modulation type and order, the pulse shape, and the packet format But Hence, if this information is not accurate, then the matche filter performs poorly. However, since most wireless network systems have pilot, preambles, synchronization word or spreading codes, these codes, can be used for the coherent detection. COGNITIVE CLASS 13 IFA2007 Energy Detection