Spectrum Sensing In Cognitive Radio

The wireless spectrum is a valuable non-renewable resource. Improving thespectrum efficiency to meet the increasing wireless communication business need asmuch as possible is the eternal subject of wireless communications. It can be said thedevelopment history of wireless communications is the history of how to improve thespectrum efficiency. The shortage of wireless spectrum resources is the bottleneck inthe continuous development of wireless mobile communication and serviceapplications. As an intelligent revolutionary spectrum sharing technology, cognitiveradio (CR) is known as the most popular wireless technology in the21stcentury. Bysecondary utilization of authorized spectrum, CR opens a new path to ease thecontradiction between growing wireless business needs and the shortage of thespectrum resources. Spectrum sensing technology is an important prerequisite of theCR technology and applications. It reflects the most essential characteristics of CR:the ability to perceive and analyze the frequency band of a specific area, then identifythe spectrum holes in them for communication. During CR applications, spectrumsensing technology is achieved through specific spectrum sensing and detectionmechanisms. This paper focuses on the spectrum sensing technology.The article summarizes several spectrum sensing detection technologies thatcurrently used, including interference temperature detection and local oscillatorleakage power detection that based on the receiving end detection, and energydetection, matched filter detection, cyclostationary feature detection that based on thetransmitter end detection. This article mainly analysis energy detection currently used.Detection performance in the Gaussian channel, Rayleigh channel, and Rice channelbased on energy detection have been studied and related simulations have been done.In addition, the negative impact that noise uncertainty gives to energy detection hasbeen learned too.The spectrum sensing technologies that currently used are all used fornarrowband signals detect, while in practical applications, broadband signals need tobe detected. Hence two-step detection method appears. This method mainly for broadband signals detects. It changes the detection accuracy and speed according todifferent needs. Two-step detection method acts in two steps. The first step is namedcoarse detection. It uses multi-resolution detection technology that based on wavelettransform. The main purpose of this step is to choose narrow-band frequency rangethat nobody use form the wide frequency band. The second step is called finedetection. It takes delay correlation detection technology. The main purpose of thisstep is to get further details of the narrow-band frequency range that first step haschosen. The two stages cooperate with each other, in order to pick out theauthorization signal quickly and efficiently from broadband signals, as well asmaintain accuracy to some extent. Two-step detection method is carried out in thetime domain. So it’s obviously that the method has distinct real-time characteristic andlow power consumption.