Research On Multi - Node Cooperative Spectrum Awareness In Cognitive Wireless Networks

With the adventment of communication technology and 4G era. Wi-Fi technology make people’s lives more convenient, so that the people of modern society to enjoy a better life. However, as more and more people start to use wireless devices and wireless networks, more and more enterprises and institutions use open network, existing spectrum resources will inevitably difficult to meet such a large demand. Band spectrum scarcity of resources coupled with the low utilization rate of the two problems has become a stage problem that we need to solve.The development of modern cognitive radio is to solve these issues the majority development space, CR cognitive radio technology is not to interfere in the case of cognitive users to proactively way into the licensed spectrum, efficient use of the spectrum, this method can effectively solve the shortage of spectrum resources. It is important to learn how to solve the waste of relaxing spectrum, how to make spectrum management detection probability and reduce false alarm probability is our first menu. This article studies the integration of a variety of criteria, and proposes a new fusion rule based on adaptive clustering cooperative sensing method, allowing users to get significantly improved performance.The second chapter,we introduced the basics of spectrum sensing technology, by classification, in turns to describe the different types of mathematical models of spectrum sensing technology-based transmitters to transmit and receive signals, different detection and analysis of various types of spectrum sensing techniques have basic understanding of the advantages and disadvantages of various types of technology are summarized in the article.The third chapter introduces the focus of this article and the concept of multi-node cooperative spectrum sensing, and elaborated compared with single node so, what advantages there are multiple nodes. Shortcoming by introducing spectrum sensing technology, leads the local single-node and multi-node cooperative spectrum sensing scheme,and specifically describes the integration of multi-node cooperative spectrum sensing algorithm, as well as specific local spectrum sensing introduces three hard decision fusion rule under program, "AND" guidelines, "OR" criteria and "K rank" criterion, and were based on the number of users for each fusion rule under different simulated and compared overall performance proved the more the number of users, the higher the overall detection performance conclusion. Finally, a new algorithm based on fusion criterion space complex degree of thought.In the fourth chapter, we introduced a new cluster-based cooperative spectrum sensing algorithm in cognitive network users clustering, and proposed a new use of a weighted average of the set threshold energy detection algorithm to cluster select the head, to ensure the detection probability of the premise, as far as possible to reduce the probability of false alarm and detection probability of cognitive users. Finally, the use of guidelines or rules according to the rules used in a cluster, the cluster collaborative spectrum sensing outside the main user determine whether there is simulation analysis.