INSIGHTS OF DISTRIBUTED SENSING ALGORITHMS FOR EFFECTIVE UTILIZATION OF RADIO SPECTRUM

Over the past decade, both in academia and in industry, Cognitive Radio (CR) has received significant research attention, as it is envisaged as a potential solution to the problem of spectrum scarcity. A CR is a system that senses the occupancy spectrum of licensed users (also called primary users) and transmits its data only when it is detected that the spectrum is available. For the efficient use of the spectrum while also ensuring adequate security to the licensed user from harmful interference, the CR should be able to sense the spectrum for primary occupancy quickly as well as accurately. This paper focuses on distributed sensing algorithms and power allocation in cognitive radio(CR) networks. The central entity may determine, by centralized methods, on the presence of the primary units, supply all the information and further process it in the central entity. The delivery of the data to the central node , takes time and the centralized approaches typically suffer from a lack of scalability. The centralized approach is at the cost of the missed detection probability, in return for minimizing the false alarm probability. Decentralized techniques such as consensus and diffusion are introduced in order to solve the above-mentioned problems with centralized methods. A distributed cooperative spectrum sensing approach based on the weighted average consensus algorithm adopts a weighted average consensus adopted for distributed cooperative spectrum sensing measurement fusion by a weighted average consensus algorithm.