Spectrum Sensing Optimization Based On Detection And Power Constraints

Cognitive radio is a novel technology used to improve the spectrum utilization efficiency without interference with the primary licensed user.The most important function in cognitive radio technology is the spectrum sensing in order to detect and utilize the unused frequency band without interference with the primary communication system.Generally,spectrum sensing detection schemes are classified into two groups: non-cooperation group which includes energy detection,matched filter detection,and cyclostationary feature detection.The second group is the cooperation detection group which depends in its work to efficiently cooperate among the cognitive radios in order to avoid some problems of spectrum sensing such as multipath fading,and shadowing.With the cooperation of the cognitive radios,sensing information can be shared among them so the detection of primary user sufficiently improved,then the cognitive radio performance will improve.Cooperative spectrum sensing has been recently recognized as a powerful solution that can overcome such effects and the limitations of cognitive radio networks.It has been proved that collaboration among cognitive radios could improve the sensing performance significantly by introducing space diversity of spectrum data source.In this work,the performance of cognitive radio networks has also been studied through considering the sensing parameters as well as power constraint.The power constraint is integrated into the objective function named power efficiency which is a combination of the main system parameters of the cognitive network.Then the objective function is reformulated to incorporate the throughput.According to different constraints or degree of significance,proper weight may be assigned to each term so that a more preferable combination of parameters could be obtained.As a result,the present contributions can be summarized in proving the existence of optimal combination of parameters such that the power efficiency is maximized and obtaining an optimal combination of parameters for different weights on throughput and power efficiency. In this dissertation,a new optimization strategy is proposed to improve the performance of cognitive network under the considerations of cooperative spectrum sensing scheme using.This optimization strategy can be stated as maximizing the probability of detection for a given value of probability of false alarm.Theoretical analysis and simulation results show that the presently proposed optimization scheme can reduce the detection time and thus increase the overall agility gain and win the probability of detection.And it is proved through this optimization strategy the existence of a convexity of cooperation spectrum sensing optimization problem and gave the condition that guarantees such convexity.