Hybrid filter detection network model for secondary user transmission in cognitive radio networks

Abstract

PurposeA huge variety of devices accumulates as well distributes a large quantity of data either with the help of wired networks or wireless networks to implement a wide variety of application scenarios. The spectrum resources on the other hand become extremely unavailable with the development of communication devices and thereby making it difficult to transmit data on time.Design/methodology/approachThe spectrum resources on the other hand become extremely unavailable with the development of communication devices and thereby making it difficult to transmit data on time. Therefore, the technology of cognitive radio (CR) is considered as one of the efficient solutions for addressing the drawbacks of spectrum distribution whereas the secondary user (SU) performance is significantly influenced by the spatiotemporal instability of spectrum.FindingsAs a result, the technique of the hybrid filter detection network model (HFDNM) is suggested in this research work under various SU relationships in the networks of CR. Furthermore, a technique of hybrid filter detection was recommended in this work to enhance the performance of idle spectrum applications. When compared to other existing techniques, the suggested research work achieves enhanced efficiency with respect to both throughputs as well as delay.Originality/valueThe proposed HFDNM improved the transmission delay at 3 SUs with 0.004 s/message and 0.008 s/message when compared with existing NCNC and NNC methods in case of number of SUs and also improved 0.02 s/message and 0.08 s/message when compared with the existing methods of NCNC and NNC in case of channel loss probability at 0.3.