Performance analysis of various codec of voice traffic in IEEE 802.22 cognitive radio network module using NETSIM

Cognitive Radio Networks (CRNs) are adaptive systems that improve spectrum efficiency through the intelligent allocation and utilization of available frequency bands. This study uses NETSIM software which assesses CRN performance under various network conditions, concentrating on two important factors: speech codec and various traffic categories. The paper entails developing different scenarios to model the impact of these factors on network behavior and Quality of Service (QoS). This work entails modelling diverse traffic kinds and evaluating several voice codecs in a CRN environment. The findings indicate that CBR traffic attains the maximum throughput of 0.43105 Mbps, where voice and video traffic achieve 0.0576 and 0.0461 Mbps, respectively. Similarly, quality of service metrics like spectral efficiency, jitter and delay across traffic types are found. The voice traffic for various codec is analyzed in which the G.711 codec delivers optimal throughput. This study emphasizes the influence of traffic characteristics and codec selection on CRN performance, providing insights for the design of efficient and high-quality service networks.