Towards contention resolution model to enhance rate of interference during dynamic spectrum utilization in cognitive radio network environment

In cognitive radio networks (CRNs), contention resolution is a fundamental challenge for optimizing dynamic spectrum access among secondary users (SUs) without causing interference to primary users (PUs). This study introduces a contention resolution model within cognitive radio networks. The queuing theory model of M/G/1/K with a First Come First Serve (FCFS) algorithm was employed. This paper proposes a novel contention resolution model using the First-Come-First-Served (FCFS) strategy, framed within a Markov Decision Process (MDP). The model dynamically allocates spectrum to SUs based on their arrival time. It leverages on M/G/1/K queuing model, providing a theoretical foundation for optimizing contention resolution. Through the FCFS algorithm, the model ensures equitable access to the spectrum, prioritizing the first arriving users. As a proof of concept and in order to validate the effectiveness of the model, simulations were performed using MATLAB and Minitab software. MATLAB was employed to simulate the dynamic behavior of the network under varying conditions, providing insights into throughput, delay, and collision metrics while Minitab was used for statistical analysis and validation of the simulation data, ensuring accuracy and reliability of the results. The results obtained from the simulations indicates that the MDP-based FCFS model significantly improves spectrum efficiency, reduces access delays, and minimizes collision rates compared to traditional contention resolution techniques. Another main contribution of this model formulation and evaluation is to help Nigerian Communication Commission (NCC) and other Dynamic Spectrum Usage functionaries in analyzing and optimizing the contention resolution predominant challenge, for the effective utilization of available spectrum resources in dynamic cognitive radio environment.