Delay and backlog distribution analysis of Amplify-and-Forward cooperative channels: A stochastic network calculus perspective

An accurate and comprehensive delay and backlog performance evaluation is crucial for the quality of service (QoS) guarantee in cooperative communication. However, the classical deterministic network calculus and queueing theory is not suitable for the wireless networks due to their inherent random behaviors. For this aim, we employ stochastic network calculus to analyze the Amplify-and-Forward cooperative communication where the inherent time-varying service characteristic and traffic self-similarity are considered. In particular, a stochastic service curve for Amplify-and-Forward cooperative channel is derived. We use a stochastic arrival curve to describe the self-similar traffic which is characterized by Fractional Brownian Motion (FBM). Furthermore, the closed-form expressions of delay and backlog distribution are derived. Simulation results validate the accuracy of the theoretical analysis. More importantly, the proposed analytical framework can be used to evaluate the performance distribution under various self-similar traffic patterns.