Accurate QoS Prediction for CSMA/CA Systems with Uncorrelated Interference
Coexistence of wireless systems in unlicensed bands is considered a severe performance bottleneck, given the heterogeneous and uncoordinated nature of the wireless technologies. A promising approach to address this issue is to apply cognitive radio (CR) techniques, which are capable of accurately predicting the quality-of-service (QoS). This enables highly reliable QoS management and performance guarantees for applications with strict requirements, such as industrial automation or connected driving. Furthermore, accurate QoS prediction is very important for the reliability of safety critical applications. To this end, we present a novel analytical model for predicting the probability distribution of the latency based on Markov Chains (MC) for transmission systems, which employ Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) as a medium access scheme. Further, we validate the high accuracy of the prediction model using ns-3 simulations of an IEEE 802.11n communication.