AFCC-r: Adaptive Feedback Congestion Control Algorithm to Avoid Queue Overflow in LTE Networks

With the dramatic increase in the number of users and the widespread use of smartphones, most of the internet content today is provided by cellular connections. The purpose of many active queue management algorithms developed for the cellular Long-Term Evolution network is to prevent forced packet drops in the Evolved Node B (eNodeB) Radio Link Control buffer and to improve delay and end-to-end throughput values. Although the algorithms developed in the literature improve some of the end-to-end throughput, delay, and packet data fraction values during bottleneck and congestion, they cannot balance these values. The proposed virtual queue management algorithm recalculates the average queue value and the packet dropping probability according to different traffic loads to solve the queue delay and queue overflow problem providing a balance between throughput, delay, and packet data fraction. Simulation results illustrate that the proposed algorithm reduces the delay of the packets and increases fairness among users compared to the Drop-tail, Random Early Drop, Controlled Delay, Proportional Integral Controller Enhanced, and Packet Limited First In First Out Queue algorithms.