A Dynamic Access Probability Adjustment Strategy
for Coded Random Access Schemes
In this paper, a dynamic access probability adjustment strategy for coded random accessschemes based on successive interference cancellation (SIC) is proposed. The developed protocolconsists of judiciously tuning the access probability, therefore controlling the number of transmittingusers, in order to resolve medium access control (MAC) layer congestion states in high load conditions.The protocol is comprised of two steps: Estimation of the number of transmitting users during thecurrent MAC frame and adjustment of the access probability to the subsequent MAC frame, based onthe performed estimation. The estimation algorithm exploits a posteriori information, i.e., availableinformation at the end of the SIC process, in particular it relies on both the frame configuration(residual number of collision slots) and the recovered users configuration (vector of recovered users)to effectively reduce mean-square error (MSE). During the access probability adjustment phase, atarget load threshold is employed, tailored to the packet loss rate in the finite frame length case.Simulation results revealed that the developed estimator was able to achieve remarkable performanceowing to the information gathered from the SIC procedure. It also illustrated how the proposeddynamic access probability strategy can resolve congestion states efficiently.