Achieving Maximum Reliability in Deadline-Constrained Random Access With Multiple-Packet Reception

This paper considers random access in a communication channel, which is shared by $N$ active users with saturated traffic. Following a slotted ALOHA-type protocol, each active user attempts to transmit in every slot with a common probability. It is assumed that the channel has the multiple-packet reception capability to enable the correct reception of up to $M$ ( $1 \leq M ) time-overlapping transmissions. To support mission- and time-critical applications that require reliable delivery within a strict delivery deadline $D$ (in units of slot), the aim of this paper is to achieve the maximum deadline-constrained reliability. First, we prove the uniqueness of the optimal transmission probability for any $1\leq M and any $D\geq 1$ . Second, we show it can be computed by a fixed-point iteration for all the cases. Third, for real-life scenarios where $N$ may be unknown and changing, we develop a distributed algorithm for $M>1$ , which allows each active user to dynamically tune its transmission probability based on a method for estimating $N$ . Simulation results verify our analysis and show that the proposed tuning algorithm is effective with near-optimal performance. In addition, as a special case (i.e., $D=1$ ) of our study, the issue of saturation throughput maximization is completely addressed for the first time.