The 5th generation (5G) technology’s objective is to provide improve users’ experience by increasing data rate, improving coverage and supporting Quality of Service (QoS) to various service classes. And variety of usage scenarios such as enhanced mobile broadband, massive machine-type communications and ultra-reliable low-latency communications. Due to the mounting increase in the user equipment (UE) devices of wireless communication technologies, 5G and beyond networks expect to support far higher user density and far lower latency than currently deployed cellular technologies. Random access channel (RACH) is a mandatory procedure for the UEs to connect with the Node (gNB). The performance of the RACH directly affects the performance of the whole network. Currently, RACH uses a uniform distribution-based (UD) random access to prevent a possible network collision among multiple UEs attempting to access channel resources. However, in a UD-based channel access, every UE has an equal chance to choose a similar contention preamble close to the expected value, which causes an increase in the collision between the UEs. Therefore, we propose a Poisson process-based RACH (2PRACH). A Poisson based distribution, such as exponential distribution, disperses the random preambles between two bounds in a Poisson point method, where random variables occur continuously and independently with a constant parametric rate. In this way, our proposed 2PRACH approach distributes the UEs in a probability distribution of a parametric collection. Simulation results show that the shift of RACH from UD-based channel access to a Poisson process-based distribution enhances the reliability and lowers the network’s latency.