A Poisson Process-Based Random Access Channel for 5G and Beyond Networks

The 5th generation (5G) wireless networks propose to address a variety of usage scenarios, such as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency (URLLC). Due the exponential increase in user equipment (UE) devices communication technologies, 5G beyond (B5G) expect support far higher density lower latency than currently deployed cellular like long-term evolution-Advanced (LTE-A). However, one critical challenges for B5G is finding clever way various channel access mechanisms maintain dense UE deployments. Random (RACH) mandatory procedure UEs connect with evolved node B (eNB). performance RACH directly affects entire network. Currently, uses uniform distribution-based (UD) random prevent possible network collision among multiple attempting resources. UD-based access, every has an equal chance choose similar contention preamble close expected value, which causes UEs. Therefore, this paper, we Poisson process-based (2PRACH) alternative RACH. A distribution, disperses preambles between two bounds point method, where variables occur continuously independently constant parametric rate. In way, our proposed 2PRACH approach distributes probability distribution collection. Simulation results show that shift from enhances reliability lowers network’s latency.