A Preamble Re-utilizing Access Scheme for Machine-Type Communications with Optimal Access Class Barring

The existing long term evolution networks originally designed for human-to-human communications are hard to tackle numerous and bursty random access requests from emerging machine-type communication devices (MTCDs). In this paper, we propose a novel preamble re-utilizing random access scheme for stationary MTCDs with optimal access class barring (ACB), which is based on joint ACB and timing advance (TA) model. By adopting load estimation algorithm, evolved node B (eNB) can detect the preamble collisions in the first step of random access procedure. Therefore, the eNB merely schedules physical uplink shared channel to the successful preambles according to standard random access procedure. The MTCDs that did not pass the first ACB check re-utilize the resources scheduled by the idle and collided preambles to access with a second optimal ACB. Analytical and simulation results manifest that our proposed scheme notably outperforms the conventional joint ACB and TA scheme in terms of four metrics: throughput, access delay, probability of preamble collision and resource efficiency.