RACH Success Probability Analysis and Optimization in NB-IoT Networks

Narrow Band-Internet of Things (NB-IoT) is a novel technology to provide a high coverage area for massive low-cost devices with latency tolerance and long battery life. However, existing random access techniques with fixed repetition values will cause severe interference and low resource utilization. In order to provide more reliable transmission for NB-IoT devices, the Random Access CHannel (RACH) success probability is first analyzed in this paper. An exact closed-form expression for the RACH success probability of a random user, including both the repetition values and received Signal to Interference plus Noise Ratio (SINR) values, is derived. We further formulate the joint optimization problem, including sub-carrier assignment, repetition value and start TS allocation, to maximize the RACH success probability. By mapping the two-dimensional resource table as a one-dimensional resource block vector, the many-to-one matching algorithm is invoked to solve this problem. The improved utility function is further designed to eliminate the "externalities" effects in the matching process. Numerical results demonstrate that the proposed optimization outperforms existing algorithm with fixed repetition value.