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It is a challenging task to design a random access protocol that achieves theoptimal throughput in multi-cell random access with decentralized transmissiondue to the difficulty of coordination. In this paper, we present adecentralized interference-aware opportunistic random access (IA-ORA) protocolthat enables us to obtain the optimal throughput scaling in an ultra-densemulti-cell random access network with one access point (AP) and a number ofusers. In sharp contrast to opportunistic scheduling for cellular multipleaccess where users are selected by base stations, under the IA-ORA protocol,each user opportunistically transmits with a predefined physical layer (PHY)data rate in a decentralized manner if not only the desired signal power to theserving AP is sufficiently large but also the generating interference leakagepower to the other APs is sufficiently small (i.e., two threshold conditionsare fulfilled). As a main result, it is shown that the optimal aggregatethroughput scaling (i.e., the MAC throughput of $\frac{1}{e}$ in a cell and thepower gain) is achieved in a high signal-to-noise ratio regime if the number ofper-cell users exceeds some level. Additionally, it is numerically demonstratedvia computer simulations that under practical settings, the proposed IA-ORAprotocol outperforms conventional opportunistic random access protocols interms of aggregate throughput.

Interference-Aware Opportunistic Random Access in Dense IoT Networks