Design of Autoconfigurable Random Access NOMA for URLLC Industrial IoT Networking

Low-power devices are massively deployed to facilitate real-time sensing and data transmission requested in low-power wide-area network. However, the dominating signaling, i.e., continuous phase modulation (CPM), barely gains attention in the context of supporting massive connectivity, not to mention ultra-reliable low-latency communications (URLLC), a primary concern in industrial network automation. To this end, autoconfigurable nonorthogonal multiple access (AC-NOMA) based on CPM signaling is proposed. The term autoconfiguration is used since each device selects a setup from a pool of configurations whenever connecting to the access point in a random and distributive way. It is proven, using ideal power allocation and phase shaping technique, that AC-NOMA offers drastically improved user load and near capacity performance even in finite blocklength regime. Moreover, to enable massive yet sporadic access, slotted ALOHA is combined with AC-NOMA. It is proven that the resultant scheme outperforms power-domain NOMA in terms of throughput even with reduced transmit power and simple forward error correction schemes, such as repetition and convolutional coding. The throughput is further improved using semi-AC-NOMA with slightly increased latency. It is demonstrated that both designs can support very high user load while enabling URLLC in finite blocklength regime, where the packet size is merely 256 bits while the error rate is
$10^{-5}$
, which are also desirable in a number of applications, including satellite communications, visible light communications, etc.