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Recently, the paradigm of massive ultra-reliable low-latency IoTcommunications (URLLC-IoT) has gained growing interest. Reliable delay-criticaluplink transmission in IoT is a challenging task since low-complex devicestypically do not support multiple antennas or demanding signal processingtasks. However, in many IoT services the data volumes are small and deploymentsmay include massive number of devices. We consider on a clustered uplinktransmission with two cooperation approaches: First, we focus on scenario wherelocation-based channel knowledge map (CKM) is applied to enable cooperation.Second, we consider a scenario where scarce channel side-information is appliedin transmission. In both scenarios we also model and analyse the impact oferroneous information. In the performance evaluation we apply the recentlyintroduced data-oriented approach that has gathered significant attention inthe context of short-packet transmissions. Specifically, it introduces atransient performance metric for small data transmissions, where the amount ofdata and available bandwidth play crucial roles. Results show that cooperationbetween clustered IoT devices may provide notable benefits in terms ofincreased range. It is noticed that the performance is heavily depending on thestrength of the static channel component in the CKM based cooperation. Thechannel side-information based cooperation is robust against changes in theradio environment but sensitive to possible errors in the channelside-information. Even with large IoT device clusters, side-information errorsmay set a limit for the use of services assuming high-reliability andlow-latency. Analytic results are verified against simulations, showing onlyminor differences at low probability levels.

Data-oriented Coordinated Uplink Transmission for Massive IoT System