Data-Oriented Channel Knowledge Map IoT Transmission Under Hardware Impairments

Abstract

Ultra-reliable low-latency IoT communications (URLLC-IoT) has recently gained a growing interest. Here the challenge in reliable low-latency uplink transmission results from the transmission power limitations and lack of multiple antennas. However, in many IoT services the data volumes are small and sensor deployments may include massive number of devices. In this work we consider a coordinated uplink transmission of clustered IoT devices. The focus is on scenarios where location-based channel knowledge map (CKM) can be applied to enable cooperation. We model and analyse the impact of hardware impairments and erroneous CKM information. In the performance evaluation we focus on the recently introduced dataoriented approach that has gathered significant attention in the context of short-packet transmissions. Specifically, it introduces a transient performance metric for small data transmissions, where the amount of data and available bandwidth play crucial roles. Results show that cooperation between clustered IoT devices may provide notable benefits in terms of increased range. Yet, the performance of the coordinated transmission system is heavily depending on the strength of the static channel component in the CKM based cooperation, the level of hardware impairments and the quality of CKM information. Analytic results are verified against simulations, showing only minor differences between analytical and experimental results.