Design and performance analysis of joint control and shared channel scheduler for downlink in 3GPP narrowband-IoT

M, Pavan Reddy and Kumar, Abhinav and Kuchi, Kiran (2021) Design and performance analysis of joint control and shared channel scheduler for downlink in 3GPP narrowband-IoT. Ad Hoc Networks, 114. p. 102440. ISSN 1570-8705

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Abstract

Narrowband-IoT (NB-IoT) is a low power wide area network technology introduced by the 3rd Generation Partnership Project (3GPP) in Release 13 specifications. The NB-IoT aims at providing cellular connectivity to low cost, low throughput, delay-tolerant devices, and hence, is a key technology for smart connected living. The NB-IoT specifications continue to evolve as part of 5G New Radio (NR), and the technology is expected to co-exist with 5G NR. A transmission bandwidth of 180 KHz is required to deploy the NB-IoT. In NB-IoT, the duration of the physical downlink control channel (NPDCCH) and the physical downlink shared channel (NPDSCH) changes dynamically. When the base station broadcasts the NPDCCH region, all the active NB-IoT devices try to decode it. Hence, to reduce the power consumption of the NB-IoT devices, more number of NB-IoT devices have to be scheduled in each scheduling attempt. For each payload in NPDCCH, there is a respective payload in NPDSCH. Thus, a base station should schedule the devices simultaneously in both NPDCCH and NPDSCH to reduce resource wastage. The time–frequency resources in NB-IoT are limited and valuable. Further, the NB-IoT devices have low battery power constraint. Thus, scheduling the devices by considering the above constraints has a significant impact on the NB-IoT system performance. Motivated by this, we propose a joint scheduling algorithm for both NPDCCH and NPDSCH. Further, we propose an adaptive repetition allocation algorithm and present a receiver design for NB-IoT. We also define performance metrics to evaluate the impact of the proposed scheduler and then present bounds on the performance gains with the proposed scheduler. With system-level and link-level simulations, we show that the proposed scheduler significantly outperforms the current state-of-the-art algorithms.

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