{"title":"Joint Control and Shared Channel Scheduling for Downlink in 3GPP Narrowband-IoT","authors":"Pavan Reddy Manne, Abhinav Kumar, K. Kuchi","doi":"10.1109/COMSNETS48256.2020.9027476","DOIUrl":null,"url":null,"abstract":"Narrowband-IoT (NB-IoT) is a low power wide area network technology introduced by the $3^{rd}$ 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 the 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. We also define performance metrics to evaluate the impact of the proposed scheduler. With system-level simulations, we show that the proposed scheduler significantly outperforms the current state-of-the-art algorithms.","PeriodicalId":265871,"journal":{"name":"2020 International Conference on COMmunication Systems & NETworkS (COMSNETS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on COMmunication Systems & NETworkS (COMSNETS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMSNETS48256.2020.9027476","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Narrowband-IoT (NB-IoT) is a low power wide area network technology introduced by the $3^{rd}$ 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 the 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. We also define performance metrics to evaluate the impact of the proposed scheduler. With system-level simulations, we show that the proposed scheduler significantly outperforms the current state-of-the-art algorithms.