Rate-latency optimization for NB-IoT with adaptive resource unit configuration in uplink transmission

Elgarhy, O., Reggiani, L., Malik, H., Alam, M. M. and Imran, M. A. (2021) Rate-latency optimization for NB-IoT with adaptive resource unit configuration in uplink transmission. IEEE Systems Journal, 15(1), pp. 265-276. (doi: 10.1109/JSYST.2020.2991073)

Abstract

Narrowband Internet of Things (NB-IoT) is a cellular IoT communication technology standardized by 3rd Generation Partnership Project (3GPP) for supporting massive machine type communication and its deployment can be realized by a simple firmware upgrade on existing long term evolution (LTE) networks. The NB-IoT requirements in terms of energy efficiency, achievable rates, latency, extended coverage, make the resource allocation, in a limited bandwidth, even a more challenging problem w.r.t. to legacy LTE. The allocation, done with subcarrier (SC) granularity in NB-IoT, should maintain adequate performance for the devices while keeping the power consumption as low as possible. Nevertheless, the optimal solution of the resource allocation problem is typically unfeasible since nonconvex, NP-hard and combinatorial because of the use of binary variables. In this article, after the formulation of the optimization problem, we study the resource allocation approach for NB-IoT networks aiming to analyze the tradeoff between rate and latency. The proposed suboptimal algorithm allocates radio resource (i.e., SCs) and transmission power to the NB-IoT devices for the uplink transmission and the performance is compared in terms of latency, rate, and power. By comparing the proposed allocation to a conventional round robin (RR) and to a brute-force approach, we can observe the advantages of the formulated allocation problem and the limited loss of the suboptimal solution. The proposed algorithm outperforms the RR by a factor 2 in terms of spectral efficiency and, moreover, the study includes techniques that reduce the dropped packets from 29% to 1.6%.

• Item Type: Articles
• Additional Information: This work was supported in part by the European Union’s Horizon 2020 Research and Innovation Program under Grant 668995, and in part by the Tallinn University of Technology Development Program 2016-2022, under Grant 2014-2020.4.01.16-0032, and in part by the Estonian Research Council under Grant PRG667.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad
• Authors: Elgarhy, O., Reggiani, L., Malik, H., Alam, M. M., and Imran, M. A.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Systems Journal
• Publisher: IEEE
• ISSN: 1932-8184
• ISSN (Online): 1937-9234
• Published Online: 18 May 2020
• Copyright Holders: Copyright © 2020 IEEE
• First Published: First published in IEEE Systems Journal 15(1): 265-276
• Publisher Policy: Reproduced in accordance with the publisher copyright policy