Rate-Latency Optimization for NB-IoT With Adaptive Resource Unit Configuration in Uplink Transmission

• Published in: IEEE systems journal 2021-03, Vol.15 (1), p.265-276
• Main Authors: Elgarhy, Osama, Reggiani, Luca, Malik, Hassan, Alam, Muhammad Mahtab, Imran, Muhammad Ali
• Format: Article
• Language: English
• Subjects: 3GPP; Algorithms; Bandwidths; Cellular communication; Combinatorial analysis; Firmware; Internet of Things; Long Term Evolution; Maximum throughput; Narrowband; NB-IoT; Network latency; Optimization; Performance evaluation; power allocation; Power consumption; Power management; Resource allocation; Resource management; Subcarriers; Throughput; Uplink; uplink scheduling; Wireless communications
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2020.2991073

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 \text{29}\% to \text{1.6}\%.