Search arXivSearch

arXiv · 1908.02798

Extreme coverage in 5G Narrowband IoT: a LUT-based strategy to optimize shared channels

Abstract

One of the main challenges in IoT is providing communication support to an increasing number of connected devices. In recent years, narrowband radio technology has emerged to address this situation: Narrowband Internet of Things (NB-IoT), which is now part of 5G. Supporting massive connectivity becomes particularly demanding in extreme coverage scenarios such as underground or deep inside buildings sites. We propose a novel strategy for these situations focused on optimizing NB-IoT shared channels through the selection of link parameters: modulation and coding scheme, as well as the number of repetitions. These parameters are established by the base station (BS) for each block transmitted until reaching a target block error rate (BLER_t ). A wrong selection of these magnitudes leads to radio resource waste and a decrease in the number of possible concurrent connections. Specifically, our strategy is based on a look-up table (LUT) scheme which is used for rapidly delivering the optimal link parameters given a target QoS. To validate our proposal, we compare with alternative strategies using an open source NB-IoT uplink simulator. The experiments are based on transmitting blocks of 256 bits using an AWGN channel over the NPUSCH. Results show that, especially under extreme conditions, only a few options for link parameters are available, favoring robustness against measurement uncertainties. Our strategy minimizes resource usage in all scenarios of acknowledged mode and remarkably reduces losses in the unacknowledged mode, presenting also substantial gains in performance. We expect to influence future BS software design and implementation, favoring connection support under extreme environments.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Emmanuel Luján, Juan A. Zuloaga Mellino, Alejandro D. Otero, Leonardo Rey Vega, Cecilia G. Galarza, Esteban E. Mocskos. 2019-12-24. Extreme coverage in 5G Narrowband IoT: a LUT-based strategy to optimize shared channels. https://doi.org/10.1109/jiot.2019.2959552

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Decoding Delay Guarantees of Space Regulated Multiple Access Random Wireless Networks using Successive Interference Cancellation

This paper is focused on decoding delay guarantees in wireless networks, where messages have a given signal-to-interference-plus-noise ratio threshold $η_0$ to meet in order to be successfully decoded, and where transmissions should occur within some strict time constraints. Its main contribution consists in quantifying the worst-case transmissions decoding delays in the uplink of cellular and cell-free networks using successive interference cancellation. We show how such decoding delay guarantees can be obtained using spatial network calculus, a new tool introduced recently, and in particular spatial regulation. The results rely on the assumption of absence of fading. We nevertheless outline what this approach will lead to in the fading case for cellular networks.

cs.NI

Toward Composable Network Digital Twins: A Subgraph-Based Latency Prediction Study

Modern networks must support changing topologies, configurations, and performance objectives, motivating fast and reliable performance estimation. Network digital twins (NDTs) enable what-if analysis for performance estimation in such network scenarios, however, existing machine learning-based NDT approaches often rely on entire topology representations, which are inherently monolithic and lack reusability under topological or traffic changes in the network. This paper introduces a composable NDT approach that decomposes networks into subgraphs represented by reusable unit twins that capture subgraph structure, configuration and traffic behaviours. A lightweight composer aggregates unit twin combinations to create NDTs that predict per-route end-to-end latency through an overall topology. Evaluation across controlled synthetic topologies and diverse traffic scenarios, real-world Topology Zoo topologies, and a public NDT challenge dataset demonstrates that the composable NDTs achieve high in-distribution accuracy while remaining stable under out-of-distribution scenarios. Comparison with monolithic full topology NDTs demonstrates that our composable approach achieves reusability, while achieving comparable or superior accuracy.

cs.NI

Pattern-Aware Virtual Network Embedding Optimization for Cloud Data Centers

The network virtualization (NV) technology has enabled the sharing of multiple resources among virtual networks (VNs) in cloud data centers. One of the key challenges is to allocate resources in real-time for virtual network request (VNR), which is known as online virtual network embedding (VNE). However, the existing online VNE methods do not exploit the multi-dimensional complementary relationship among diverse VNRs, resulting in the fragmentation and waste of substrate resources. In this paper, we propose the pattern matching based online VNE approach by constructing appropriate matching rules among observed patterns to maximize resources utilization. We devise the clustering based VNRs quantization method and conduct rigorous study on the pattern combination filtering problem. Then, we utilize the column generation to solve it and construct the pattern matching rules. Based on the rules, we propose an online pattern matching VNE algorithm with linear worst-case complexity. Evaluation on a 106-server testbed using Alibaba production cluster trace dataset shows that our algorithm achieves close-to-offline performance and more accepted workloads that outperforms traditional designs by 25%-30%.

cs.NI