Evidence map›Paper›PMID 38067904›Full record

ArticleSensors (Basel, Switzerland)2023

Beacon Success Rate versus Gateway Density in Sub-GHz Sensor Networks.

Başak Can, Bora Karaoğlu, Srikar Potta, Franklin Zhang, Artur Balanuta, Muhammed Faruk Gencel, Uttam Bhat, Johnny Huang, Pooja Patankar, Shruti Makharia and 3 more

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 85% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 1 institution in 1 country.

Başak CanAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.ORCID 0009-0007-1554-5774
Bora KaraoğluAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.ORCID 0000-0002-3092-5499
Srikar PottaAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.
Franklin ZhangAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.
Artur BalanutaAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.
Muhammed Faruk GencelAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.ORCID 0000-0002-5452-7516
Uttam BhatAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.
Johnny HuangAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.ORCID 0009-0003-8758-1994
Pooja PatankarAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.
Shruti MakhariaAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.
Radhakrishnan SuryanarayananAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.
Arvind KandhaluAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.
Vinay Sagar Krishnamurthy Vijaya ShankarAmazon Lab126, 1100 Enterprise Way, Sunnyvale, CA 94089, USA.
Amazon (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple Gateways (GWs) provide network connectivity to Internet of Things (IoT) sensors in a Wide Area Network (WAN). The End Nodes (ENs) can connect to any GW by discovering and acquiring its periodic beacons. This provides GW diversity, improving coverage area. However, simultaneous periodic beacon transmissions among nearby GWs lead to interference and collisions. In this study, the impact of such intra-network interference is analyzed to determine the maximum number of GWs that can coexist. The paper presents a new collision model that considers the combined effects of the Medium Access Control (MAC) and Physical (PHY) layers. The model takes into account the partial overlap durations and relative power of all colliding events. It also illustrates the relationship between the collisions and the resulting packet loss rates. A performance evaluation is presented using a combination of analytical and simulation methods, with the former validating the simulation results. The system models are developed from experimental data obtained from field measurements. Numerical results are provided with Gaussian Frequency Shift Keying (GFSK) modulation. This paper provides guidance on selecting GFSK modulation parameters for low bit-rate and narrow-bandwidth IoT applications. The analysis and simulation results show that larger beacon intervals and frequency hopping help in reducing beacon loss rates, at the cost of larger beacon acquisition latency. On the flip side, the gateway discovery latency reduces with increasing GW density, thanks to an abundance of beacons.

Indexed as

beacon collisionbeacon intervalCarrier-to-Interference ratiofrequency hoppinggatewayGFSKIEEE 802.15.4Internet of Things (IoT)latencysensorsWide Area Network (WAN)

Identifiers

PMID38067904
PMCPMC10708715
OpenAlexW4389193326

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.