Name
Title | ||
|---|---|---|
Bayesian-Based Channel Quality Estimation Method For Lorawan With Unpredictable Interference |
Abstract | ||
|---|---|---|
The "Internet of things" has become a common term, and low-power wide-area (LPWA) technology is attracting much attention as one of its elemental technologies. LPWA achieves wide-area communication without consuming much energy, allowing various data sensing and gathering applications. LoRa is an LPWA communication technology that uses unlicensed bands. Because it is possible to build a self-managed network with LoRa, many LoRa-based services will be scattered in the same area without an overall administrator. As a result, the communication performance of LoRa may degrade due to unintended radio interference. Unfortunately, many LPWA techniques, including LoRa, have low data rates, making it difficult to gather sufficient control information to avoid such degradation of communication performance. In this paper, we propose a method for estimating network congestion states through successive estimation using Bayesian updates of prior distributions. Computer simulations show the network slate can be estimated by our proposed method with accumulating a little control information. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/GLOBECOM42002.2020.9322136 | 2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM) |
Keywords | DocType | ISSN |
Bayesian attractor model, human cognition model, state estimation, LPWA | Conference | 2334-0983 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daichi Kominami | 1 | 58 | 12.02 |
| Yohei Hasegawa | 2 | 103 | 12.78 |
| Kosuke Nogami | 3 | 0 | 0.34 |
| Hideyuki Shimonishi | 4 | 124 | 22.41 |
| Masayuki Murata | 5 | 1615 | 239.01 |