Name
Abstract | ||
|---|---|---|
The article deals with the problem of ultra-narrowband IoT signals processing in the presence of thermal noise and flicker noise (FN). To achieve the maximum efficiency of processing under conditions of a priori uncertainty, adaptation of the parameters of the FN model is used. An adaptive filtering algorithm is obtained based on the logarithm of the likelihood ratio in discrete time. The computer simulation method is used to study the speed and accuracy of adaptive parameter adjustment. The proposed method is relevant in the development of wireless sensors in the Internet of Things NB-IoT systems, as well as in other systems for receiving and transmitting ultra-narrowband signals. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/MECO55406.2022.9797128 | 2022 11th Mediterranean Conference on Embedded Computing (MECO) |
Keywords | DocType | ISSN |
flicker noise,phase noise,stochastic model,non-Gaussian model,adaptive signal processing | Conference | 2377-5475 |
ISBN | Citations | PageRank |
978-1-6654-6829-9 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Parshin | 1 | 0 | 0.34 |
| Yuri Parshin | 2 | 0 | 0.34 |