AI Article Synopsis
- - This paper introduces a method for improving electromagnetic awareness in mobile ad hoc networks (MANET) by using cooperative spectrum sensing, which helps in detecting signal presence more accurately.
- - The approach utilizes energy detectors for signal detection and employs evidence theory at a fusion center to make decisions on channel usage, even with incomplete data.
- - Simulations in MATLAB and OMNET-based MAENA demonstrate that this method enhances sensing efficiency significantly compared to basic data fusion techniques.
Article Abstract
This paper presents a solution for building awareness of the electromagnetic situation in cognitive mobile ad hoc networks (MANET) using the cooperative spectrum sensing method. Signal detection is performed using energy detectors with noise level estimation. Based on the evidence theory, the fusion center decides on the particular channel occupancy, which can process incomplete and unambiguous input data. Next, a reinforced machine learning algorithm estimates the usefulness of particular channels for the MANET transmission and creates backup channels list that could be used in case of interferences. Initial simulations were performed using the MATLAB environment, and next an OMNET-based MAENA high fidelity simulator was used. Performed simulations showed a significant increase in sensing efficiency compared to sensing performed using simple data fusion rules.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838463 | PMC |
| http://dx.doi.org/10.3390/s22030716 | DOI Listing |
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