# Context-Aware Lossless and Lossy Compression of Radio Frequency Signals

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## Abstract

**:**

## 1. Introduction

## 2. RF Signals Data Format

## 3. The FAPEC Data Compressor

## 4. FAPEC Tailoring for RF Data

#### 4.1. General Aspects of the Proposed Algorithm

#### 4.2. Smart Lossy

**spectrum sensing method**consists of first estimating the noise power and using this estimate to implement an energy detector. Then, different levels of losses can be applied to what is assumed to be signal or noise, respectively. The problem can be stated as follows:

**prediction evaluation method**, aims at a simple and fast implementation by reusing quantities already computed in the prediction stage. It relies on the Levinson–Durbin algorithm, from which we take the autocorrelation ${r}_{x}\left(i\right)$, the training length T, the estimated error $\u03f5$, the filter order Q, and the LPC coefficients ${h}_{i}$. From these values, noise power ${\widehat{\sigma}}_{w}^{2}$ can be estimated as

## 5. Test Setup

## 6. Test Results

#### 6.1. Lossless and Near-Lossless Compression

#### 6.2. Smart Lossy

## 7. Conclusions and Future Work

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Abbreviations

AIC | Akaike Information Criterion |

AM | Amplitude Modulation |

APRS | Automatic Packet Reporting System |

BER | Bit Error Rate |

CLT | Central Limit Theorem |

ESA | European Space Agency |

FAPEC | Fully Adaptive Prediction Error Coder |

FFT | Fast Fourier Transform |

FLAC | Free Lossless Audio Codec |

GNSS | Global Navigation Satellite System |

IQ | In-phase and Quadrature |

LPC | Linear Predictive Coding |

LSB | Least Significant Bits |

RF | Radio Frequency |

SDR | Software-Defined Radio |

SNR | Signal-to-Noise Ratio |

WSS | Wide Sense Stationary |

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**Figure 3.**Average compression ratio and throughput (complete dataset) for $N=8192$ and different values of T.

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**MDPI and ACS Style**

Martí, A.; Portell, J.; Riba, J.; Mas, O.
Context-Aware Lossless and Lossy Compression of Radio Frequency Signals. *Sensors* **2023**, *23*, 3552.
https://doi.org/10.3390/s23073552

**AMA Style**

Martí A, Portell J, Riba J, Mas O.
Context-Aware Lossless and Lossy Compression of Radio Frequency Signals. *Sensors*. 2023; 23(7):3552.
https://doi.org/10.3390/s23073552

**Chicago/Turabian Style**

Martí, Aniol, Jordi Portell, Jaume Riba, and Orestes Mas.
2023. "Context-Aware Lossless and Lossy Compression of Radio Frequency Signals" *Sensors* 23, no. 7: 3552.
https://doi.org/10.3390/s23073552