esa-sceva/satcom-chunk-collection huggingface dataset:
# Temporally Programmable Hybrid MOPA Laser with Arbitrary Pulse Shape and Frequency Doubling
## 3 MOPA Laser with Arbitrary Pulse Shape
### Arbitrary Pulse Shape Output for the First Nd:YVO\({}_{4}\) Amplifier  
In this section, we verified the feasibility of the theoretical method. By introducing three pulses and compensating the pulse distortion, the shape of a car, interestingly, was obtained. The input average power was 19.5 mW at a pulse repetition rate of 100 kHz, with a square pulse and pulse width of 168 ns.  
First, the small-signal gain was calculated through our model [19]. Since the stimulated emission section \(\sigma_{es}\) directly affects the gain integral, it is a key parameter for the small-signal gain. For Nd:YVO\({}_{4}\) crystal, \(\sigma_{es}\) is strongly dependent on the boundary temperature [20; 21]. We measured the temperature of the crystal at the pumping input end when the pump power was 56 W. The result was 120 \({}^{\circ}\)C, and \(\sigma_{es}\) was estimated to be 12.5 \(\times\) 10\({}^{-19}\) cm\({}^{2}\)[21; 22; 23; 24]. Therefore, we obtained the small-signal gain of the first solid-state stage as 40 dB by slice model [19]. By applying the iteration method [17], the initial pulse gain of 26.5 dB obtained only after 25 times, as depicted by Figure 3. The pulse shape transfer functions from experiment and simulation were plotted in Figure 4a, while the output pulse shapes from experiment and simulation with the same input pulse shape were plotted in Figure 4b. The simulated output power was 7.38 W, being consistent with the experimental one of 7.32 W. Comparing the experimental and simulated results, it was concluded that the theoretical method was very effective in calculating the gain characteristics and in obtaining the pulse shape transfer function.  
Figure 3: Pulse shape evolution during the iteration.  
Figure 2: The results are measured at a pulse repetition rate of 100 kHz with a pulse duration of 168 ns. (**a**) Raman frequency shift from the stimulated Brillouin scattering (SBS) effect; (**b**) pulse distortion due to backward SBS generation.  
To test the capability of compensating pulse distortion and obtain car-shaped pulse shapes, the input pulses were theoretically obtained by the desired output pulse shapes and \(G(t)\). With the same amplifier setup, the pulse shape transfer function was the same as that in Figure 4. As shown in Figure 5a, for the input pulses, the leading edges' amplitude values were smaller than those of the trailing edges. As the gain of the leading edges were larger than that of the trailing edges, the output shapes were car-shaped, as plotted in Figure 5b. Comparing the target pulse shapes (in black dot lines) and the experimental one, they are in good accordance with each other. As for the output power of the three pulse shapes, they were all equal to 7.3 W with identical input powers of 19.5 mW.
# Cooperative Crossing Cache Placement in Cache-Enabled Device to Device-Aided Cellular Networks
## 3 Offloading Probability Analysis  
We consider cooperative crossing cache placement (BS-to-user or user-to-user) with three cooperation content offloading strategies to transmit content to the user, in which content delivery traffic can be offloaded via the local cache, a D2D link, or a conventional cellular link. Without loss of generality, we assume that a typical user requesting content \(k\) is located at the origin.
# Constellation Encryption Design Based on Chaotic Sequence and the RSA Algorithm
## 2 Theoretical Content
### RSA Algorithm  
#### 2.2.1 The Process of RSA Algorithm  
1. Arbitrarily choose two different prime numbers \(p\) and \(q\) to calculate the product \(n=p\cdot q\), \(\varphi(n)=(p-1)(q-1)\).
2. An integer \(e\) is arbitrarily selected, which must satisfy \(gcd(e,\varphi(n))=1\) and \(1<e<\varphi(n)\), and the integer \(e\) is used as the encryption key.
3. Determine the decryption key \(d\) and satisfy \((de)mod\varphi(n)=1\).
4. The integers \(n\) and \(e\) are made public, and \(d\) is kept secret.
5. Encrypt plaintext \(m\) (\(m\) is an integer) into ciphertext \(c\), use public key (\(n\),\(e\)) for encryption, and encrypt algorithm \(c=E(m)=m^{e}modn\).
6. Decrypt ciphertext \(c\) into plaintext \(m\), use private key (\(n\),\(d\)) for decryption, and decrypt algorithm \(m=D(c)=c^{d}modn\) (provided in Appendix A).
## 4 Experiment
### Impact on Future Intelligent Marine Traffic Systems  
In the field of intelligent marine traffic systems, the research and application of efficient networks for semantic segmentation tasks of Complex Waterway Scenes have provided effective and practical solutions. Our proposed LDMNet, with its meticulously designed network structure, achieves rapid and accurate identification of various objects and obstacles within Complex Waterway Scenes. This provides crucial environmental information for autonomous navigation and collision decision-making. As artificial intelligence algorithms are applied in the field of Unmanned Surface Vehicles, they can significantly accelerate the research, development, and application of USVs, enhancing the overall operational capabilities of the system. With the maturation and advancement of technology, there will be a drive to update relevant regulations and standards, ensuring navigation safety and promoting technological progress and standardization in the entire waterborne transportation industry.
# Ultra-Low-Loss Silicon Waveguides for Heterogeneously Integrated Silicon/III-V Photonics
## 5 Conclusions  
In conclusion, we have demonstrated ULL silicon waveguides using 500 nm thick SOI that can be seamlessly integrated with heterogeneous silicon/III-V active components such as lasers, modulators, and photodetectors. Waveguide loss is as low as 4 dB/m for a multimode waveguide, and 16 dB/m for a quasi-single mode waveguide. The ultralow loss directly benefits applications such as optical gyroscopes in which a long delay line is needed. It can also be utilized in high-\(Q\) ring resonators and narrowband grating-based filters. We demonstrate rings with 4.1 million intrinsic \(Q\), which are promising to realize narrow linewidth lasers on silicon. Calculations show that linewidths on the order of 100 Hz should be achievable using these waveguides.  
[PERSON] designed the devices; [PERSON], [PERSON] performed the experiments; [PERSON], [PERSON], T.K. simulated and analyzed the data; [PERSON], [PERSON], [PERSON] fabricated the devices; [PERSON], [PERSON], [PERSON], [PERSON] wrote the manuscript; [PERSON] supervised the project.  
DARPA MTO Contract N66001-16-C-4017.  
This work was supported by DARPA MTO. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing official policies of DARPA or the U.S. Government. The authors would like to thank [PERSON] for help with simulation, [PERSON] for processing advice, [PERSON] for help with testing, [PERSON], [PERSON] and [PERSON] for fruitful discussions.  
The authors declare no conflict of interest.
###### Abstract  
A multi-section active photonic integrated circuit (PIC) is characterized in detail to gauge its suitability as a transmitter for short reach applications. The PIC is 1.5 mm long and consists of two lasers integrated in a master-slave configuration, which enables optical injection locking (OIL) of the slave laser. The beneficial impact of the injection is characterized by static and dynamic measurements. The results show a reduction of the optical linewidth from 8 MHz to 2 MHz, a relative intensity noise (RIN) value as low as \(-154.3\) dB/Hz and a \(45\%\) improvement of the slave laser modulation bandwidth from 9.5 GHz to 14 GHz. This frequency response enhancement allows the direct modulation of the slave gain section at a data rate of 10.7 Gb/s and an error-free transmission over 25 km of standard single-mode fiber (SSMF). Transmission performance of the injected case shows a 2 dB improvement in the minimum optical power required to achieve a bit error rate of \(3.8\times 10^{-3}\) (hard decision forward error correction limit). These results demonstrate that the multi-section PIC can serve as an attractive cost-efficient transmitter in a wide variety of low-cost short-reach data communication applications.  
Keywords:photonic integration; optical injection; linewidth; relative intensity noise (RIN); frequency response; direct modulation; bit error rate (BER) +
Footnote †: journal:
## 2 Proposed Radio Link Model for Underground Mines
### Propagation Zone Model
#### 2.2.2 Multi-Mode (Limited) Dividing Point  
The multi-mode propagation zone is divided into two sub-zones: the multi-mode (limited) and multi-mode (fundamental) zones. The multi-mode zones occur in between \(DP_{1}\) and \(DP_{3}\), where we experience high Transverse Electric (TE) and Transverse Magnetic (TM) modes of propagation as compared to the free space zone. To determine the location of \(DP_{2}\), an assumption is made that the tunnel has an equivalent rectangular cross-section. Based on this assumption, the distance from the transmitter (Tx) to \(DP_{2}\) can be calculated by considering the second fundamental mode of the tunnel. These modes are essentially standing waves that can be established in the tunnel, and they are defined by the number of times they reflect off the vertical or horizontal walls. According to the model described in [2], \(DP_{2}\) is located at the distance where the second fundamental mode has undergone one reflection from the walls. This distance is calculated in Equation (12), with w and h regarded as the width and height of the tunnel.  
\[DP_{2}=Max\left\{\left(\frac{w^{4}}{\sqrt{\lambda+\frac{w}{h}}}\right),\left( \frac{h^{4}}{\sqrt{\lambda+\frac{w}{h}}}\right)\right\} \tag{12}\]
## 3 Linear and Nonlinear Characterizations
### Nonlinear Characterizations  
With the experimental setup shown in Figure 4, FWM experiments were implemented to characterize the nonlinear parameter \(\gamma\) of the fabricated SRN ridge waveguides with different dimensions. The pump signal was provided by a commercial continuous-wave (CW) laser (AdValue Photonics AP-CW1) with a fixed wavelength of 1950.1 nm. The probe signal was generated by a homemade CW laser having a thulium doped fiber as the gain media pumped at 793 nm. The wavelength of our homemade CW laser was set at 1953 nm. High power isolators (HP-ISOs) were used to protect the CW lasers and the pump and signal lights were combined by a 9:1 coupler. The combination of a fiber polarization beam splitter (PBS) and a fiber polarization controller (PC) was implemented to guarantee both the pump light and the signal light were TE-polarized when injected into the waveguides by a tapered lensed fiber. The output light was collected by another lensed fiber and the FWM spectra were recorded by an optical spectrum analyzer (OSA, Yokogawa AQ6375B). The idler signal with \(\omega_{I}=2\omega_{P}-\omega_{S}\) can be generated in the SRN ridge waveguide via the degenerate FWM, where \(\omega_{I}\), \(\omega_{P}\), \(\omega_{S}\) are the frequencies of the idler, pump and signal lights, respectively. Since the deposited SRN possessing a moderate excess of Si, the TPA and free-carrier absorption (FCA) can be neglected in the 2 \(\upmu\)m band. Considering the linear loss, self-phase modulation, cross-phase modulation and FWM, the interaction relationships among these three lights can be described by the following full-vectorial coupling equations [41]  
\[\frac{\partial A_{P}}{\partial z}=-\frac{1}{2}\alpha_{P}A_{P}+j\gamma_{P}\Big{(} |A_{P}|^{2}+2|A_{S}|^{2}+2|A_{I}|^{2}\Big{)}A_{P}+2j\gamma_{P}A_{S}A_{I}A_{P} ^{*}\exp(j\Delta\beta z) \tag{4}\]  
\[\frac{\partial A_{S}}{\partial z}=-\frac{1}{2}\alpha_{S}A_{S}+j\gamma_{S} \Big{(}|A_{S}|^{2}+2|A_{P}|^{2}+2|A_{I}|^{2}\Big{)}A_{S}+j\gamma_{S}A_{P}^{2} A_{I}^{*}\exp(-j\Delta\beta z) \tag{5}\]  
\[\frac{\partial A_{I}}{\partial z}=-\frac{1}{2}\alpha_{I}A_{S}+j\gamma_{I} \Big{(}|A_{I}|^{2}+2|A_{P}|^{2}+2|A_{S}|^{2}\Big{)}A_{I}+j\gamma_{I}A_{P}^{2} A_{S}^{*}\exp(-j\Delta\beta z) \tag{6}\]  
where \(A_{m}\) (\(m=P\), \(S\), \(I\)) is the field amplitude of the pump, signal, or idler, \(\alpha_{m}\) is the linear loss, \(\Delta\beta\) is the linear phase mismatch, and \(\gamma_{m}\) is the nonlinear parameter, respectively. When the interacting waves are all in the same wavelength band, \(\gamma_{m}\) can be expressed as Equation (7) [44]  
\[\gamma_{m}=\frac{\omega_{m}}{cA_{eff}(\omega_{m})}\overline{n}_{2}(\omega_{m}) \tag{7}\]  
Figure 4: The experimental setup for four-wave mixing (FWM) experiments in the fabricated silicon-rich nitride (SRN) ridge waveguides. CW: continuous-wave; HP-ISO: high power isolator; PBS: polarization beam splitter; PC: polarization controller; VOA: variable optical attenuator; OSA: optical spectrum analyzer. where \(A_{\textit{eff}}\) is the effective mode area and \(\overline{n}_{2}\) is the effective nonlinear RI.
# Performance Evaluation of GFDM Channel Estimation Using DFT for Tactile Internet Application
###### Abstract  
In this work, discrete Fourier transform (DFT)-based channel estimation is proposed in generalized frequency division multiplexing (GFDM) system. In the GFDM system, the subcarriers are non-orthogonal; therefore, the pilot symbols cannot be easily observed due to the interference from data symbols and noise. The proposed method can improve the channel estimation of least square (LS) method by eliminating channel impulse response outside the number of actual impulse response. First, the received signal is demodulated using zero forcing demodulator. Then, it is divided with transmitted pilot symbols to obtain channel response. Interpolation in frequency and time domains is conducted to acquire channel response for all GFDM blocks. Finally, the channel estimation algorithm using DFT is performed. The parameters of the system are adjusted so that they are suitable for tactile internet application. The channel model used is NYUSIM, which utilizes mmWave. Three scenarios in NYUSIM such as urban microcell, urban macro cell and rural macro cell are used and power delay profiles generated from NYUSIM simulator are employed in this system. The results show that mean square error (MSE) from DFT-based channel estimation gives substantial improvement for all scenarios. In addition, symbol error rate (SER) of DFT-based channel estimation provides a slight improvement of \(\sim\)1.5 dB than LS channel estimation.  
GFDM; DFT-based channel estimation; NYUSIM; tactile internet 2021210955. [[https://doi.org/10.3390/electronics1005095](https://doi.org/10.3390/electronics1005095)]([https://doi.org/10.3390/electronics1005095](https://doi.org/10.3390/electronics1005095))
## 3 ROR: Reliable Opportunistic Routing for CRSN
### Channel Selection and Route Request Initiation
As illustrated in Figure 2, it is important at this point to note that for the source node, both the node receiving channel, Cr, and node sending channel, Cs, fields will hold the same channel. However, in the case of all nodes after the sink, the Cr and Cs fields may vary, as will be discussed in the following section. The source node then sets both the hop count and the channel switch count to zero and broadcasts the packet through CC. Figure 2: Route request (RREQ) operation with payload.
## 6 Evaluation and Discussion  
This section aims to validate our proposal, NDN-BDA. We began by performing a security analysis to test its resilience against the attacks mentioned in Section 4. Following that, we evaluated the effectiveness of NDN-BDA using the validation tool AVISPA [40]. Automated Validation of Internet Security Protocols and Applications (AVISPA) is a tool that analyses and validates cryptographic protocols. It also provides analysis techniques to detect possible vulnerabilities and flaws in protocols.
## 1 Introduction
These systems utilize sophisticated algorithms to analyze and categorize network traffic, allowing them to adapt to changing attack patterns without depending entirely on predefined rules or signatures. Machine learning models are particularly effective at detecting anomalies in high-dimensional datasets, allowing for the identification of new threats. Although promising, current machine learning methods encounter challenges related to scalability, computational efficiency, and real-time applicability, particularly when handling the large volumes of traffic common in modern networks. This study tackles these challenges by introducing a Scalable Hybrid AE-ELM IDS Framework, a new intrusion detection model that combines the advantages of Autoencoders (AE) and Extreme Learning Machines (ELM). Autoencoders are used for dimensionality reduction, condensing high-dimensional traffic data into a more compact form while preserving essential features and eliminating noise. This process greatly alleviates the computational load, enhancing the framework's suitability for real-time applications. After dimensionality  
Figure 1: Elements of Intrusion Detection System. reduction, the simplified feature set is processed by ELM, a machine learning model recognized for its fast training time and excellent generalization ability [15]. ELM effectively classifies traffic into benign or malicious categories with high accuracy, providing a reliable and efficient detection system. An overview of the proposed framework is illustrated in Figure 2. The proposed framework's performance is validated using the CSE-CIC-IDS2018 dataset under realistic conditions. This diverse dataset, with its high-dimensional features, guarantees that the framework is capable of managing the complexity and scale associated with modern network traffic. Utilizing cutting-edge machine learning methods, the framework bridges key gaps in current IDS solutions, providing a scalable, efficient, and precise intrusion detection approach. The key contributions of this study include:  
1. Proposing a novel integration of Autoencoders and Extreme Learning Machines (AE-ELM) for intrusion detection, optimizing both scalability and efficiency. 2. Improving high-dimensional data handling via tuned Autoencoders that reduce computational cost without sacrificing feature integrity. 3. Employing ELM for fast, accurate classification, enabling real-time anomaly detection with minimal computational overhead. 4. Validating the framework on the CSE-CIC-IDS2018 dataset, using multiple evaluation metrics to demonstrate robustness and adaptability. 5. Demonstrating superior performance over traditional IDS approaches, showcasing effectiveness in addressing modern network security threats.
## 2 Basic Measurement Techniques for Localization in WSNs
### Angle of Arrival (AOA) Measurements  
The AOA measurement techniques are also known as the bearing measurements or the direction of arrival measurements. The AOA measurements can be obtained from two categories of techniques: one from the receiver antenna's amplitude response and another from the receiver antenna's phase response. These techniques calculate the angle at which the signal arrives from the anchor node to the unknown sensor nodes. Then, the region where the unknown sensor is located, is a line having a certain angle from the anchor node. In AOA measurement techniques, at least two anchor nodes are needed to calculate the position. The localization error could be large if there is a small error in measurement. The accuracy is depended on the directionality of the antenna and measurements are further complicated by the presence of shadowing and multipath effect of the measurement environment. A multipath component from the transmitted signal may appear as a signal coming from entirely different direction and consequently causes a very large error in measurement accuracy [50]. Thus, AOA technique is of limited interest in localization unless it is used with large antenna arrays [8]. As a result, for WSNs with tiny sensor nodes, this option is not energy efficient at all.
## 5 Simulation Result
### Proportional Current Control (PCC)  
The simulation results of the _LC_-HAPF with PCC under 50V DC-link voltage conditions are shown in Figure 5b and Table 2. The THD\({}_{six}\) reduces to about 8.7% after compensation. The compensated \(i_{sn}\) is 0.44 Arms and the compensated \(i_{sx}\) is around 2.48 Arms. Moreover, the three-phase PFs are equal to 1, and the Q\({}_{Total}\) reduces to 3.8 var. The total SW loss of PCC is 26.3 W.  
Figure 6: Simulation results of three-phase PCC voltage, source current and neutral current before and after the _LC_-HAPF compensation with **(a)** HCC; **(b)** PCC; **(c)** LQRC; and **(d)** LQRIC under 40 V DC-link voltage. (For each graph, the blue lines are the waveforms of source voltage, the red lines are the waveforms of source current, and the peacock blue lines are the waveforms of neutral current.)The simulation results of the \(LC\)-HAPF with PCC under 40V DC-link voltage conditions are shown in Figure 6b and Table 3. The \(\text{THD}_{\text{fix}}\) reduces to about 15.0% after compensation. The compensated \(i_{\text{sn}}\) is 0.77 Arms and the compensated \(i_{\text{sx}}\) is around 2.45 Arms. Moreover, the three-phase PFs increase to 0.99, and the \(\text{Q}_{\text{Total}}\) reduces to 9.7 var. The total SW loss of PCC is 13.8 W.