esa-sceva/satcom-chunk-collection huggingface dataset:
# A Systematic Survey on 5G and 6G Security Considerations, Challenges, Trends, and Research Areas
## Abbreviations  
The following abbreviations are used in this manuscript:  
3 GPP 3 rd Generation Partnership Project 5G 5 th Generation CN  Core Network RAN  Radio Access Network UE  User Equipment PQC  Post-Quantum Cryptography IoT  Internet of Things ZTA  Zero Trust Architecture gNB  gNodeB SDN  Software-Defined Network NFV  Network Function Virtualization MEC  Mobile Edge Computing TS  Technical Standard AKA  Authentication and Key Agreement SN  Serving Network AN  Access Network AUSF  Authentication Server Function SEAF  Security Anchor Function NIST  National Institute of Science and Technology SBA  Service Based Architecture O-RAN  Open Radio Access Network CDM  Continuous Diagnostics and Mitigation ICAM  Identity, Credential, and Access Management MNO  Mobile Network Operator EAP  Extensible Authentication Protocols PFS  Perfect Forward Security  
\begin{tabular}{l l} DH & Diffie-Hellman \\ USIM & Universal Subscriber Identity Module \\ UDM & Unified Data Management \\ SUPI & Subscription Permanent Identifier \\ SUCI & Subscriber Concealed Identifier \\ DOS & Denial of Service \\ MA & Mutual Authentication \\ ASIC & Application-Specific Integrated Circuits \\ FPGA & Field-Programmable Gate Array \\ SMC & Security Mode Control \\ RRC & Radio Resource Control \\ PUF & Physical Unclonable Function \\ NPN & Non-Public Networks \\ TSN & Time-Sensitive Networking \\ NR & New Radio \\ LTE & Long-Term Evolution \\ VANET & Vehicular Ad Hoc Network \\ WLANs & Wireless Local Area Networks \\ HetNet & Heterogeneous Network \\ EPC & Evolved Packet Core \\ UMTS & Universal Mobile Telecommunications System \\ O-vRAN & Open Virtualized Radio Access Network \\ CVE & Common Vulnerabilities and Exposures \\ QoS & Quality of Service \\ TLS & Transport Layer Security \\ RIS & Reconfigurable Intelligent Surface \\ IRIS & Illegal Reconfigurable Intelligent Surface \\ OAuth & Open Authentication \\ NAS & Non-Access Stratum \\ AS & Access Stratum \\ MIMO & Multiple Input Multiple Output \\ RB & Radio Bearer \\ NOMA & Non-Orthogonal Multiple Access \\ PHY & Physical Layer \\ PLS & Physical Layer Security \\ SNR & Signal-to-Noise Ratio \\ D2D & Device to Device \\ V2X & Vehicle to Everything \\ BYOD & Bring Your Own Device \\ i-ZTA & Intelligent Zero Trust Architecture \\ SelfDN & Self-Driving Network \\ MEP & Mobile Edge Computing Platform \\ UPF & User Plane Function \\ UDN & Ultra Dense Network \\ AP & Access Point \\ ECC & Elliptic Curve Cryptography \\ XMSS & eXtended Merkle Signature Scheme \\ FIPS & Federal Information Processing Standards \\ CRYSTALS & Cryptographic Suite for Algebraic Lattices \\ CA & Certificate Authority \\ QoE & Quality of Experience \\ RIC & RAN Intelligent Controller \\ VNF & Virtualized Network Functions \\ THz & Terahertz \\ NTN & Non-Terrestrial Networks \\ \end{tabular}
# A 60 GHz CMOS I/Q Receiver for High-Speed Wireless Communication System
### Design of 60 GHz Low Noise Amplifier  
A 60 GHz receiver requires a low noise figure as well as high linearity. Therefore, a three-stage CS LNA with a low noise figure is proposed. Figure 2 shows the schematic of 60 GHz LNA. The single-ended structured LNA input is connected to the antenna. The inductive source degeneration technique (L\({}_{4}\), L\({}_{6}\)) is used in the first and the second stages to achieve the low noise figure at 60 GHz. The common source amplifier structure is implemented without a source degeneration inductor in the third stage to improve the gain and linearity. The input matching network is formed by inductors L\({}_{1}\) and L\({}_{2}\) and  
Figure 1: Block diagram of proposed 60 GHz CMOS I/Q receiver.  
capacitor C\({}_{1}\). The shunt inductor (L\({}_{1}\)) is implemented in the input matching network for ESD protection. The switched resistive feedback network is implemented to control the gain at the second and the third stage. The PMOS transistor switch is used in the feedback network so that the additional DC block capacitor is avoidable. Since the additional parasitic capacitance can be removed, it helps to achieve a 21 dB gain at 60 GHz. To control the gain of around 6 dB, the feedback resistors R\({}_{\rm{f1}}\) and R\({}_{\rm{f2}}\) are used, considering the on-resistance of PMOS. A custom cap metal-oxide-metal (MOM) capacitor is used with EM simulation to achieve an accurate frequency of 60 GHz. The shunt inductor (L\({}_{1}\)) is implemented in the input matching network for ESD protection. The simulated gain of 21 dB and the noise figure of <5.5 dB are achieved at 57-62 GHz. The gain of the LNA is controllable from 15 dB to 21 dB at 57-62 GHz. The output impedance is matched to 50 \(\Omega\) for driving two separate single-to-differential amplifiers. The parameter value of the components in the circuit is shown in Figure 2.
## 5 Addressing the Research Questions
### RQ1: What Are the Primary Fields of Application Where VR, AI, and IoT Are Used in Combination?
#### 5.3.2 Layered Architectures  
A layered system architecture ensures modularity, scalability, and efficient data processing. Typical layers include a hardware layer with IoT devices, a data layer for storage and analysis, a business logic layer with AI models, and a presentation layer using XR interfaces. This structure allows for seamless integration of different technologies and ensures efficient system performance.  
A good example was [77] which proposed a hierarchical four-layered system that includes a physical layer with IoT networks and devices, a slicing layer that regulates communications, a microverse layer for DTs, and an application layer for user interaction where VR and AR could be implemented. [72] describes a system with a presentation layer for user interaction, a business layer for data processing and assessment, and an application server for system logic. [78] uses a layered approach with a blockchain handler for security and a SIP message handler for processing data. The Sensor2 Scene framework at [74], while not explicitly using a layered architecture, uses a framework that can be seen as layered: sensor data are processed and then used to create AR experiences with LLMs and generative models as intermediaries.
# Fast Calculation of Transient Thermal Stress in Surge Lines with Thermal Stratification Region
## 2 Theoretical Background  
[PERSON]'s function method is a method used to solve in-homogeneous differential equations with boundary conditions or initial conditions. The sub-equation can be regarded as the mathematical relationship between the specific \"field\" and the \"source\" that causes the specific field. In the fast calculation of the thermal stress of the surge line, the temperature field of the fluid in the surge line causes the thermal stress change in the surge line, so the temperature field of the fluid in the surge line is the \"source\", and the thermal stress is the \"field\". When the overall temperature on the thermal boundary area of any plant components and equipment changes with time, the temperature distribution depends on the temperature distribution state of the previous time. Additionally, the temperature distributions on them are determined by the state of the temperature distribution of a previous time.  
The thermal stress at any point in time can be obtained through the temperature distribution. The heat transfer equation in a component under the boundary conditions of heat convection and heat conduction is:  
\[K\frac{\partial}{\partial n}T(n)+CT(t)=\varphi(t) \tag{1}\]  
where \(T(t)\) and \(\varphi(t)\) are the component temperature and the fluid temperature at time \(t\), respectively, \(n\) is the normal direction at the boundary, and \(K\) and \(C\) are the functions of heat conduction and heat convection.  
Using [PERSON]'s function, the transient temperature distribution can be expressed in the form of Duhamel integral as  
\[T(t)=\int_{0}^{t}X(t-\tau)\frac{\partial}{\tau}\varphi(\tau)d\tau \tag{2}\]  
where \(X(t-\tau)\) is the temperature Green's function.  
For the temperature change history at any time, it can be discretized into a series of temperature change points. Each temperature change point causes the response of thermal stress. According to the principle of linear elastic stress superposition, the stress change with time can be calculated. The [PERSON]'s function method calculates the thermal stress through volume integral operation. The thermal stress at time \(t\) is as follows:  
\[\sigma(t)=\int_{0}^{t}g(t-\tau)\frac{\partial}{\partial\tau}\varphi(\tau)d\tau \tag{3}\]  
\[\sigma(t)=g_{0}(\varphi(t)-T_{ref})+\sum_{t-t_{d}}^{t}g(t)\Delta\varphi(\tau) \tag{4}\]  
where \(g_{0}=\underset{t\rightarrow\infty}{\lim}g(t)\) s the steady-state value during transient changes, \(t_{d}\) is the decay period of [PERSON]'s function, which is required for the steady state of the transient process area, \(T_{\text{ref}}\) is the reference temperature for structural stress calculation at which the structure is in a state of zero thermal stress, \(g(t)\) is the thermal stress at time \(t\), \(g(t)\) is the unit Green's function value at the elapsed time \(t\), \(\varphi(t)\) and \(\Delta\varphi(t)\) are the fluid temperature and temperature change value at time \(t\), respectively.
## 5 Discussion
### Limitations in Satisfying Security Requirements for Offline Payment Function
#### 5.1.5 Using Cryptographic Technique  
[PERSON] and [PERSON] [44], [PERSON] and [PERSON] [67], [PERSON] [64], [PERSON] [69], and [PERSON] [73] used cryptographic techniques for security. Of the five methods, the cryptographic technique could be considered to be the only technique that perfectly applies to the offline payment function. The PKI method, mentioned in Section 3, allows safe transactions even though the certificate authority is offline, since a certificate states whether the counterpart is a trusted user. In addition, [PERSON] et al. [3] proposed implementing offline payment through certificate issuance using the two-tier hierarchical infrastructure method based on PKI. Many studies focusing on offline transactions deal with security elements through the method of using cryptography technology.  
Discussion to Satisfy Security Requirements for Offline Payment Function--Focusing on the Research about Offline Payment Protocol of CBDC  
It is possible to confirm that several documents dealt with the offline payment function of CBDC. Riksbank proposed a method of limiting the amount that can be remitted when CBDC transactions occur in offline situations [110]. [PERSON] et al. [111] stated that using CBDC as a token-based rather than account-based system is advantageous for offline payment. In an account-based system, the balances of the payer and the recipient are updated during transactions, and a token-based system is recorded only for those who hold CBDCs [112]. Crunchfish's turn-key solution eliminates the risk of server overload, failure, and downtime for offline digital currency [113]. It is also possible to use a method in which the central bank allows only authorized CBDCs to be transacted through one signer. The World Economic Forum proposed a method of limiting the number of transactions offline [114]. Additionally, a method of making reliable hardware for offline payments is used [115].  
However, throughout the research conducted thus far, [PERSON] et al. [95] is the only research that proposed the implementation of the CBDC offline payment function in the form of a protocol. The security requirements that [PERSON] et al. [95] did not satisfy, for example unforgeability and DDoS attack prevention, can be supplemented by applying the existing method and proposing a new method.
# Enhanced Routing Algorithm Based on Reinforcement Machine Learning--A Case of VoIP Service
## 4 Experimental Setup
### Network Topology  
In this work, four network topologies were created to simulate a wireless node network, which are called T1, T2, T3 and T4. Node names were distributed in order to improve the understanding of the scenarios that will be described later. The topologies were developed in order to guarantee that each route has a different number of hops. In Topology T1, there are 3 routes and 8 nodes as illustrated in Figure 4.  
The Topology T2 is an extension of T1 with the addition of three nodes, thus, in total there are 11 nodes and four different routes, which are distributed according to Figure 5.  
Figure 4: Network Scenario Topology T1.  
Figure 3: Scheme of dynamic adjustment of Adjustment Factor (_AF_).  
The T3 is illustrated in Figure 6. This topology is also an extension of the T1 but now we add five extra nodes; thus, there are a total of 13 nodes with 5 different routes.  
The T4 is illustrated in Figure 7. This topology like the others is an extension of the T1 but now we add eight extra nodes; thus, there are a total of 16 nodes with 6 different routes.  
Figure 5: Network Scenario Topology T2.  
Figure 6: Network Scenario Topology T3.  
Figure 7: Network Scenario Topology T4.
## 4 Dynamic Reconfiguration of Distribution Network
### Power Loss Model Considering the DC-Linked MGs  
As shown in Figure 2, DC-link placed between two MGs can serve as additional sources of active and reactive powers. Active power is transferred from an exporting MG to an importing MG to serve as an extra generator [7]. In order to control the exchanging energy, the voltage regulation method can be applied to control the active and reactive power of the AC-DC-AC convertor [9]. Therefore, DC-link within a MG coalition does not have impact on the open loop operation of distribution network, and the MGs can be equivalent to a PQ node with constant power factor in the power flow calculation.  
Thus, the power flow of the distribution network containing DC-linked MGs can be reformulated as follows.  
\[{P_{i}}^{\prime}(t)=\sum_{j\in C_{i}}\left[{P_{j}(t)+r_{j}l_{j}(t)}\right]+{P_ {li}(t)-P_{mi}(t)} \tag{19}\]  
\[{Q_{i}}^{\prime}(t)=\sum_{j\in C_{i}}\left[{Q_{j}(t)+x_{j}l_{j}(t)}\right]+{Q_ {li}(t)-Q_{mi}(t)} \tag{20}\]  
\[{\rm U}_{k}^{\prime}(t)^{2}{=}{\rm U}_{i}^{\prime}(t)^{2}{+}2\left[{r_{i}{P_{ i}}^{\prime}(t)+x_{i}{Q_{i}}^{\prime}(t)}\right]+{({r_{i}}^{2}+{x_{i}}^{2})l_{i}} \tag{21}\]  
where \(P_{mi}(t)\) and \(Q_{mi}(t)\) is the active and reactive power exchanging between MGs and DNO, respectively.  
Figure 2: Distribution network with Direct Current (DC)-linked Microgrids (MGs).  
Thus, the power loss at time \(t\) is:  
\[{P_{loss}}^{\prime}(t)=\sum\limits_{i=1}^{N}{r_{i}\frac{{{P_{i}}^{\prime}(t)^{2}+{ Q_{i}}^{\prime}(t)^{2}}}{{{U_{i}}^{\prime}(t)}^{2}}} \tag{22}\]
# Coalition Formation Game for Cost-Efficient Multiparty Payment Channel in Payment Channel Networks
## 3 Background
### Multihop Payment Channel Network  
It is costly and impractical for a user to create a PC for a new payee every time. The PCN supports indirect payment through multiple PCs based on the conditional balance proof (BP) concept of Ethereum that guarantees atomic payment between a payee, which works similarly with the hashed timelocked contract of the Lightning network [17]. Details of this protocol are described in Figure 1.  
For the PBT procedure from the user \(A\) to \(C\), the user \(A\) sends a conditional BP, including a new channel balance with his signature, to the user \(B\), preventing double spending by \(A\). The conditional BP can be valid only when the receiver secures a pre-image of the hashed secret #S included in the BP. The receiver can reimburse the amount of the conditional BP from a counterparty or smart contract in the main chain if the counterparty does not unlock it after receiving the \(S\) until the deadline. The smart contract verifies the pre-image \(S\) and hash value, #S = SHA256 (\(S\)), for the balance update, returns the amount based on the final balance, and closes the PC. Accordingly, rational users behave honestly to keep the channels open for future transactions or monetary incentives from PBT relaying [34]. The receiver can try to request the unlock repeatedly from the counterparty, rather than the arbitration of a smart contract for dispute resolution.  
The Raiden network [18] supports concurrent PBTs (i.e., PBT flow) with a Merkle tree of information of the in-flight conditional payments, such as the amount, a lock timer, a secret hash, the public key of a payer, etc. Concurrency is also supported in the Bitcoin-compatible PCN [45]. To avoid a balance deficiency due to many in-flight PBTs, each conditional payment has a lock timer for a deadline that prevents collateral from being locked infinitely. Expired conditional BPs are discarded, and the corresponding amount can be used for the next payment if no PSP along the payment path unlocks before the PBT is canceled. However, finding an optimal lock time is challenging based on previous PBTs; the tight duration can cause frequent payment failures and channel closures, while a loose duration increases the collateral costs.
# Seismic Hazard Evaluation and Strain Dynamics in the
## 1 Introduction
as the relatively vulnerable building stock and infrastructure. Therefore, in this study, in addition to all the critical issues discussed in detail above, a comprehensive seismic hazard analysis was conducted for the SFZ and its vicinity. This analysis was motivated by the continuation of destructive earthquakes in the instrumental period, following those that occurred during the historical period, as well as the fault zone's potential to generate large-magnitude earthquakes in the future. For this purpose, the most extensive earthquake catalog for the SFZ and its vicinity were first obtained from the KOERI database; to ensure homogeneity in the dataset, all earthquakes with M \(\geq\) 3 listed in the catalog were converted to moment magnitude (Mw). Subsequently, to derive a detailed assessment of the region's seismic hazard, the \(a\) and \(b\) parameters of the Gutenberg-Richter law were estimated and earthquake recurrence periods were calculated. Finally, the strain rates of SFZ segments were derived from geodetic data, providing insights into the current stress state of each segment. In this study, the instrumental earthquake records of the SFZ were analyzed in terms of temporal, spatial, and energy patterns, and a comprehensive seismic hazard analysis was conducted for the SFZ in light of the current geodetic strain rates. The results, when analyzed in conjunction with historical earthquake data, offer a comprehensive understanding of the region's dynamics at the spatial scale. They quantitatively reveal fault behavior while simultaneously incorporating future risks into projections. This study offers valuable quantitative and qualitative data-driven guidance for earthquake risk management and disaster policies. In this respect, this study provides valuable data-driven guidance, offering both scientific and practical insights for earthquake risk management and disaster policies.
## 3 Results and Discussion
### Texture Properties  
Table 4 shows the texture values of the raw chicken meat after the SC-CO\({}_{2}\) treatment. The results show that some important attributes were affected (\(p<0.05\)) during the storage period. For example, hardness, cohesiveness, gumminess, chewiness, and resilience are among the factors that were influenced in some days of the storage period. The most affected attribute was hardness, which changed (\(p<0.05\)) for all storage times after SC-CO\({}_{2}\) application. Medium-pressure (11.4 MPa) SC-CO\({}_{2}\) hardened the meat samples to \(6360\pm 846\) g, followed by high-pressure (15.4 MPa) SC-CO\({}_{2}\), which hardened it to \(4646\pm 650\) g in contrast to low-pressure (7.4 MPa) SC-CO\({}_{2}\), which produced a meat hardness of \(1473\pm 281\) g. The hardness degree of the control sample (\(2030\pm 629\) g) was not significantly different compared to the low-pressure SC-CO\({}_{2}\). The medium-pressure (11.4 MPa) SC-CO\({}_{2}\) hardened the meat on the third day of evaluation, but the hardness of the meat was increased even more with high SC-CO\({}_{2}\) pressure (15.4 MPa) on the seventh day of storage. Regardless of the hardened texture, these results can be considered acceptable compared to the study by [PERSON] et al. [14] with 57.2 N (5832 g) and 82.8 N (8443 g) for treatment at 8 and 14 MPa for 45 min at 40 \({}^{\circ}\)C, respectively. Another finding that proves that using a higher temperature and longer treatment time of SC-CO\({}_{2}\) could negatively affect the texture was reported by [PERSON] et al. [15], where the hardness values of the treated chicken meat were recorded at 7248, 8822, and 8808 g after storage at zero, three and seven days, respectively. There was high cohesiveness of the control meat samples at the zeroth and seventh day of storage followed by the low-pressure SC-CO\({}_{2}\) on the zeroth day and high-pressure SC-CO\({}_{2}\) on the seventh day of storage, but cohesiveness did not change (\(p>0.05\)) on the third day of storage. The 15.4 MPa SC-CO\({}_{2}\) pressure showed high gumminess on the zeroth and seventh day of treatment, whereas the control sample revealed the lowest degree of gumminess during storage time. The meat treated with medium- and high-pressure SC-CO\({}_{2}\) showed a notably (\(p<0.05\)) high degree of chewiness at the zeroth day, but this did not significantly change on the seventh day of treatment. The low-pressure SC-CO\({}_{2}\) indicated a high degree of resilience in comparing the control sample with the other pressure-treated samples on the zeroth and seventh day of storage. The remaining affected factors were adhesiveness and springiness, both of which were not influenced (\(p>0.05\)) over all the days of texture evaluation; one of the reasons for this finding could be that the meat hardness after SC-CO\({}_{2}\) treatment had