esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Work  
### ARIA Block Cipher  
The block length of ARIA block cipher is 128 bits, and the key length is 128, 192, and 256 bits. Depending on the length of each key, the encryption process consists of 12, 14, and 16 rounds. Each round of the ARIA block cipher consists of the following three parts. First, the round key addition layer is XORed with the 128-bit round key. Second, the substitution layer uses two types of substitution layers. Each substitution layer uses precalculated values of S\({}_{1}\), S\({}_{2}\), and their inverses (i.e., S\({}_{1}^{-1}\), S\({}_{2}^{-1}\)). Figure 1 shows ARIA block cipher structure and two types of substitution layers. Odd rounds use Type 1 and even rounds use Type 2. Lastly, the diffusion layer is a simple linear map which is an involution. The diffusion layer is given by  
\[(x_{0},x_{1},\cdots,x_{15})\rightarrow(y_{0},y_{1},\cdots,y_{15}),\]  
where  
\[y_{0}=x_{3}\oplus x_{4}\oplus x_{6}\oplus x_{8}\oplus x_{9} \oplus x_{13}\oplus x_{14}, y_{8}=x_{0}\oplus x_{1}\oplus x_{4}\oplus x_{7}\oplus x_{10} \oplus x_{13}\oplus x_{15},\] \[y_{1}=x_{2}\oplus x_{5}\oplus x_{7}\oplus x_{8}\oplus x_{9} \oplus x_{12}\oplus x_{15}, y_{9}=x_{0}\oplus x_{1}\oplus x_{5}\oplus x_{6}\oplus x_{11} \oplus x_{12}\oplus x_{14},\] \[y_{2}=x_{1}\oplus x_{4}\oplus x_{6}\oplus x_{10}\oplus x_{11} \oplus x_{12}\oplus x_{15}, y_{10}=x_{2}\oplus x_{3}\oplus x_{5}\oplus x_{6}\oplus x_{8} \oplus x_{13}\oplus x_{15},\] \[y_{3}=x_{0}\oplus x_{5}\oplus x_{7}\oplus x_{10}\oplus x_{11} \oplus x_{13}\oplus x_{14}, y_{11}=x_{2}\oplus x_{3}\oplus x_{4}\oplus x_{7}\oplus x_{9} \oplus x_{12}\oplus x_{14},\] \[y_{4}=x_{0}\oplus x_{2}\oplus x_{5}\oplus x_{8}\oplus x_{11} \oplus x_{14}\oplus x_{15}, y_{12}=x_{1}\oplus x_{2}\oplus x_{6}\oplus x_{7}\oplus x_{9} \oplus x_{11}\oplus x_{12},\] \[y_{5}=x_{1}\oplus x_{3}\oplus x_{4}\oplus x_{9}\oplus x_{10} \oplus x_{14}\oplus x_{15}, y_{13}=x_{0}\oplus x_{3}\oplus x_{6}\oplus x_{7}\oplus x_{8} \oplus x_{10}\oplus x_{13},\] \[y_{6}=x_{0}\oplus x_{2}\oplus x_{7}\oplus x_{9}\oplus x_{10} \oplus x_{12}\oplus x_{13}, y_{14}=x_{0}\oplus x_{3}\oplus x_{4}\oplus x_{5}\oplus x_{9} \oplus x_{11}\oplus x_{14},\] \[y_{7}=x_{1}\oplus x_{3}\oplus x_{6}\oplus x_{8}\oplus x_{11} \oplus x_{12}\oplus x_{13}, y_{15}=x_{1}\oplus x_{2}\oplus x_{4}\oplus x_{5}\oplus x_{8} \oplus x_{10}\oplus x_{15}.\]  
In [8], an efficient 8-bit-based diffusion layer implementation method was introduced. It reduces the number of operations to 76 XOR operations using four additional variables (\(T_{1}\), \(\cdots\), \(T_{4}\)) as follows.
## 3 Privacy and Security Threats in IoT Domain
### Homomorphic Encryption
#### 3.1.2 Primarily Study: HE Model Exploration  
HE model is widely used in the ML domain. Therefore, there are multiple libraries available that support different forms of HE. These libraries differ in their underlying encryption schemes, ease of use, and computational efficiency. Some of the most common libraries are as follows:  
* SEAL (Simple Encrypted Arithmetic Library) [30]: Microsoft(r) developed the SEA. It supports both BFV and CKKS schemes, which fit very well with the encrypted arithmetic of integers and real numbers, respectively.
* HElib [31]: IBM developed HElib, which is open source. It implements the BGV scheme in C++ and supports efficient arithmetic on encrypted data.
* TenSEAL [32]: A library for HE-based encrypted tensor manipulation, using Microsoft SEAL as its base. It is developed to integrate seamlessly with machine learning frameworks like PyTorch.
* Zama's Concrete-ML [33]: Yet another emerging, highly promising solution. It is based on Torus Fully Homomorphic Encryption (TFHE), the FHE framework on which Concrete-MI develops. TFHE operates directly on encrypted bits and allows for Boolean operations with quite promising efficiency and security.  
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline  
* OpenFHE [32] (previously known as PALISAADE): This supports all major FHE schemes, including BGV, BFV, CKKS, DM (FHEW), and CGGI (TFHE) schemes.  
As discussed previously, the TFHE is based on the General Learning with Errors (GLWE) problem, an extension of the Learning With Errors (LWE) framework, which itself forms the backbone of modern cryptographic solutions. The GLWE framework enhances the robustness of the encryption scheme by allowing for a broader range of error distributions, thus offering enhanced security against a wide spectrum of cryptographic attacks. This foundation enables TFHE to perform fast bootstrapping, a process to refresh the noise in ciphertexts, allowing for an unlimited number of computations without decrypting the data.
## 3 Using IC-BEVS for AAV Production
### Development of AAV Production Systems
(**c**) Using ribosome leakage scanning to express AAV Rep and Cap proteins downstream of PH and P10 promoters, respectively, and inserting the rAAV genome between two baculovirus promoters in a single recombinant virus [(74; 75)]. (**d**) The Rep and Cap structure was placed into the EGT site, and the classical polyhedron site was reserved for inserting rAAV cassettes [(76)]. CMV: cytomegalovirus promoter; GFP: Green fluorescent protein; ITR: Inverted Terminal Repeat; BSD: blasticidin; hr2: Heptad Repeat 2. To get rid of the dependence of the complex Sf9 packaging cell lines, in 2018, [PERSON] et al. first reported using ribosome leakage scanning to express AAV Rep and Cap proteins downstream of polh and P10 promoters, respectively, and inserting the rAAV genome between two baculovirus promoters in a single recombinant virus (Figure 3(Cc)). The yield of recombinant serotypes rAAV2, rAAV8, and rAAV9 obtained from a single baculovirus-infected Sf9 cell exceeded \(10^{5}\) vector genomes per cell, and we suggest that this system is suitable for the mass production of rAAV. Individual baculovirus proved to be stable, with no significant decline in rAAV production after at least four successive generations [74]. They further optimized the process and expanded the rAAV production range to serotype 1-13. The translation of the AAV Cap gene was optimized by ribosome leakage scanning, and the gene of interest (GOI) was cloned into Bac-Cap-(ITR-GFP)-Rep shuttle plasmid. All the r AAVs 1-13 show relatively high yields ranging from \(5\times 10^{4}\) to \(4\times 10^{5}\) VG/cell and show different potencies for in vitro transduction and cell-type tropisms [75]. Furthermore, in 2021, [PERSON] et al. introduced a system called Mono-Bac, wherein the AAV produced requires Sf9 cells to be infected by a single BEV containing all three essential genes (Bac-ITR-GOI-Cap-Rep). The Rep-Cap structure was placed into the EGT site, and the classical polyhedron site was reserved for inserting recombinant AAV vector cassettes (Figure 3(Cd)). Compared with the Two-Bac system, its vector yield doubled, and the DNA pollution of baculovirus was reduced [76]. Each iteration of the BEV system has undergone continuous development and refinement to achieve the following specific objectives: maintaining sustained expression of AAV proteins (Rep and Cap) at desired ratios, enhancing AAV yield and functionality, and overall improvement in vector quality [77].
# Regulated Assembly of LPS, Its Structural Alterations and Cellular Response to LPS Defects
## 4 Regulation of Synthesis of UDP-GlcNAc-Precursor for LPS Biosynthesis
It is likely that proteolytic activity of FtsH might be regulated by concentration or forms of acyl-ACPs or lipid A disaccharide. Since LpxC stability is increased in a _fabI_(ts) mutant suggests that membrane fatty acids might influence proteolytic activity or add additional checkpoints in regulating lipid A and phospholipid amounts [29]. Although not fully elaborated, regulation at the level of LpxB and LpxK may serve as additional pathways of this co-regulation. Consistent with such a notion, LpxB has been shown earlier to co-purify with phospholipids [34]. A regulatory checkpoint has been postulated on the basis of a reduced LpxK activity upon reduced membrane fluidity when more saturated fatty acids are present [35]. LpxK mediates the last essential step that completes lipid IV\({}_{\text{A}}\) biosynthesis [4]. LpxK catalyzes the phosphorylation of the 4\({}^{\prime}\) hydroxyl of the distal glucosoamine of lipid A disaccharide. Under conditions like compromised function of either LapB or FtsH, which stabilize LpxC leads to depletion of \(R\)-3-hydroxynristoyl-ACP. This in turn decreases the synthesis of unsaturated fatty acids, which can decrease the LpxK activity, leading to accumulation of lipid A disaccharide [9; 35]. This accumulation of lipid A disaccharide intermediate by the feedback mechanism causes increased proteolysis of LpxC, thereby decreasing flux of \(R\)-3-hydroxynristoyl-ACP into a lipid A biosynthesis pathway, thus again to regain a balance between phospholipid and lipid A biosynthesis. WaaA is also one of the substrates of FtsH protease [36]. Regulation of WaaA turnover by FtsH may be yet another step in preventing an excessive synthesis of LPS over phospholipids. However, a direct impact of changes in WaaA concentration on either LPS synthesis or accumulation of different glycoforms remains to be understood.
## 2 Methodology
### Cycle Slip Repair Method with Success Probability  
Hypothetically, there are \(m\) satellites and \(t\) cycle slips. After we use the ILAM to determine which satellites have cycle slips, it is possible to make use of the least square to estimate the position parameters, clock error parameters and cycle slips parameters:  
\[X=\left({{B^{T}}\cdot{P}\cdot{B}}\right)^{-1}\cdot{B^{T}}\cdot{P}\cdot{l} \tag{21}\]  
where:  
\[X=\left[{\begin{array}{*{20}{c}}{\Delta{r_{u}^{x}}}\\ {\Delta{r_{u}^{y}}}\\ {\Delta{r_{u}^{z}}}\\ {c\Delta{t}}\\ {\Delta{N_{1}}}\\ \end{array}}\right]\]  
\[B=\left[{\begin{array}{*{20}{c}}{e_{1}^{x}}&{e_{1}^{y}}&{e_{1}^{z}}&1&{ \lambda_{1}}\\ \vdots&\vdots&\vdots&\ddots\\ {e_{t}^{x}}&{e_{t}^{y}}&{e_{t}^{z}}&1\\ \vdots&\vdots&\vdots&\vdots\\ {e_{m}^{y}}&{e_{m}^{z}}&1\\ \end{array}}\right]\]  
Figure 3: Cycle Slips Detection Flow of ILAM.  
\[l=\left[\begin{array}{c}\lambda_{1}\Delta\widetilde{\varphi}_{1}\\ \lambda_{2}\Delta\widetilde{\varphi}_{2}\\ \vdots\\ \lambda_{m}\Delta\widetilde{\varphi}_{m}\end{array}\right]\]  
The values of matrix \(P\) are calculated by the elevation-dependent measurement weighting method.  
After calculating a float solution, searching for integer cycle slips is the next step to repair the cycle slips. The LAMBDA method is a popular and effective method to search integer ambiguity [30], when the parameters' true values are all integers. But in reality, the non-integer outliers may occur, and the integer search may fail. A separately rounding method is available to obtain integer cycle slips. The success probability is an ambiguity validation method for ambiguity rounding and is calculated as [31]:  
\[P\left(\Delta N=\Delta\widetilde{N}\right)=P(\left|\Delta N-\Delta\hat{N} \right|\leq\frac{1}{2})=2\phi\left(\frac{1}{2\sigma_{\Delta\hat{N}}}\right)-1 \tag{22}\]  
where \(\Delta\hat{N}\) is the float solution of \(\Delta N\), \(\Delta\widetilde{N}\) is the closest integer of \(\Delta N\), \(\phi\left(x\right)\) meets the standard normal distribution, and \(\sigma_{\Delta\hat{N}}\) is the standard deviation of \(\Delta\hat{N}\).  
Because the standard deviations of float solutions of cycle slips and outliers are similar by this method, the success probability cannot detect the non-integer outliers. The decimal test can solve this problem because the fractional part of the cycle slip is bound by the standard deviation. We can detect outliers with the formula:  
\[\left|\Delta\hat{N}-\Delta\widetilde{N}\right|\leq 3\sigma_{\Delta\hat{N}} \tag{23}\]  
where \(\Delta\widetilde{N}\) is the closest integer of \(\Delta\hat{N}\). The float solution can be rounded and can repair cycle slips when Equation (23) is true. If the float solution does not meet Equation (23), there is outlier at this satellite.
## 3 Results
### Fixed Points  
Fixed points of (8) are given by the solutions of  
\[\begin{cases}0&=\alpha-\gamma\bar{x}-\delta\bar{x}\bar{y}+\beta\frac{g^{m}}{x _{th}^{m}+\bar{x}^{n}}\\ 0&=\rho\frac{g^{m}}{y_{th}^{m}+\bar{x}^{m}}-\omega\bar{y}.\end{cases}\]  
So we have  
\[\bar{y}=\frac{\rho}{\omega}\frac{\bar{x}^{m}}{y_{th}^{m}+\bar{x}^{m}}\]  
where \(\bar{x}\) is given by the solutions of  
\[\alpha-\gamma\bar{x}-\frac{\delta\rho}{\omega}\frac{\bar{x}^{m+1}}{y_{th}^{m} +\bar{x}^{m}}+\beta\frac{\bar{x}^{n}}{x_{th}^{n}+\bar{x}^{n}}=0 \tag{9}\]  
Recall that for the biological motivation of the model, we are only interested in non-negative \(\bar{x}\). In the following, for simplicity of notation, we shall omit the bars from \(\bar{x}\).  
In the general case \(n\
eq m\) and \(x_{th}\
eq y_{th}\), solutions of (9) are the zeros of the polynomial  
\[a_{0}x^{n+m+1}+a_{1}x^{n+m}+a_{2}x^{n+1}+a_{3}x^{m+1}+a_{4}x^{n}+a_{5}x^{m}+a_ {6}x+a_{7}=0\]where  
\[a_{0}=-(\gamma\omega+\rho\delta)<0, a_{1}=\omega(\alpha+\beta)>0,\] \[a_{2}=-\gamma y_{th}^{m}\omega<0, a_{3}=-x_{th}^{n}(\gamma\omega+\rho\delta)<0,\] \[a_{4}=y_{th}^{m}\omega(\alpha+\beta)>0, a_{5}=\alpha\omega x_{th}^{n}>0,\] \[a_{6}=-\omega\gamma x_{th}^{n}y_{th}^{m}<0, a_{7}=\alpha\omega x_{th}^{n}y_{th}^{m}<0.\]  
Let us consider a special case which is relevant for our application, and assume \(n=m=2\) and \(x_{th}=y_{th}\). Then, fixed points \((\tilde{x},\tilde{y})\) satisfy  
\[\tilde{y}=\frac{\rho}{\omega}\frac{\tilde{x}^{2}}{x_{th}^{2}+\tilde{x}^{2}} \tag{10}\]  
with \(\tilde{x}\) given by the solutions of a cubic equation  
\[(\delta\rho+\omega\gamma)\tilde{x}^{3}-\omega(\beta+\alpha)\tilde{x}^{2}- \omega\gamma x_{th}^{2}\tilde{x}-\alpha\omega x_{th}^{2}=0 \tag{11}\]  
which has either three real zeros, or one real and two complex solutions. Thus, we might have up to three biologically-relevant fixed points.
# Power Control Techniques for Interference Management-
## 2 Systematic Review Method
### Selection and Data Extraction
#### 2.3.4 Data Extraction  
One information specialist from the University of South Africa library and the two Professors playing supervisory roles in this study conducted initial data extraction. Each of the parties was involved independently. The lead author (AL) reviewed all final studies and iteratively generated the list of the literature. The characteristics of the studies collected included authors, year of publication, objective, study design, setting, intervention studied (if any), participant sampling methods, inclusion and exclusion criteria, data collection and analysis methods, participants' characteristics, main results, and authors' conclusion(s).  
The data extracted from each study were the following:  
* Publication source (author(s)).
* Year of publication.
* Power control taxonomy.
* Specific power control technique.
* Contributions.
* Limitations/future work.
## 4 SAR System Requirements Effect on Satellite Design
### System Design and Selection of Parameters  
Having examined the small satellites and their properties, the required peak transmitting power is assumed to be approximately 1 kW. Scenarios are then generated based on the antenna area-power figures presented in the previous sections of this paper. It is evaluated that these power and system performance values are achievable by a micro-sized satellite, as demonstrated by successful real-world operations and tests. The objective is to determine the required SAR antenna area and establish acceptable resolutions, in conjunction with other system input and output parameters. Table 3 presents the scenarios with corresponding input and output parameters.  
In the scenarios discussed, the system parameters have a direct impact on the desired outputs. Minimizing the satellite mass, transmitting power, and antenna area are the key objectives to focus on. While most parameters can be adjusted during the design process, the selection of the altitude of the platform is important not only for radar system design but also for space mission design. This paper presents some of the trade-offs involved in SAR system design. The incidence angle and operating frequency in the X-band are selected for their optimal values. Although the system losses and other SAR parameters can be engineered, the transmitting power and antenna area remain the most significant challenges when designing a microsatellite to meet the desired resolution and system performance.
## 8 PGB Force Coefficients vs. Rotor Speed (Synchronous Frequency Condition)  
The analysis continues for the PGB with dimensions in Table 1 and for clearance \(c^{*}=0.010\) mm, the one providing the peak aerostatic stiffness (\(K_{S}\)). The operating speed range covers 0 to 30 krpm, with a mean operating speed (MOS) \(\Omega^{*}=25\) krpm (417 Hz); hence the shaft surface speed \(\Omega R=120\) m/s. The pressure supply \(p_{S}=2\) bar \(\to 8\) bar, and the ambient pressure \(p_{a}=1\) bar. Note the feed flow parameter \(\Lambda_{\kappa}=\gamma^{2}=5.3\); and at the lowest supply pressure and MOS, \(\Lambda_{\Omega*}=6\frac{\mu\ \Omega_{*}}{p_{S}}\left(\frac{R^{2}}{c^{2}}\right)\) -21, thus indicating a moderate aerodynamic effect will assist with the generation of load capacity.  
Figure 6 depicts the PGB force coefficients vs. shaft speed (\(\Omega\)) and four \(p_{S}\). The coefficients are evaluated at a whirl frequency coinciding with shaft speed (\(\omega=\Omega\)), namely a synchronous speed condition. Note that at the centered condition, \(K_{XX}=K_{YY}\), \(K_{XY}=-K_{YX}\), \(C_{XX}=C_{YY}\), and \(C_{XY}=-C_{YX}\); see Equation (22). Effective force coefficients are  
\[K_{\mathit{eff}}=K_{XX}+C_{XY}\ \omega\ \text{,}\ C_{\mathit{eff}}=C_{XX}-K_{XY} \omega\text{.} \tag{34}\]  
In general, the magnitude of the PGB force coefficients increases as the supply pressure grows. For hybrid operation (aerostatic plus aerodynamic effects), the direct stiffness (\(K_{XX}\)) increases with rotor speed (\(\Omega\)), whereas the direct damping \(C_{XX}\) drops rapidly. At the top speed (30 krpm), \(K_{XX}\) is approximately two times larger than at the low speed (aerostatic) condition. On the other hand, \(C_{XX}\) reduces to \(\sim\)1/5 in magnitude at low shaft speed. The cross-coupled stiffness \(K_{XY}\) (\(<<\)\(K_{XX}\)) is peculiar, as it reverses sign at a certain shaft speed. The larger \(p_{S}\) is, the higher the speed at which \(K_{YX}\) changes from positive to negative. Note \(-C_{XY}<<C_{XX}\) with a peak magnitude at a certain shaft speed. Since \(C_{XY}<0\), then \(K_{\mathit{eff}}<K_{XX}\) for all shaft speeds. At a low shaft speed condition, the effective damping is \(\sim\)50% of \(C_{XX}\). On the other hand, at the high end of shaft speeds, \(C_{\mathit{eff}}\) is slightly larger than \(C_{XX}\) since \(K_{XY}<0\).
# Research on Large Divergence Angle Laser Ranging System +
## 3 Design of Large-Divergence Transmitter and Wide-Field-of-View (WFOV) Receiver Systems
### Beam Quality Simulation of Diverging Lens Optical System  
The light incident on the paraxial sphere at a small angle with the optical axis (\(Z\) axis) is called paraxial light. Let the angle between the paraxial ray and the optical axis be \(\theta\), then \(\sin\theta\approx\theta\) is satisfied, \(\tan\theta\approx\theta\), and \(\cos\theta\approx 1\).  
The original divergence angle of the laser is 12.2 mrad, so it can be obtained that the angle between the light and the laser optical axis is about \(\theta\) = 6.1 mrad \(\approx\) 0.006 rad, then \(\sin\left(\frac{6}{17.45}\right)\) = 0.00598, \(\tan\left(\frac{6}{17.45}\right)\) \(\approx\) 0.006 and \(\cos\left(\frac{6}{17.45}\right)\) = 0.999982 meet paraxial optical conditions. When the paraxial optical conditions are satisfied, the beam conversion can be regarded as not affecting the beam quality.  
The laser spot, after passing through the divergent lens, is simulated at a distance of 100 mm and 1000 m from the lens. The results are shown in Figures 6 and 7 below. It can be seen from the simulation results that the Gaussian distribution of power is ensured for the spot after beam reduction at both short and long distances.  
Figure 5: Real ray tracing data.  
Figure 6: Illuminance simulation diagram at 100 mm.
## 2 Materials and Methods
### Immunofluorescence Analysis of Autophagy Factors LC3 and Beclin-1  
Immunofluorescence analysis was performed according to a previous published method [32]. Briefly, the cells, seeded on coverslip in a six-well plate and subjected to treatments, were fixed in methanol, washed in Phosphate Buffered Saline + Tween 20 (PBS-T) and incubated in 4% bovine serum albumin (BSA) and PBS-T, then further incubated with the LC3 and Beclin-1 primary antibodies for 1 h at room temperature (RT). After washing in PBS-T, the cells were placed in the specific Alexa Fluor 488 secondary antibody (Invitrogen, Thermo Fisher Scientific, Waltham, Massachusetts, USA) for 45 min in a dark room at RT and rinsed with PBS-T, then a coverslip was put onto slide with a drop of 4\({}^{\prime}\),6-Diamidino-2-phenylindole dihydrochloride (DAPI). The slides were examined to analyze LC3 and Beclin-1 expression by Leica Microsystems DM 4500 B Light and Fluorescence Microscopy (Leica Microsystems, Weltzlar, Germany) equipped with a JenoptikProg-Res-C10 Plus Videocam (Jenoptik Optical Systems GmbH, Jena, Germany). A semiquantitative analysis (four fields for each treatment) for the intensity of the fluorescence was completed according to the following grading system [44]: negative, <5%; +/-, 6-10%; +, 11-30%; ++, 31-60%; ++, >61%.
# Propagation Characteristics of Modulated EHF Signal in the Wake Region of Plasma Sheath
###### Abstract
High-frequency signals could penetrate the plasma sheath via wake regions with less signal attenuation compared with other regions of plasma sheaths [30]. In order to make the signals propagate in the wake region, the onboard antenna needs to be installed at the tail of the vehicle. Since the electron density of the tail is the lowest during the evolution of the sheath, the performance of communication via wake region may be better than that via aft region, particularly when relay communication is adopted [31; 32]. The Atmospheric Reentry Demonstrator (ARD) experiment used NASA's Tracking and Data Relay Satellite (TDRS) for communication. During the experiment, the duration of \"blackout\" was much shorter than was expected. Theoretical analysis shows that the shorter \"blackout\" might be attributed to the lower electron density in the wake region [33]. In general, the existing works showed that the wake region has less signal attenuation and that the wake region may be a more ideal antenna installation area. However, it should be noted that \"blackout\" is a communication problem, and many factors may have an important impact on the communication performance, such as signal modulation mode, carrier frequency selection, and antenna orientation. However, so far, there is still a lack of research on these issues. In other words, if the antenna is installed in the wake area, there is a very important and practical issue that is not clear, that is: what is the optimal comprehensive design scheme of the modulation mode, carrier frequency, and antenna direction? In this paper, the communication performance of modulated EHF signals with different modulation modes in different channels in the wake region of a blunt-coned plasma sheath are studied. It aimed to propose the optimal combination design scheme for the modulation mode and the carrier frequency, as well as the optimal channel angle design scheme. The results are helpful in solving the \"blackout\" problem that occurs when relay communication is adopted in engineering.