esa-sceva/satcom-chunk-collection huggingface dataset:
# Advanced Noncoherent Detection in Massive MIMO Systems via Digital Beamspace Preprocessing
###### Abstract  
Noncoherent detection in massive multiple-input/multiple-output (MIMO) uplink systems provides a low-complexity alternative to its coherent counterpart. Requiring no actual channel knowledge but the per-user induced power at the base station, comparable performance as channel-estimation-based detection can be achieved when the users are located in the near-field of the base station. However, noncoherent detection fails in scenarios where users are in the far-field due to an insufficient capability to separate the users in terms of their spatially induced power. For this purpose, a dielectric lens or an analog beamforming structure can be employed, which are capable to focus the power of the incident waves to a smaller subset of the antennas at the base station. These so-called analog beamspace techniques have been demonstrated to enable again the noncoherent detection scheme. Analogous to a spatial Fourier transform, beamspace techniques can be also realized in the digital domain offering more flexibility. Its applicability to noncoherent detection is studied in this paper. It is shown numerically that by means of digital beamspace preprocessing, considerable performance gains can be achieved. Applied in dominant line-of-sight channels, a large number of users can be accommodated and the residual performance gap to coherent detection with perfect channel knowledge is minimal.  
massive MIMO; noncoherent detection; beamspace processing +
Footnote †: journal:
## 3 Results
### Marshall Stability of Cold Bituminous Mixtures  
Table 9 shows the Marshall stability of the examined cold bituminous mixtures at different times.  
Figure 10 shows that B1 had insufficient mechanical characteristics to allow the rapid repair of the runways; B2 had only one specimen able to be tested; B4 did not have consistency: its specimen broke even before being inserted into the press. Only B3 showed mechanical characteristics appropriate for rapid repair.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Product**} & \multicolumn{6}{c}{**Compressive Cubic Strength (MPa)**} \\ \cline{2-9}  & \multicolumn{2}{c}{**Water/Cement Ratio**} & \multicolumn{6}{c}{**Time (h)**} \\  & \multicolumn{2}{c}{**3**} & **6** & **12** & **24** & **72** & **168** & **672** \\ \hline M1 & 0.450 & 0 & 0.5 & 1.8 & 3.5 & 13.4 & 18.6 & 27.2 \\ M2 & 0.450 & 0 & 0.5 & 2.5 & 4.3 & 13.1 & 17.6 & 22.2 \\ M3 & 0.130 & 32.9 & 37.5 & 41.0 & 44.8 & 52.6 & 57.4 & 65.8 \\ M4 & 0.125 & 21.7 & 34.7 & 36.0 & 38.4 & 48.1 & 54.3 & 64.4 \\ M5 & - & - & - & - & - & - & - & - \\ R & - & 4.59 & 4.60 & 4.72 & 4.74 & 4.77 & 5.45 & 54.2 \\ Concrete with cement 32.5 & 0.500 & 0.13 & 1.8 & 11.5 & 19.2 & 30.2 & 33.5 & 48.5 \\ Concrete with cement 42.5 & 0.500 & 0.31 & 2.3 & 12.6 & 20.4 & 32.9 & 38.4 & 54.0 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Compressive cubic strength of cementitious mixes.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Product**} & \multicolumn{6}{c}{**Marshall Stability (daN)**} \\ \cline{2-7}  & \multicolumn{6}{c}{**Time (h)**} \\  & **3** & **6** & **12** & **24** & **48** & **72** \\ \hline B1 & 222 & 238 & 241 & 240 & 266 & 270 \\ B2 & 36 & - & - & - & - & - \\ B3 & 599 & 850 & 1041 & 1232 & 1327 & 1213 \\ B4 & - & - & - & - & - & - \\ \hline \hline \end{tabular}
\end{table}
Table 9: Marshall stability.  
Figure 9: Structural strength depending on time.  
At the end of this laboratory experimentation, the more reliable products which could be used for the runway rapid repair were: M4, B3, and M1. These materials and the expanding resin were used for on-site tests.
# Higher-Order Belief Propagation Correction Decoder for Polar Codes
## 3 Design of Higher-Order Belief Propagation Correction Decoder  
As the SNR increases, the decoding failure is gradually dominated by the graph structure, and the scheme for selecting code bits based on the value of LLR alone is flawed. This section first proposes a metric to effectively select the corrected code bit. Differently from the reduction of the searching range in [22], the stopping tree is selected as a part of the metric. Then, to solve the issue of additional latency caused by bilateral attempts, the original BPC is modified by refining the correction operation with a threshold. Then, a high-order modified BPC decoder is designed to further improve the BLER performance.
# MAC Address Anonymization for Crowd Counting
## 1 Introduction
### Contributions  
The following sections review the crowd monitoring system used in [3; 4] for forecasting purposes and presented in [5] (with fewer details about anonymization than in this manuscript). This paper discusses the strength of our anonymization procedure and the effect of time synchronization inaccuracies on it. Besides the proposal of the anonymization process, our contributions also include the demonstration that our system satisfies the following four requirements:  
1. It is computationally intractable to recover the original MAC addresses from the anonymous identifiers our system generates.
2. Anonymous identifiers from two distinct one-minute time frames cannot be compared against one another, which entails the impossibility to track individuals over time.
3. The proportion of time instants during which two sensors of our system could generate distinct anonymous identifiers for the same MAC address is negligible.
4. Assuming WiFi devices in an area generate \(10^{7}\) distinct MAC addresses within one minute in a monitored area, the collision rate of our anonymization procedure is lower than \(10^{-9}\). The value of \(10^{7}\) distinct MAC addresses corresponds roughly to an event of a few million people, which is comparable to or higher than the number of attendees of the vast majority of public events in the world.  
Requirements (1) and (2) guarantee privacy, in that the original MAC addresses of devices cannot be recovered and also because tracking individuals is impossible. Requirements (3) and (4) enable the central server to compute accurate attendee counts. Should Requirement (3) not be met, sensors would too often return different SA identifiers for identical devices simultaneously detected (because of overlapping detection ranges), thereby inducing a positive counting bias. Requirement (4) ensures a negligible probability of two devices being identified as a single one (which would imply a negative counting bias).  
Proving our system meets Requirement (4) is overwhelmingly a mathematical effort that is based on mathematical approximations of the collision rate of hash functions. This is the most complex result to derive in this paper and, due to its general nature, the theorem approximating the collision rate could be of interest to researchers pursuing other endeavors than the design of a crowd counting system.
# Semantic 3D Reconstruction for Robotic Manipulators with an Eye-In-Hand Vision System
## 5 Discussion and Conclusions  
This paper proposes an algorithm framework for semantic 3D reconstruction using a robotic manipulator with an eye-in-hand camera. Unlike SLAM, SFM, and other multi-angle modeling methods, our approach adds semantic information into the 3D reconstruction process. We have improved the precision of image segmentation by combining deep learning and geometric feature analysis, and we have increased the accuracy of the 3D reconstruction model through the SICP algorithm to optimize camera pose. The semantic information plays two important roles in 3D reconstruction, one of which is providing the foundation for voxel block merging in image segmentation works, and the other is to remove background during the point cloud matching process and improve the accuracy of the ICP algorithm.  
We evaluated the four methods on the YCB Benchmarks and the dataset created by ourselves. The experimental results show that, compared with the deep learning methods, our algorithm is more accurate in the edge segmentation of objects, leading to an improvement of 3D reconstruction. Moreover, the accuracy of the 3D reconstruction of objects is remarkably improved due to the removal of the background interference. Compared with the mask-only, mask + ICP, and SLIC + ICP methods, our method improved the accuracy of the 3D reconstruction on the YCB Benchmarks by 13.65%, 4.01%, and 3.27%, respectively. The same trend was showed on our dataset, with the increasing of the accuracy by 25.49%, 4.93%, and 3.50%, respectively.  
In the future, we will apply this method to more scenarios and objects. Based on semantic 3D reconstruction, we will use the object point cloud model to analyze the spatial topological relationship between objects to obtain the decision of the corresponding capture strategy and then make the autonomous robot planning perform a variety of tasks in a semantic map.  
Conceptualization, F.Z. and Y.F. methodology, F.Z. software, Y.F. validation, Y.F., P.W. and W.G. formal analysis, Y.F. writing-original draft preparation, F.Z. writing-review and editing, Y.F.; visualization, Y.F.; supervision, M.L. and H.C. project administration, M.L. funding acquisition, M.L. and X.W. All authors have read and agreed to the published version of the manuscript. This research was funded by [Natural Science Foundation of China] grant number [61773139], [Shenzhen Science and Technology Program] grant number [KQTD2016112515134654], and [Shenzhen Special Fund for Future Industrial Development] grant number [JCYJ20160425150757025]. This work was supported by Natural Science Foundation of China (No.61773139), Shenzhen Science and Technology Program (No.KQTD2016112515134654) and Shenzhen Special Fund for Future Industrial Development (No.JCYJ20160425150757025). The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
## 3 Numerical Validation
### Flying Wing with Coupled Flight Dynamics and Aeroelasticity
#### 3.2.4 Effects of Mass Distribution on Longitudinal Stability  
It is known from the results and analyses presented in Section 3.2.1 that the spanwise distribution of mass will affect the trimmed state of the aircraft, which will further influence the flight dynamic characteristics. It can be inferred that the mass distribution in spanwise will alter the longitudinal stability, changing the unstable phugoid mode into a stable one.  
In this experiment, part of the 152 kg payload remained in the central pod, and the remaining mass was distributed equally to the left and right ones.  
Figure 13 shows the variations of the altitude of the mid-span of the highly flexible aircraft with, respectively, 100%, 95%, 90% and 80% of the total payload mass on the central pod and the rest on the side ones.  
It can be clearly seen that, in the case of the same total payload, with the reduction of the mass at central pod, the amplitude of oscillation decreases dramatically; the frequency also decreases to some extent. When the mass on the central pod reduces to 80% of the total payload, the amplitude of oscillation after perturbation even begins to decay.  
With the varying distributions of payload mass, other parameters (the airspeeds and AOAs) have the same trend as the altitude of the aircraft, which are not explain in details here. Generally, for a rigid  
Figure 12: AOA at mid-span with different payload.  
straight wing without sweep and dihedral, the effects of spanwise mass distributions on longitudinal stability and dynamic responses are negligible. However, it clearly tells that the longitudinal stability and dynamic responses of a flexible wing will be significantly affected by the spanwise mass distributions. With the same mass of payload, a span-loaded aircraft is more stable than a center-loaded one.
## 1 Introduction
### Problems in the Application of DE-XRT
#### 1.4.3. Fan-Shaped Effect  
The fan-shaped effect is shown in Figure 1. The X-ray source is approximate to a point light source. The change of the distance \(d_{x}\) from the detector directly below its focus will cause the detected signal to change, which mainly brings about the following influences: (i) the greater the \(d_{x}\) is, the greater the ray energy attenuation due to distance. The larger the \(d_{x}\) is, the more the thickness of the penetrated material increases compared to the actual material thickness, which leads to more attenuation of the detected signal. (ii) The larger the \(d_{x}\) is, the greater the increase in thickness of the penetrated materials compared with the actual material thickness due to the relationship between the right side of a right triangle and the hypotenuse, which will cause more attenuation of the detected signal. (iii) Similarly, the difference in the \(d_{x}\) leads to a change in thickness of X-ray penetrating copper sheets  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Shading of** & **Exposure** & \begin{tabular}{c} **Mass** \\ **Thickness** \\ \end{tabular} & **SNR** & **Contrast** & \(\textit{TIT}_{\textbf{0}}\) & \
\begin{tabular}{c} **Impact on** \\ **R\_Value** \\ \end{tabular} &
\begin{tabular}{c} **Sorting-** \\ **Ability** \\ \end{tabular} \\ \hline Too small & Overex & Small & Small & Small & Large & Large & Poor \\ Too large & Underexposure & Large & Large & Large & Small & Large & Poor \\ \hline \hline \end{tabular}
\end{table}
Table 1: Influence of XRT parameters on measurement.  
between the low and high energy due to the relationship between the right side of a right triangle and the hypotenuse, which will vary filtering of low-energy signals. This has a certain impact on the R_value, mass and center-of-gravity coordinates calculation.
## 3 Results and Analysis
### Effect of Different Treatments on Crystallization Properties of Wood
#### 3.1.2 Effect of Wood Veneer Metallization on Crystallization Properties of Wood  
The effect of wood veneer metallization on the crystallization properties of structural wood is shown in Figure 3. The relative intensity of the diffraction peak on the crystalline surface (002) decreases by 11.2% when coating time is 50 s, 6.3% when coating time is 150 s, 13.3% when coating time is 10 min, and 19.8% when coating time is 15 min. Additionally, the intensity of the diffraction peak of the sample at 15 min (200 \({}^{\circ}\)C) decreased by 25.5%. One of the reasons for the decrease in diffraction peak intensity is that the thickness of copper film increases and the depth of X-ray radiation in wood decreases with the increase in coating time. Another reason is that the deposited copper film absorbs and reflects the diffraction line of wood, which also causes the peak intensity of wood cellulose to decrease [25]. The relative crystallinity of wood cellulose is calculated according to the formula of crystallinity in Formula (1). The crystallinity changes of different treatment methods are shown in Table 2. Comparing the sample after copper plating with the sample before copper plating (ethanol ultrasonic treatment), the crystallinity of the sample after copper plating hardly changed, and the change rule is not obvious. The cellulose molecular chains in the wood crystalline region are orderly arranged, and the sputtered copper atoms cannot enter the crystallization region. However, although the structure of the amorphous region is loose, ultrasonic treatment of the wood veneer will cause alcohol molecules to occupy the voids of the wood in the amorphous region, stimulating the surface activity of cellulose microfibrils in the amorphous region. The resulting hydroxyl group makes the microfibrils in the amorphous region tend to be ordered. In group e of Table 2, since the density of this group of wood samples may be uneven at different locations, ultrasonic treatment has a lesser effect on locations with higher density. The difference in the content and structure of the wood itself will also lead to different degrees of crystallinity [26]. Although the crystallinity of the wood treated by ultrasonic has little change, it will increase the permeability of the wood [17; 27; 28]. During the coating process, the sputtered copper atoms only partially enter the voids on the surface of the wood and penetrate into the amorphous region of the wood cell wall, which has little effect on the crystallinity of the wood cellulose [15; 17].
## 4 Simulation Results and Discussion  
Here, the results obtained from EH scheduling and management in different networks in the day-ahead markets facing EGHNs are presented. The EH scheduling problem is presented as an optimization problem with the aim of maximizing the profit of hubs. In this study, the IFLA algorithm has been employed to optimize the problem under study, and a comparison is made between the suggested algorithm and conventional FLA, PSO, and MRFO. Population size, maximum iteration, and independent executions of each algorithm are selected as 100, 200, and 25, respectively. Table 1 lists the control parameters of the algorithms. It should be noted that the control parameters of different methods are the values provided by their authors in reference papers. In this study, the parameters of the conventional FLA algorithm are considered the same as the parameters set by its authors. Although the authors have checked the setting of these parameters and found that the parameters set by the authors of the algorithm provide the best results for base simulation with the FLA.
# Image-Based Tactile Deformation Simulation and Pose Estimation for Robot Skill Learning
## 1 Introduction
### Current TacTip Simulation Methods and Limitations  
Several TacTip simulation methods have been developed to enhance its applications. For instance, ref. [12] developed a soft body simulation for TacTip using the Unity simulation engine. The simulation results showed that the error in pin position was less than 1 mm. However, the simulated shape exhibited relatively high strain in the part of the skin that contacted the object, which differs from real-world TacTip behavior, as the strain of the deformed tip of TacTip is negligible overall. In [4], the simulated TacTip feedback was generated as a depth image following methods from [13,14]. Notably, the simulated depth image is not directly related to real-world TacTip feedback. Instead, a GAN [15] is trained to translate the real-world feedback into simulated feedback, which can then be used for robot policy generation. Similarly, in [5], a GAN was trained to translate real-world image feedback to match the simulated depth image. Furthermore, a saliency map was used to extract desired features, and the extracted features were denoised. The method introduced in [4] is further expanded in [16] to include three types of tactile sensors, including TacTip.  
The primary challenge of TacTip application is extracting depth information from the observed pin distribution. The relationship between actual depth and the feedback from the TacTip camera is unintuitive, as the observation is the position of pins projected onto a 2D plane. Current methods mostly use machine learning [4,17,18] to interpret the pin position to depth information. The exact mathematical relation of depth and pin position in TacTip has yet to be established. Without a mathematical model, the simulation of TacTip is difficult to explain and adjust due to the black-box-like nature of neural networks.
# B5 GEMINI: AI-Driven Network Digital Twin
## 1 Introduction
B5 GEMINI will enable an extensive use of advanced AI mechanisms to realize several valuable AI applications, such as (i) the training and testing of ML components to deploy smart applications such as cybersecurity or network management in real-time environments; (ii) the development of intelligent support to management, orchestration, and dynamic control of the network components (e.g., Virtual Network Functions--VNFs, Network Services--NS and Slices); (iii) the use of the NDT as a platform to perform distributed training and inference processes for ML and DL models using on-demand GPU virtualization; (iv) ML as a service to deploy off-the-shelf pre-trained ML models in the NDT allocated resources to perform ML tasks with a high degree of efficiency, avoiding costly training and testing tasks; (v) the use of the NDT for network deployment planning. In addition, B5 GEMINI will allow one to realize several interesting use cases, such as (i) the design of ML components for network cybersecurity capabilities and (ii) the leverage NDT as a validation environment for energy consumption optimization of the ML/DL components deployed in the real network. It is worth noting that other types of applications, such as cyber-ranges or educational applications in general, could greatly benefit from the use of a realistic and controlled 5G/6G network environment such as B5 GEMINI, even if only the virtual twin is used. Finally, and regarding that the time and cost of planning, designing, and implementing a complete NDT system from scratch can be unaffordable, B5 GEMINI includes in its design a modular building approach based on the Digital Map concept, which is a novel concept that has appeared in recent IETF discussions as a possible way to specifically solve this problem. The remainder of this work is organized as follows: Section 2 reviews the literature on the application of AI methods in NDTs and presents the state-of-the-art in the field. Section 3 describes the B5 GEMINI architecture, providing details of the underlaying infrastructure and the integration of the 5G core capabilities in it. Section 4 details several interesting applications that B5 GEMINI can address, and Section 5 presents the main B5 GEMINI AI components jointly with the open challenges associated with their deployment. Section 6 presents two notable use cases related to cyber-security and energy efficiency. In addition, the second use case depicts the application of the novel concept of Digital Maps for a modular NDT construction. Finally, Section 7 summarizes the main findings of this work.