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Selected Papers from 14th International Conference on Signal Processing and...
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Selected Papers from 14th International Conference on Signal Processing and Communication Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 54733

Special Issue Editor

Prof. Dr. Tadeusz A. Wysocki

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Interests: modulation techniques; propagation of microwaves; diversity combining; space-time processing; NOMA, nano-communications; signal formats for wireless communications

Special Issue Information

Dear Colleagues,

The 14th International Conference on Signal Processing and Communication Systems, ICSPCS’2020, follows the very successful ICSPCS'2018 and ICSPCS'2019. A major objective of the Conference is to pursue the progression from communication and information theory through to the implementation, evaluation and performance improvement of practical communication systems using signal processing technology. The Conference is also planned to be a forum for presenting research into topics ranging from those of the physical layer to the application layer. All aspects of the protocols and processes required for the future communication systems to operate better and the applications to utilize the full potential offered by the current and the emerging networking infrastructure are also encompassed. Papers dealing with signal processing for 5G and beyond and for minimizing energy use (Green Communications) are very welcome, too. Similarly, the conference welcomes papers concerned with protocols for the Internet of Things (IoT) and Smart Grid. In addition, we expect that, as during the previous events, there will be several papers dealing with image, video and audio processing for multimedia, medical and forensic applications, with the security of networks and information transmitted and stored, as well as other unconventional applications of signal processing and/or telecommunications modeling techniques. This special issue will be composed of selected papers from ICSPCS’2020 Conference, extended and reviewed to meet the high standard of Journal publications.

Prof. Dr. Tadeusz A. Wysocki
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • Signal Processing
  • Wireless Networks
  • 5G
  • Wireless Communication
  • Sensor Networks
  • Multimedia Communication
  • Communication System Security
  • Data Security
  • Information Theory
  • Communication Theory
  • Modeling Biological Systems

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Published Papers (17 papers)

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Research

27 pages, 8697 KiB  
Article
Maximizing Channel Capacity of 3D MIMO System via Antenna Downtilt Angle Adaptation Using a Q-Learning Algorithm
by Shu-Hung Lee, Xiao-Pei Shi, Tan-Hsu Tan, Yu-Che Tung and Yung-Fa Huang
Electronics 2022, 11(8), 1189; https://doi.org/10.3390/electronics11081189 - 8 Apr 2022
Cited by 2 | Viewed by 1970
Abstract
3D MIMO introduces the vertical dimension of the antenna downtilt angle to make the direction of signal transmission more accurate to improve system capacity. In this paper, we verify the effect of antenna downtilt angle on channel capacity through simulations of four fixed [...] Read more.
3D MIMO introduces the vertical dimension of the antenna downtilt angle to make the direction of signal transmission more accurate to improve system capacity. In this paper, we verify the effect of antenna downtilt angle on channel capacity through simulations of four fixed antenna downtilt angles, 90, 96, 99, and 102 degrees under the conditions that the distance between mobile station (MS) and base station (BS) is 250 m, and the heights of antenna in BS and MS are 25 m and 1.5 m, respectively. The simulation results show that the antenna downtilt angle of 96 degrees has a larger channel capacity than the others. In addition, we proposed an adaptive optimization method by applying the Q-learning algorithm to adaptively optimize the antenna downtilt angles to maximize system capacity. The performance of the proposed method is to investigate the Q-learning algorithm with three different discount rates at 0.9, 0.5, and 0.1, and four different propagation distances on 20 × 1 and 60 × 4 MIMO. We demonstrate that there is only a 1% difference between the adaptively optimized antenna downtilt angle and the ideal optimal antenna downtilt angle when the discount rate of Q-learning algorithm is 0.9, and its channel capacity performance can reach more than 99.72% of the ideal optimal one. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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17 pages, 4588 KiB  
Article
AlexNet Convolutional Neural Network for Disease Detection and Classification of Tomato Leaf
by Hsing-Chung Chen, Agung Mulyo Widodo, Andika Wisnujati, Mosiur Rahaman, Jerry Chun-Wei Lin, Liukui Chen and Chien-Erh Weng
Electronics 2022, 11(6), 951; https://doi.org/10.3390/electronics11060951 - 18 Mar 2022
Cited by 133 | Viewed by 11403
Abstract
With limited retrieval of reserves and restricted capability in plant pathology, automation of processes becomes essential. All over the world, farmers are struggling to prevent various harm from bacteria or pathogens such as viruses, fungi, worms, protozoa, and insects. Deep learning is currently [...] Read more.
With limited retrieval of reserves and restricted capability in plant pathology, automation of processes becomes essential. All over the world, farmers are struggling to prevent various harm from bacteria or pathogens such as viruses, fungi, worms, protozoa, and insects. Deep learning is currently widely used across a wide range of applications, including desktop, web, and mobile. In this study, the authors attempt to implement the function of AlexNet modification architecture-based CNN on the Android platform to predict tomato diseases based on leaf image. A dataset with of 18,345 training data and 4,585 testing data was used to create the predictive model. The information is separated into ten labels for tomato leaf diseases, each with 64 × 64 RGB pixels. The best model using the Adam optimizer with a realizing rate of 0.0005, the number of epochs 75, batch size 128, and an uncompromising cross-entropy loss function, has a high model accuracy with an average of 98%, a strictness rate of 0.98, a recall value of 0.99, and an F1-count of 0.98 with a loss of 0.1331, so that the classification results are good and very precise. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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13 pages, 2283 KiB  
Article
Performance Analysis of AF Cooperative Relaying Networks with SWIPT
by Zih-Sin Wang, Liang-Hung Lin, Jyh-Horng Wen, Yen-Ju Lin and Chien-Erh Weng
Electronics 2022, 11(4), 589; https://doi.org/10.3390/electronics11040589 - 15 Feb 2022
Cited by 2 | Viewed by 2072
Abstract
Cooperative communication networks have received more attention due to its ability to improve the signal quality of terminal devices by spatial diversity. Under recent advance in internet of things, In order to extend the service life of terminal devices powered by battery, simultaneous [...] Read more.
Cooperative communication networks have received more attention due to its ability to improve the signal quality of terminal devices by spatial diversity. Under recent advance in internet of things, In order to extend the service life of terminal devices powered by battery, simultaneous wireless information and power transfer (SWIPT) technique has been emphasize. The terminal devices can harvest energy and decode information from the same radio frequency (RF) signal using by SWIPT technique. In this paper, we combine both techniques to study the performance of both conventional cooperative relaying networks without SWIPT and cooperative relaying networks with SWIPT under an amplify-and-forward (AF) relaying network. To the best of our knowledge, no one simultaneously studies and compares the performance of both systems. Therefore, the outage probabilities of both systems are carried out, and numerical results are compared in this paper. The main results include: (1) Compared with conventional cooperative communication, the cooperative communication with SWIPT has better outage probability only when the distance between relay node and source node is less than one. It implies that, to outperform the conventional cooperative communication, the relay node should harvest enough energy for signal transmission. (2) With the diversity of direct path and relay path, the outage probability of cooperative communication with EH under an AF relaying network has been significantly reduced. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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13 pages, 4581 KiB  
Article
Performance on Multiple Pilot-Based Grouping Methods in Satellite-Terrestrial Cooperative Wireless Networks
by Jheng-Sian Li, Jyh-Horng Wen, Chung-Hua Chiang and Chien-Erh Weng
Electronics 2022, 11(3), 430; https://doi.org/10.3390/electronics11030430 - 30 Jan 2022
Viewed by 1942
Abstract
The grouping method is an efficient transmitting strategy in a spatial diversity system. In this paper, relay-based grouping methods in satellite terrestrial cooperative wireless networks are proposed. The proposed methods focus on finding out the best two signals received from relay stations in [...] Read more.
The grouping method is an efficient transmitting strategy in a spatial diversity system. In this paper, relay-based grouping methods in satellite terrestrial cooperative wireless networks are proposed. The proposed methods focus on finding out the best two signals received from relay stations in a user’s neighborhood and use the advantage of space diversity to overcome the effect of channel fading. A grouping method, called the pilot-based grouping method was proposed in our previous work. In order to improve the grouping success rate and the channel capacity, a modified grouping method is proposed. In addition, for a single relay the modified grouping method can achieve better results than the pilot-based grouping method. In the end, several analysis strategies of the grouping method for multimedia broadcast and multicast services in satellite terrestrial cooperative networks are proposed. The simulation results show the performance improvement and the system evaluation for different quality of services in the demanded relay-based cooperative networks. The proposed modified grouping methods can be widespread in any relay-based cooperative networks. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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13 pages, 4565 KiB  
Article
Cost-Effective Data Aggregation Method for Smart Grid
by Hsi-Chou Hsu, Shi-Ren Zhuang and Yung-Fa Huang
Electronics 2021, 10(23), 2911; https://doi.org/10.3390/electronics10232911 - 24 Nov 2021
Cited by 2 | Viewed by 1937
Abstract
Finding a more efficient use of energy is an important problem that needs attention. Compared with the traditional power grid, a smart grid can monitor users’ electricity situation and electricity consumption instantly. However, it involves many problems of deploying network equipment. Consequently, it [...] Read more.
Finding a more efficient use of energy is an important problem that needs attention. Compared with the traditional power grid, a smart grid can monitor users’ electricity situation and electricity consumption instantly. However, it involves many problems of deploying network equipment. Consequently, it is vital to promote smart grids by collecting data from smart meters efficiently and keeping costs low. In this article, we propose a two-stage method of data collection for smart grids. The main contribution of this paper is to lower the number of data aggregation points (DAPs) so that the cost can be reduced. By using the K-means method, an entire smart grid can be divided into many smaller parts. In addition, the needs of transmitting and receiving data in the entire smart grid can be met by installing the least number of DAPs. Finally, the simulations show that the proposed two-stage method of data collection can use fewer DAPs to collect data than other methods which use one-stage methods, so the proposed scheme is more cost-effective. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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16 pages, 7667 KiB  
Article
An Efficient Indoor Positioning Method with the External Distance Variation for Wireless Networks
by Ching-Mu Chen, Yung-Fa Huang and You-Ting Jheng
Electronics 2021, 10(16), 1949; https://doi.org/10.3390/electronics10161949 - 12 Aug 2021
Cited by 6 | Viewed by 2419
Abstract
This study strengthens the external distance variation for the indoor positioning performance. With the received signal strength (RSS) of the unknown node, a localization is performed to positioning its coordinates. The mean square error (MSE) of localization is deteriorated by the shadowing effect [...] Read more.
This study strengthens the external distance variation for the indoor positioning performance. With the received signal strength (RSS) of the unknown node, a localization is performed to positioning its coordinates. The mean square error (MSE) of localization is deteriorated by the shadowing effect and the MSE depends on the location of reference nodes. Moreover, the minimum mean square error (MMSE) algorithm is also used with the RSS. The amount of variation in the distance between the reference point and the positioning node will also affect the accuracy. Therefore, this paper considers the distance between the reference point and the positioning node and also the distance variation between the reference points. MSE is used to estimate positioning performance and Monte Carlo is also used to simulate the average error of different shadowing and decay environments. When reference nodes have known distances, the distance is obtained separately and the estimated distances are identified by the MMSE method. In order to reduce the number of reference nodes and calculation cost, this paper uses adaptive reference node selection to improve the accuracy of positioning. Simulation results show that the external distance variation mechanism strengthens the indoor positioning performance. Moreover, this paper investigates the performance of several reference nodes (three, four, five, and six reference nodes) through 3D graphs to estimate the small range area. The differences are more clearly observed with fewer reference nodes and lower MSE. Finally, simulation results show that the MSE value of fixed three reference nodes is almost 100% better with external distance variation method compared to the random selected three reference nodes. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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16 pages, 1293 KiB  
Article
Lightweight Physical Layer Aided Key Agreement and Authentication for the Internet of Things
by Seungnam Han, Yonggu Lee, Jinho Choi and Euiseok Hwang
Electronics 2021, 10(14), 1730; https://doi.org/10.3390/electronics10141730 - 19 Jul 2021
Cited by 5 | Viewed by 2743
Abstract
In this paper, we propose a lightweight physical layer aided authentication and key agreement (PL-AKA) protocol in the Internet of Things (IoT). The conventional evolved packet system AKA (EPS-AKA) used in long-term evolution (LTE) systems may suffer from congestion in core networks by [...] Read more.
In this paper, we propose a lightweight physical layer aided authentication and key agreement (PL-AKA) protocol in the Internet of Things (IoT). The conventional evolved packet system AKA (EPS-AKA) used in long-term evolution (LTE) systems may suffer from congestion in core networks by the large signaling overhead as the number of IoT devices increases. Thus, in order to alleviate the overhead, we consider cross-layer authentication by integrating physical layer approaches to cryptography-based schemes. To demonstrate the feasibility of the PL-AKA, universal software radio peripheral (USRP) based tests are conducted as well as numerical simulations. The proposed scheme shows a significant reduction in the signaling overhead, compared to the conventional EPS-AKA in both the simulation and experiment. Therefore, the proposed lightweight PL-AKA has the potential for practical and efficient implementation of large-scale IoT networks. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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16 pages, 1245 KiB  
Article
Multi-Kernel Polar Codes versus Classical Designs with Different Rate-Matching Approaches
by Souradip Saha and Marc Adrat
Electronics 2021, 10(14), 1717; https://doi.org/10.3390/electronics10141717 - 17 Jul 2021
Cited by 3 | Viewed by 2314
Abstract
Polar codes, which have been proposed as a family of linear block codes, has garnered a lot of attention from the scientific community, owing to their low-complexity implementation and provably capacity-achieving capability. Thus, they have been proposed to be used for encoding information [...] Read more.
Polar codes, which have been proposed as a family of linear block codes, has garnered a lot of attention from the scientific community, owing to their low-complexity implementation and provably capacity-achieving capability. Thus, they have been proposed to be used for encoding information on the control channels in the upcoming 5G wireless networks. The basic approach introduced by Arikan in his landmark paper to polarize bit channels of equal capacities to those of unequal capacities can be used to design only codewords of length N=2n, which is a major limitation when codewords of different lengths are required for the underlying applications. In the predecessor paper, this aspect was partially addressed by using a 3×3 kernel circuit (used to generate codewords of length M=3m), along with downsizing techniques such as puncturing and shortening to asses the optimal design and resizing techniques based on the underlying system parameters. In this article, we extend this research to include the assessment of multi-kernel rate-matched polar codes for applicability over a much wider range of codeword lengths. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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21 pages, 1645 KiB  
Article
Low-Complexity Aggregation Techniques for DOA Estimation over Wide-RF Bandwidths
by Ronald Mulinde, Mayank Kaushik, Manik Attygalle and Syed Mahfuzul Aziz
Electronics 2021, 10(14), 1707; https://doi.org/10.3390/electronics10141707 - 16 Jul 2021
Cited by 3 | Viewed by 2107
Abstract
Accurate direction of arrival (DOA) estimation of wideband, low-power nonstationary signals is important in many radio frequency (RF) applications. This article analyses the performance of two incoherent aggregation techniques for the DOA estimation of high chirp-rate linear frequency modulated (LFM) signals used in [...] Read more.
Accurate direction of arrival (DOA) estimation of wideband, low-power nonstationary signals is important in many radio frequency (RF) applications. This article analyses the performance of two incoherent aggregation techniques for the DOA estimation of high chirp-rate linear frequency modulated (LFM) signals used in modern radar and electronic warfare (EW) applications. The aim is to determine suitable aggregation techniques for blind DOA estimation for real-time implementation with a frequency channelised signal. The first technique calculates a single pseudospectrum by directly combining the spatial covariance matrices from each of the frequency bins. The second technique first calculates the spatial pseudospectra from the spatial covariance matrix (SCM) from each frequency bin and then combines the spatial pseudospectra into one single estimate. Firstly, for single and multiple signal emitters, we compare the DOA estimation performance of incoherent SCM-based aggregation with that of the incoherent spatial pseudospectra-based aggregation using the root mean-squared error (RMSE). Secondly, we determine the types of signals and conditions for which these incoherent aggregation techniques are more suited. We demonstrate that the low-complexity SCM-based aggregation technique can achieve relatively good estimation performance compared to the pseudospectra-based aggregation technique for multiple narrowband signal detection. However, pseudospectra aggregation is better suited for single wideband emitter detection. Both the incoherent aggregation techniques presented in this article offer a computational advantage over the coherent processing techniques and hence are better suited for real-time implementation. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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14 pages, 718 KiB  
Article
Evaluation of Transmission Properties of Networks Described with Reference Graphs Using Unevenness Coefficients
by Sławomir Bujnowski, Beata Marciniak, Zbigniew Lutowski, Adam Flizikowski and Olutayo Oyeyemi Oyerinde
Electronics 2021, 10(14), 1684; https://doi.org/10.3390/electronics10141684 - 14 Jul 2021
Cited by 3 | Viewed by 1866
Abstract
This paper discusses an evaluation method of transmission properties of networks described with regular graphs (Reference Graphs) using unevenness coefficients. The first part of the paper offers generic information about describing network topology via graphs. The terms ‘chord graph’ and ‘Reference Graph’, which [...] Read more.
This paper discusses an evaluation method of transmission properties of networks described with regular graphs (Reference Graphs) using unevenness coefficients. The first part of the paper offers generic information about describing network topology via graphs. The terms ‘chord graph’ and ‘Reference Graph’, which is a special form of a regular graph, are defined. The operating principle of a basic tool used for testing the network’s transmission properties is discussed. The next part consists of a description of the searching procedure of the shortest paths connecting any two nodes of a graph and the method determining the number of uses of individual graph edges. The analysis shows that using particular edges of a graph depends on two factors: their total number in minimum length paths and their total number in parallel paths connecting the graph nodes. The latter makes it possible to define an unevenness coefficient. The calculated values of the unevenness coefficients can be used to evaluate the transmission properties of networks and to control the distribution of transmission resources. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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26 pages, 5653 KiB  
Article
Deep Learning Techniques for the Classification of Colorectal Cancer Tissue
by Min-Jen Tsai and Yu-Han Tao
Electronics 2021, 10(14), 1662; https://doi.org/10.3390/electronics10141662 - 12 Jul 2021
Cited by 58 | Viewed by 6164
Abstract
It is very important to make an objective evaluation of colorectal cancer histological images. Current approaches are generally based on the use of different combinations of textual features and classifiers to assess the classification performance, or transfer learning to classify different organizational types. [...] Read more.
It is very important to make an objective evaluation of colorectal cancer histological images. Current approaches are generally based on the use of different combinations of textual features and classifiers to assess the classification performance, or transfer learning to classify different organizational types. However, since histological images contain multiple tissue types and characteristics, classification is still challenging. In this study, we proposed the best classification methodology based on the selected optimizer and modified the parameters of CNN methods. Then, we used deep learning technology to distinguish between healthy and diseased large intestine tissues. Firstly, we trained a neural network and compared the network architecture optimizers. Secondly, we modified the parameters of the network layer to optimize the superior architecture. Finally, we compared our well-trained deep learning methods on two different histological image open datasets, which comprised 5000 H&E images of colorectal cancer. The other dataset was composed of nine organizational categories of 100,000 images with an external validation of 7180 images. The results showed that the accuracy of the recognition of histopathological images was significantly better than that of existing methods. Therefore, this method is expected to have great potential to assist physicians to make clinical diagnoses and reduce the number of disparate assessments based on the use of artificial intelligence to classify colorectal cancer tissue. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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32 pages, 10712 KiB  
Article
Viewing Direction Based LSB Data Hiding in 360° Videos
by Dang Ninh Tran, Hans-Jürgen Zepernick and Thi My Chinh Chu
Electronics 2021, 10(13), 1527; https://doi.org/10.3390/electronics10131527 - 24 Jun 2021
Cited by 1 | Viewed by 2326
Abstract
In this paper, we propose a viewing direction based least significant bit (LSB) data hiding method for 360° videos. The distributions of viewing direction frequency for latitude and longitude are used to control the amount of secret data to be hidden at the [...] Read more.
In this paper, we propose a viewing direction based least significant bit (LSB) data hiding method for 360° videos. The distributions of viewing direction frequency for latitude and longitude are used to control the amount of secret data to be hidden at the latitude, longitude, or both latitude and longitude of 360° videos. Normalized Gaussian mixture models mimicking the viewing behavior of humans are formulated to define data hiding weight functions for latitude, longitude, and both latitude and longitude. On this basis, analytical expressions for the capacity offered by the proposed method to hide secret data in 360° cover videos are derived. Numerical results for the capacity using different numbers of bit planes and popular 360° video resolutions for data hiding are provided. The fidelity of the proposed method is assessed in terms of the peak signal-to-noise ratio (PSNR), weighted-to-spherically uniform PSNR (WS-PSNR), and non-content-based perceptual PSNR (NCP-PSNR). The experimental results illustrate that NCP-PSNR returns the highest fidelity because it gives lower weights to the impact of LSB data hiding on fidelity outside the front regions near the equator. The visual quality of the proposed method as perceived by humans is assessed using the structural similarity (SSIM) index and the non-content-based perceptual SSIM (NCP-SSIM) index. The experimental results show that both SSIM-based metrics are able to account for the spatial perceptual information of different scenes while the PSNR-based fidelity metrics cannot exploit this information. Furthermore, NCP-SSIM reflects much better the impact of the proposed method on visual quality with respect to viewing directions compared to SSIM. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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20 pages, 4624 KiB  
Article
A Gravity Inspired Approach to Multiple Target Localization Through-the-Wall Using Non-Coherent Bi-Static Radar
by Imran Mohammed, Iain B. Collings and Stephen V. Hanly
Electronics 2021, 10(13), 1524; https://doi.org/10.3390/electronics10131524 - 23 Jun 2021
Cited by 2 | Viewed by 2573
Abstract
This paper considers multiple target localization using a non-coherent bi-static radar with multiple receivers, where the targets are located behind a wall. This paper presents a new clustering algorithm inspired by Newtonian gravity that iteratively groups particles at target locations and eliminates particles [...] Read more.
This paper considers multiple target localization using a non-coherent bi-static radar with multiple receivers, where the targets are located behind a wall. This paper presents a new clustering algorithm inspired by Newtonian gravity that iteratively groups particles at target locations and eliminates particles at non-target locations. We first propose a histogram based pre-processing algorithm that imposes a grid over the region of interest and defines a particle with measurement-dependent mass for each grid square. We then calculate a Newtonian inspired force on each of the particles and move them in the direction of the force. We repeat the process until there is no further movement. The proposed algorithm works even when some of the measurements are unavailable or missing and when some of the measurements are false measurements. Location accuracy is shown to be in the order of 8 cm. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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21 pages, 513 KiB  
Article
Genetic Algorithms to Maximize the Relevant Mutual Information in Communication Receivers
by Jan Lewandowsky, Sumedh Jitendra Dongare, Rocío Martín Lima, Marc Adrat, Matthias Schrammen and Peter Jax
Electronics 2021, 10(12), 1434; https://doi.org/10.3390/electronics10121434 - 15 Jun 2021
Cited by 2 | Viewed by 2446
Abstract
The preservation of relevant mutual information under compression is the fundamental challenge of the information bottleneck method. It has many applications in machine learning and in communications. The recent literature describes successful applications of this concept in quantized detection and channel decoding schemes. [...] Read more.
The preservation of relevant mutual information under compression is the fundamental challenge of the information bottleneck method. It has many applications in machine learning and in communications. The recent literature describes successful applications of this concept in quantized detection and channel decoding schemes. The focal idea is to build receiver algorithms intended to preserve the maximum possible amount of relevant information, despite very coarse quantization. The existent literature shows that the resulting quantized receiver algorithms can achieve performance very close to that of conventional high-precision systems. Moreover, all demanding signal processing operations get replaced with lookup operations in the considered system design. In this paper, we develop the idea of maximizing the preserved relevant information in communication receivers further by considering parametrized systems. Such systems can help overcome the need of lookup tables in cases where their huge sizes make them impractical. We propose to apply genetic algorithms which are inspired from the natural evolution of the species for the problem of parameter optimization. We exemplarily investigate receiver-sided channel output quantization and demodulation to illustrate the notable performance and the flexibility of the proposed concept. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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24 pages, 7183 KiB  
Article
Research on QoS Classification of Network Encrypted Traffic Behavior Based on Machine Learning
by Yung-Fa Huang, Chuan-Bi Lin, Chien-Min Chung and Ching-Mu Chen
Electronics 2021, 10(12), 1376; https://doi.org/10.3390/electronics10121376 - 8 Jun 2021
Cited by 15 | Viewed by 3379
Abstract
In recent years, privacy awareness is concerned due to many Internet services have chosen to use encrypted agreements. In order to improve the quality of service (QoS), the network encrypted traffic behaviors are classified based on machine learning discussed in this paper. However, [...] Read more.
In recent years, privacy awareness is concerned due to many Internet services have chosen to use encrypted agreements. In order to improve the quality of service (QoS), the network encrypted traffic behaviors are classified based on machine learning discussed in this paper. However, the traditional traffic classification methods, such as IP/ASN (Autonomous System Number) analysis, Port-based and deep packet inspection, etc., can classify traffic behavior, but cannot effectively handle encrypted traffic. Thus, this paper proposed a hybrid traffic classification (HTC) method based on machine learning and combined with IP/ASN analysis with deep packet inspection. Moreover, the majority voting method was also used to quickly classify different QoS traffic accurately. Experimental results show that the proposed HTC method can effectively classify different encrypted traffic. The classification accuracy can be further improved by 10% with majority voting as K = 13. Especially when the networking data are using the same protocol, the proposed HTC can effectively classify the traffic data with different behaviors with the differentiated services code point (DSCP) mark. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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13 pages, 683 KiB  
Article
Prediction of Public Trust in Politicians Using a Multimodal Fusion Approach
by Muhammad Shehram Shah Syed, Elena Pirogova and Margaret Lech
Electronics 2021, 10(11), 1259; https://doi.org/10.3390/electronics10111259 - 25 May 2021
Cited by 7 | Viewed by 2571
Abstract
This paper explores the automatic prediction of public trust in politicians through the use of speech, text, and visual modalities. It evaluates the effectiveness of each modality individually, and it investigates fusion approaches for integrating information from each modality for prediction using a [...] Read more.
This paper explores the automatic prediction of public trust in politicians through the use of speech, text, and visual modalities. It evaluates the effectiveness of each modality individually, and it investigates fusion approaches for integrating information from each modality for prediction using a multimodal setting. A database was created consisting of speech recordings, twitter messages, and images representing fifteen American politicians, and labeling was carried out per a publicly available ranking system. The data were distributed into three trust categories, i.e., the low-trust category, mid-trust category, and high-trust category. First, unimodal prediction using each of the three modalities individually was performed using the database; then, using the outputs of the unimodal predictions, a multimodal prediction was later performed. Unimodal prediction was performed by training three independent logistic regression (LR) classifiers, one each for speech, text, and images. The prediction vectors from the individual modalities were then concatenated before being used to train a multimodal decision-making LR classifier. We report that the best performing modality was speech, which achieved a classification accuracy of 92.81%, followed by the images, achieving an accuracy of 77.96%, whereas the best performing model for text-modality achieved a 72.26% accuracy. With the multimodal approach, the highest classification accuracy of 97.53% was obtained when all three modalities were used for trust prediction. Meanwhile, in a bimodal setup, the best performing combination was that combining the speech and image visual modalities by achieving an accuracy of 95.07%, followed by the speech and text combination, showing an accuracy of 94.40%, whereas the text and images visual modal combination resulted in an accuracy of 83.20%. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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Article
Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse Channels
by Olutayo Oyeyemi Oyerinde, Adam Flizikowski and Tomasz Marciniak
Electronics 2021, 10(7), 842; https://doi.org/10.3390/electronics10070842 - 1 Apr 2021
Cited by 3 | Viewed by 1963
Abstract
The channel of the broadband wireless communications system can be modeled as a dynamic sparse channel. Such a channel is difficult to reconstruct by using linear channel estimators that are normally employed for dense channels’ estimation because of their lack of capacity to [...] Read more.
The channel of the broadband wireless communications system can be modeled as a dynamic sparse channel. Such a channel is difficult to reconstruct by using linear channel estimators that are normally employed for dense channels’ estimation because of their lack of capacity to use the inherent channel’s sparsity. This paper focuses on reconstructing this type of time-varying sparse channel by extending a recently proposed dynamic channel estimator. Specifically, variable step size’s mechanism and variable momentum parameter are incorporated into traditional Iterative Hard Thresholding-based channel estimator to develop the proposed Iterative Hard Thresholding with Combined Variable Step Size and Momentum (IHT-wCVSSnM)-based estimator. Computer simulations carried out in the context of a wireless communication system operating in a dynamic sparse channel, show that the proposed IHT-wCVSSnM-based estimator performs better than all the other estimators significantly. However, the computational complexity cost of the proposed estimator is slightly higher than the closely performing channel estimator. Nevertheless, the inherent complexity cost of the proposed estimator could be compromised in a situation where the system’s performance is of higher priority when compared with the computational complexity cost. Full article
(This article belongs to the Special Issue Selected Papers from 14th International Conference on Signal Processing and Communication Systems)
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