Wireless Channel Research Articles

RRI Yogyakarta Brand Communication at the 2022 Nusantara Student Festival Event

Current technological developments have provided significant changes to information media, Information and communication media companies need to always innovate to maintain the company's image and remain the people's choice. The research aims to determine RRI Yogyakarta's brand communication at the 2022 Nusantara Student Festival event. This research uses a qualitative descriptive case study approach to explore and explore in depth. The theory used is brand communication strategy theory with brand visualization (logo) indicators. The research results show that the brand communication strategy implemented by RRI Yogyakarta includes a logo that is disseminated through branding media at the FPN 2022 event location and through Instagram social media, then direct marketing carried out door-to-door and radio broadcasts, social media via Instagram platform, promotions carried out include offers of collaboration and the use of influencers, marketing events through organizing the 2022 Nusantara Student Festival event, as well as sponsorship in the form of service support.

Ground-to-UAV sub-terahertz channel measurement and modeling

Unmanned aerial vehicle (UAV) assisted wireless communications have been expected to play a vital role in the next generation of wireless networks. UAVs can serve as either repeaters or data collectors within the communication link, thereby potentially augmenting the efficacy of communication systems. Despite their promise, the channel analysis and modeling specific to terahertz (THz) wireless channels leveraging UAVs remain under-explored. This work delves into a ground-to-UAV channel at 140 GHz, with a specific focus on the influence of UAV hovering behavior on channel performance. Employing experimental measurements through an unmodulated channel setup and a geometry-based stochastic model (GBSM) that integrates three-dimensional positional coordinates and beamwidth, this work evaluates the impact of UAV dynamic movements and antenna orientation on channel performance. Our findings highlight the minimal impact of UAV orientation adjustments on channel performance and underscore the diminishing necessity for precise alignment between UAVs and ground stations as beamwidth increases.

Discrete mechanical model for nonlinear dynamical analysis of planar guyed towers considering the unilateral contact of cables

Towers are widely used for power line transmission, wind power plants, TV and radio broadcasting, and telecommunications. To enhance their stability, cables are often employed to anchor these towers to the ground. In this study, we investigate the nonlinear static and dynamic responses of a planar guyed tower in which the unilateral constraints on the cables are considered. A representative discrete mechanical model with two degrees of freedom is developed to simulate the central mast of the tower, and the cables are modeled as unilateral springs with linear stiffness. The nonlinear equilibrium equations are derived using an energy approach that incorporates the dissipative forces, total potential, and kinetic energies into the Euler-Lagrange equations. Unilateral cable contact is directly included in the nonlinear equilibrium equation for the guyed tower, allowing for numerical analysis without the need to evaluate the contact point at each time or load step. Several numerical strategies are employed to obtain nonlinear static equilibrium paths, bifurcation diagrams, phase portraits, and Poincaré sections. Our analyses provide novel results for the influence of unilateral cable contact in nonlinear static and dynamic analysis, evaluating the effects of unilateral contact and prestressing on the results. A parametric analysis reveals that cable contact affects nonlinear oscillations, bifurcation, and stability. Our numerical results indicate that unilateral cable contact introduces less structural stiffness compared to bilateral contact, thereby significantly affecting the static and dynamic stability of a planar guyed tower. This is evidenced by a decrease in the static limit load and alterations in the bifurcation diagrams, where unilateral contact destroys the trivial solutions, leading to periodic and quasi-periodic solutions at low levels of vertical load.

Closed-form energy-based signal detection analysis in presence of a Lomax fading channel in full hyper-Rayleigh regime

The presented research examines the energy-based spectrum sensing problem of a signal transmitted over a wireless communication channel with severe fading. To account for the most challenging propagation conditions, a recently developed Lomax wireless channel model was utilized, which exhibits hyper-Rayleigh characteristics over the entire range of possible parameter values. For the channel model under consideration, the existence of the specific hyper-Rayleigh regimes (i.e., weak, strong, and full) are identified asymptotically and studied numerically for a finite signal-to-noise ratio. For the most severe fading conditions, the system’s performance was assessed in terms of the average probability of detection, receiver operating characteristics, and area under the curve. These metrics were derived in closed-form for the cases of Maximum Ratio Combining at the receiver and without diversity reception. The obtained expressions were analyzed via numerical and statistical simulation as functions of system and channel parameters, including the sensing base, average signal-to-noise ratio, and scale parameter for the signal-to-noise probability distribution. The results from numerical simulations were compared with existing regulations specified in the 5G standard for energy-based detection in medium access procedures.

Community Radio Content in Print Facebook Posts: Limitations and Opportunities for Indigenous Languages

With the advent of social media, traditional analogue radio has converged to audio-visual with print formats. Using the case of community radio in Zimbabwe, this article explores how radio broadcasters have taken advantage of media convergence to disseminate text as implant on radio. A qualitative content analysis of community radio platforms on Facebook reveals that some multilingual community radio stations still maintain their local languages in written text as captions or print, although there is a tendency towards English and major indigenous language dominance. Using language revitalisation theory, we argue that merging written text with radio on social media should always maintain the distinctness of radio and text as implant that reflect the local languages of community radio stations to revitalise or strengthen indigenous languages. We find the affordances of digital connection through Facebook useful to revitalise languages which are no longer used in the everyday communication of a digital audience.

A Physical-Layer Security Cooperative Framework for Mitigating Interference and Eavesdropping Attacks in Internet of Things Environments.

Intentional electromagnetic interference attacks (e.g., jamming) against wireless connected devices such as the Internet of Things (IoT) remain a serious challenge, especially as such attacks evolve in complexity. Similarly, eavesdropping on wireless communication channels persists as an inherent vulnerability that is often exploited by adversaries. This article investigates a novel approach to enhancing information security for IoT systems via collaborative strategies that can effectively mitigate attacks targeting availability via interference and confidentiality via eavesdropping. We examine the proposed approach for two use cases. First, we consider an IoT device that experiences an interference attack, causing wireless channel outages and hindering access to transmitted IoT data. A physical-layer-based security (PLS) transmission strategy is proposed in this article to maintain target levels of information availability for devices targeted by adversarial interference. In the proposed strategy, select IoT devices leverage a cooperative transmission approach to mitigate the IoT signal outages under active interference attacks. Second, we consider the case of information confidentiality for IoT devices as they communicate over wireless channels with possible eavesdroppers. In this case, we propose a collaborative transmission strategy where IoT devices create a signal outage for the eavesdropper, preventing it from decoding the signal of the targeted devices. The analytical and numerical results of this article illustrate the effectiveness of the proposed transmission strategy in achieving desired IoT security levels with respect to availability and confidentiality for both use cases.

MIMO Signal Detection Based on IM-LSTMNet Model

Signal detection is crucial in multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, yet classical detection methods often struggle with nonlinear issues in wireless channels. To handle this challenge, we propose a novel signal detection method for MIMO-OFDM system based on the fractional Fourier transform (FrFT), leveraging the robust time series processing capabilities of long short-term memory (LSTM) networks. Our innovative approach, termed IM-LSTMNet, integrates LSTM with convolutional neural networks (CNNs) and incorporates a Squeeze and Excitation Network to emphasize critical information, enhancing neural network performance. The proposed IM-LSTMNet is applied to the FrFT-based MIMO-OFDM system to improve signal detection performance. We compare the detection results of IM-LSTMNet with zero forcing (ZF), minimum mean square error (MMSE), simple LSTM neural network, and CNN–LSTM network by evaluating the bit error rate. Experimental results demonstrate that IM-LSTMNet outperforms ZF, MMSE, LSTM, and other methods, significantly enhancing system signal detection performance. This work offers a promising advancement in MIMO-OFDM signal detection, presenting a deep learning-based solution that effectively improves the system signal detection performance.

Studying the influence of correction codes on coherent reception of M-PSK signals in the presence of noise and harmonic interference

Objectives. Signals with multiple phase shift keying (M-PSK) exhibiting good spectral and energy characteristics are successfully used in many information transmission systems. These include satellite communication systems, GPS, GLONASS, DVB/DVB-S2, and a set of IEEE 802.11 wireless communication standards. In radio communication channels, the useful signal is affected by various interferences in addition to noise. One of these is harmonic interference. As a result, high intensity harmonic interference practically destroys the reception of M-PSK signals. One of the important requirements for the quality of data transmission is the system error tolerance. There are different ways of improving the quality of information transmission. One of these is the use of corrective encoding technology. The aim of the paper is to assess the noise immunity of a coherent demodulator of M-PSK signals using Hamming codes (7,4) and (15,11), and convolutional encoding with Viterbi decoding algorithm (7,5) when receiving M-PSK signals under noise and harmonic interference in the communication channel.Methods. The methods of statistical radio engineering, optimal signal reception theory and computer simulation modeling were used.Results. Experimental dependencies of the bit error rate on the signal-to-noise ratio and on the intensity of harmonic interference of coherent reception of M-PSK signals in a channel with noise and harmonic interference were obtained using computer simulation modeling. This was done without using correction codes and with Hamming code (7.4) and (15.11) and convolutional encoding with Viterbi decoding algorithm (7,5).Conclusions. It is shown that the application of the correction codes effectively corrects errors in the presence of noise and harmonic interference with lower intensity. The correction is ineffective in the presence of high intensity interference. These results can provide important guidance in designing the reliable and energy efficient system.

Adaptive Frame Structure Design for Sensing-Assisted Downlink Communication in the Vehicle-to-Infrastructure Scenario.

Vehicle-to-everything (V2X) is considered a key factor in driving the future development of intelligent transport, which requires high-quality communication and fast sensing of vehicle information in high-speed mobile scenarios. However, high-speed mobility makes the wireless channel change rapidly, which requires frequent channel estimation and channel feedback between a vehicle and the roadside unit (RSU), resulting in an increase in communication overhead. At the same time, the high maneuverability of vehicles leads to frequent switching and misalignment of communication beams, so the RSU must have better beam prediction and tracking capabilities. To address this problem, this paper proposes an adaptive frame structure design scheme for sensing-assisted downlink (DL) communication. The basic idea of the scheme involves analyzing the communication model during the vehicle's movement. This analysis aims to establish a theoretical relationship between the Symbol Error Rate (SER) and the following two key factors: the vehicle's starting position and the distance it travels across. Subsequently, the scheme leverages the vehicle's position data, as detected by the RSU, to calculate the real-time SER for DL communication. The SER threshold is set based on the requirements of DL communication. If the real-time SER is below this threshold, channel estimation becomes unnecessary. This decreases the frequency of channel estimation and frees up time and frequency resources that would otherwise be occupied by channel estimation processes within the frame structure. The design of an adaptive frame structure, as detailed in the above scheme, is presented. Furthermore, the performance of the proposed method is analyzed and compared with that of the traditional communication protocol frame structure and the beam prediction-based frame structure. The simulation results indicate that the communication throughput of the proposed method can be improved by up to 6% compared with the traditional communication protocol frame structure while maintaining SER performance.

Floating meta-bubbles: aerial gateway and routing on the sky

Reflecting intelligent surface technology (RIS) is regarded as a key enabler of the sixth-generation (6G) communication system. It provides the ability to reshape radio channels through passively reflecting beams in a reconstructive manner. Furthermore, aerial RIS (ARIS) introduces more flexibility in providing line-of-sight (LOS) links. Unfortunately, most of the related research efforts supposed the system as a planar RIS mounted on a satellite, unmanned aerial vehicle (UAV), or balloon despite reported limitations of planar RISs. The essential problem in designing any planar RIS network resides in mutual orientation and alignment difficulty, especially under random fluctuation of position/orientation due to wind conditions or UAV wobbling in the hover state. So, this paper highlights spherical RIS (bubble) as the optimal choice for aerial beam routing where the orientation/rotation can be completely relaxed. It outperforms planar RIS in terms of RIS networking flexibility, dead zone relaxation, and coverage extension. Consequently, due to the added degrees of freedom, many new deployment scenarios/use cases are recommended such as introducing meta-bubbles as intermediate gateways between satellite and ground nodes and extending network infrastructure installation down to the client level to enhance its visibility and throughput. Simulations demonstrate the superiority of meta-bubbles in minimizing channel loss over successive multi-hop routing.

A multidisciplinary analysis of over 53,000 fascioliasis patients along the 1995–2019 countrywide spread in Vietnam defines a new epidemiological baseline for One Health approaches

Fascioliasis, only foodborne trematodiasis of worldwide distribution, is caused by Fasciola hepatica and F. gigantica, liver flukes transmitted by freshwater snails. Southern and southeastern Asia is an emerging hot spot of F. gigantica, despite its hitherto less involvement in human infection. In Vietnam, increasing cases have been reported since 1995, whereas only sixteen throughout 1800–1994. A database was created to include epidemiological data of fascioliasis patients from the 63 Vietnam provinces throughout 1995–2019. Case profiles were based on serology, symptoms, eosinophilia, imaging techniques, stool egg finding, and post-specific-treatment recovery. Radio broadcasting about symptoms and costless diagnosis/treatment led patients to hospitals after symptom onset. Yearly case numbers were modelled and spatio-temporally analyzed. Missing data and confounders were assessed. The countrywide spread has no precedent. It started in the central coast, including 53,109 patients, mostly adults and females. Seasonality, linked to vegetable consumption, peaks in June, although the intensity of this peak differs according to relief/climatic zones. Incidence data and logistic regression curves are obtained for the first time in human fascioliasis. Fasciolid hybrids accompanying the spreading F. gigantica flukes, and climate change assessed by risk index correlations, are both ruled out as outbreak causes. Human-guided movements of livestock from an original area prove to be the way used by fasciolids and lymnaeid vectors to expand geographically. Radix viridis, a highly efficient transmitting and colonizing vector, played a decisive role in the spread. The use of irrigated crop fields, widely inhabited by R. viridis, for livestock grazing facilitated the transmission and spread of the disease. General physician awareness and diagnostic capacity improvement proved the successful impact of such knowledge transfer in facilitating and increasing patient infection detection. Information, education and communication to the public by radio broadcasting demonstrated to be very helpful. Fasciola gigantica is able to cause epidemic and endemic situations similar to F. hepatica. The magnitude of the human outbreak in Vietnam is a health wake-up call for southern and southeastern countries of Asia which present the highest human population densities with increasing food demands, uncontrolled livestock inter-country exchange, foreign import practices, and monsoon's increasing climate change impact.

A Low-Power Impedance-to-Frequency Converter for Frequency-Multiplexed Wearable Sensors.

We propose a low-power impedance-to-frequency (I-to-F) converter for wearable transducers that change both its resistance and capacitance in response to mechanical deformation or changes in ambient pressure. At the core of the proposed I-to-F converter is a fixed-point circuit comprising of a voltage-controlled relaxation oscillator and a proportional-to-temperature (PTAT) current reference that locks the oscillation frequency according to the impedance of the transducer. Using both analytical and measurement results we show that the operation of the proposed I-to-F converter is well matched to a specific class of sponge mechanical transducer where the system can achieve higher sensitivity when compared to a simple resistance measurement techniques. Furthermore, the oscillation frequency of the converter can be programmed to ensure that multiple transducer and I-to-F converters can communicate simultaneously over a shared channel (physical wire or virtual wireless channel) using frequency-division multiplexing. Measured results from proof-of-concept prototypes show an impedance sensitivity of 19.66 Hz/ Ω at 1.1 kΩ load impedance magnitude and a current consumption of [Formula: see text]. As a demonstration we show the application of the I-to-F converter for human gesture recognition and for radial pulse sensing.

On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels

On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels

Resource allocation for device-to-device communications underlaying uplink cellular networks

Underlying cellular networks, device-to-device (D2D) communications are a practical network technology that can increase power efficiency and spectrum usage for close-proximity wireless services and applications. However, D2D link interference, when sharing resources with cellular users (CUs), poses a major challenge in such distribution situations. In this research, we primarily utilize wireless channel data that exhibits slowly shifting large-scale fading to conduct spectrum sharing and power allocation. The overall ergodic capacity of all cellular user equipment (CUE) links is initially considered as the optimization target in order to maximize the overall throughput of CUE links while ensuring the reliability of each D2D link. Then, the expansion of the minimum ergodic capacity is measured to ensure a more consistent capacity performance across all CUE links. We utilized algorithms that are resilient to channel fluctuations and produce optimal resource allocation. We use MATLAB, and the computer simulation validates its intended performance.

Intelligent non-invasive elderly fall monitoring by designing software defined radio frequency sensing system

The global increase in life expectancy poses challenges related to the safety and well-being of the elderly population, especially in relation to falls. While falls can lead to significant cognitive impairments, timely intervention can mitigate their adverse effects. In this context, the need for non-invasive, efficient monitoring systems becomes paramount. Although wearable sensors have gained traction for monitoring health activities, they may cause discomfort during prolonged use, especially for the elderly. To address this issue, we present an intelligent, non-invasive Software-Defined Radio Frequency (SDRF) sensing system, tailored red for monitoring elderly people's falls during routine activities. Harnessing the power of deep learning and machine learning, our system processes the Wireless Channel State Information (WCSI) generated during regular and fall activities. By employing sophisticated signal processing techniques, the system captures unique patterns that distinguish falls from normal activities. In addition, we use statistical features to streamline data processing, thereby optimizing the computational efficiency of the system. Our experiments, conducted for a typical home environment while using treadmill, demonstrate the robustness of the system. The results show high classification accuracies of 92.5%, 95.1%, and 99.8% for three Artificial Intelligence (AI) algorithms. Notably, the SDRF-based approach offers flexibility, cost-effectiveness, and adaptability through software modifications, circumventing the need for hardware overhaul. This research attempts to bridge the gap in RF-based sensing for elderly fall monitoring, providing a solution that combines the benefits of non-invasiveness with the precision of deep learning and machine learning.

Japanese Military Government Policy on Radio Broadcasting in Java

In World War II, radio was one of the effective communication media that could be used to spread news and propaganda. The Japanese military government in Java made efforts to control or censor radios owned by the public. Control and censorship efforts to prevent the public from listening to radio broadcast by the Allies. On the other hand, radio was also useful for Japan to spread propaganda in society. The purpose of this study is to examine the policy of the Japanese military government in controlling and utilizing radio as a propaganda media in Java during wartime. This study is a historical research, thus the method used in this study is the historical method. The primary data used were Asia Raya newspaper, Djawa Baroe magazine, and Kan Pō (the government news) published by the Japanese military government in Java in 1942-1945. The results of this study show that the Japanese military government paid great attention to radio broadcasting and was strict in controlling it, radio broadcasts from enemy countries (Allies) were strictly forbidden to be listened to by the public, even the Japanese military government will impose severe punishment on the people if anyone violates. However, the Japanese military government also employed radio as a media for disseminating propaganda such as radio speeches from Japanese military officials, government programs, news, and so on.

TWO-LEVEL CONCEPT FOR SIMULATING UNIFORM INTERFERENCE-RESISTANT DIGITAL DATA TRANSMISSION

The article formalizes, creates and provides for consideration the concept of a single secure interference-resistant data transmission channel. In modern cybersecurity theory and practice, there is the NIST Cybersecurity Framework, which is a set of recommendations for reducing risks for organizations. In order for high-level data to be secure, there are requirements for the SIA triad, namely confidentiality, integrity and availability of information. Therefore, in the future, the expediency of the work and its result will directly depend on the satisfaction of the SIA conditions. As you know, high-level data: such as e-mail, visual data in the GUI of various applications, etc., are transmitted over low-level communication channels: such as cables, wireless radio communication channels, and others. At each of the levels for safe transmission of information, there are specific pests. At high levels, the main threat to information is man and the human factor. The lower the level of information transmission becomes, the more nature, natural obstacles and random short phenomena begin to influence. In order for the user to be able to use various devices without a threat to the confidentiality, integrity and availability of information, it is necessary to actively and continuously develop, improve and improve the existing methods of data protection, restoration, transmission and storage. Each aspect in this struggle for security is both an advantage and a disadvantage: excessive security is not appropriate for mass traffic, complexity does not always provide adequate security, and so on. Therefore, the optimality and expediency of the methods used becomes an important factor. For these reasons, the paper proposes a relatively simple, but no less effective approach to maintaining SIA requirements.

Wireless communication channel modeling based on ML

Nowadays, wireless communication plays an important role in various fields of our lives, and in order to ensure good communication performance, reliable channel models are important. In this paper, we present a comprehensive survey of Machine Learning (ML) based channel modeling methods to help with the estimation and prediction accuracy on wireless channel modeling. To begin with, we start with a review of the traditional methods of wireless communication channel modeling, basically empirical method and deterministic method. Then, we introduce several ML methods to address limitations of traditional ways will be used for channel modeling, such as Support Vector Machine (SVM), Random Forests, autoencoder, Deep Learning, etc. Lastly, we demonstrate the application of ML methods including deep learning, SVM, and random forests on wireless channel modeling. Through learning the underlying channel distribution, Deep Learning methods have already demonstrated remarkable performance in channel modeling for different scenarios in some previous learning. Also, by training with suitable kernels and conducting sufficient training iterations, optimal hyperplanes can be identified, Support Vector Machines (SVM) can then be utilized to predict channel characteristics based on input features. Random Forests can identify the most relevant features influencing the channel and optimize system design by handling complex and high-dimensional data through iterative feature selection and splitting criteria. These methods achieve competitive accuracy with respect to traditional methods, however, there are still challenges and issues to be addressed in the application of machine learning methods for communication channel modeling.

Wireless channel characterizations in UMi scenarios via ray-tracing at 28 GHz: A perspective of asymmetric beams

As a novel communication pattern, the asymmetric beams adopt a strategy of different beamwidths for a specific link to reduce the beam alignment overheads and energy consumption. A good and thorough knowledge of the radio propagation characteristics is pivotal for further network deployment and optimization of wireless mobile communication systems. In this paper, a multiple-bounce beam channel model is proposed based on the ray-tracing considering the beamforming effects. Besides, a space–time–frequency (STF) power density profile reconstruction method is proposed. Relevant simulations are conducted to emulate an urban micro-cellular (UMi) street scenario at 28 GHz under the case of perfect beam alignment. On this basis, the beam-dependent small-scale fading properties (including STF power density profiles, delay spread, Doppler frequency shift spread, and angular spread) together with the large-scale fading characteristics (involving path loss and shadow fading) are fully investigated. Results reveal that the downlink of asymmetric beams presents more dispersions in contrast to the uplink in the STF domains. Furthermore, the shadow fading variances are asymmetric over different transceivers array element numbers.

Adapting LoRa Ground Stations for Low-latency Imaging and Inference from LoRa-enabled CubeSats

Recent years have seen the rapid deployment of low-cost CubeSats in low-Earth orbit, many of which experience significant latency (several hours) from the time information is gathered to the time it is communicated to the ground. This is primarily due to the limited availability of ground infrastructure that is bulky to deploy and expensive to rent. This article explores the opportunity in leveraging the extensive terrestrial LoRa infrastructure as a solution. However, the limited bandwidth and large amount of Doppler on CubeSats precludes these LoRa links to communicate rich satellite Earth images—instead, the CubeSats can at best send short messages. This article details our experience in designing LoRa-based satellite ground infrastructure that requires software-only modifications to receive packets from LoRa-enabled CubeSats recently launched by our team. We present Vista, a communication system that adapts encoding onboard the CubeSat and decoding configuration on commercial LoRa ground stations to allow images to be communicated. We perform a detailed evaluation of Vista by leveraging wireless channel measurements from a recent CubeSat (2021), and show that Vista can achieve 55.55% lower latency in retrieving data with 12.02 dB improvement in packet retrieval in the presence of terrestrial interference. We then evaluate Vista on a case study on land-use classification over images transmitted over the CubeSat link to further demonstrate a 4.56 dB improvement in image PSNR and 1.38× increase in classification accuracy over baseline approaches.