Transmission Scenarios Research Articles

Linear Encryption Against Eavesdropping on Remote State Estimation

This article considers the problem of eavesdropping on remote state estimation. Linear encryption strategies are used to protect the transmitted data. Two types of data transmission are considered: raw measurements generated by traditional sensors as well as innovations generated by smart sensors. For these two transmission scenarios, the encryption coefficients are obtained by formulating different optimization problems, with the target of maximizing the eavesdropper's estimation error covariance. For stable systems, the designed encryption strategies can effectively impair the eavesdropper's estimation performance. For unstable systems, the encryption can be designed to make the eavesdropper's estimation error covariance divergent. The encryption performance is evaluated through numerical simulations on both stable and unstable systems.

Rate-Splitting Multiple Access: Fundamentals, Survey, and Future Research Trends

Rate-splitting multiple access (RSMA) has emerged as a novel, general, and powerful framework for the design and optimization of non-orthogonal transmission, multiple access (MA), and interference management strategies for future wireless networks. Through information and communication theoretic analysis, RSMA has been shown to be optimal (from a Degrees-of-Freedom region perspective) in several transmission scenarios. Compared to the conventional MA strategies used in 5G, RSMA enables spectral efficiency (SE), energy efficiency (EE), coverage, user fairness, reliability, and quality of service (QoS) enhancements for a wide range of network loads (including both underloaded and overloaded regimes) and user channel conditions. Furthermore, it enjoys a higher robustness against imperfect channel state information at the transmitter (CSIT) and entails lower feedback overhead and complexity. Despite its great potential to fundamentally change the physical (PHY) layer and media access control (MAC) layer of wireless communication networks, RSMA is still confronted with many challenges on the road towards standardization. In this paper, we present the first comprehensive overview on RSMA by providing a survey of the pertinent state-of-the-art research, detailing its architecture, taxonomy, and various appealing applications, as well as comparing with existing MA schemes in terms of their overall frameworks, performance, and complexities. An in-depth discussion of future RSMA research challenges is also provided to inspire future research on RSMA-aided wireless communication for beyond 5G systems.

QUIC vs TCP: A Performance Evaluation over LTE with NS-3

In the vast majority of mobile applications, the Transmission Control Protocol (TCP) is still leveraged at the transport layer of the Internet’s protocol stack. But, in many cases, the performance of TCP over mobile networks has been proven sub-optimal in practice, thus causing substantial bottlenecks. Quick UDP Internet Connections (QUIC) is a new protocol, currently being standardized by the Internet Engineering Task Force (IETF), that aims at solving some of the inherent problems of TCP. The purpose of this paper is to provide a comprehensive overview of QUIC and compare the performance of QUIC and TCP in wireless networks. To compare QUIC with TCP under various transmission scenarios over LTE networks, the ns-3 network simulator has been employed. The simulations performed showed that 1) under good or average transmission conditions, QUIC is characterized by a better steady state throughput at the same time achieving quite lower file download times; and 2) under poor transmission conditions, the two protocols exhibit a similar performance.

Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures (Cities) - China, 2022.

IntroductionMinimizing the importation and exportation risks of coronavirus disease 2019 (COVID-19) is a primary concern for sustaining the “Dynamic COVID-zero” strategy in China. Risk estimation is essential for cities to conduct before relaxing border control measures.MethodsInformed by the daily number of passengers traveling between 367 prefectures (cities) in China, this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks.ResultsUnder the transmission scenario (R0=5.49), this study estimated the cumulative case incidence of Changchun City, Jilin Province as 3,233 (95% confidence interval: 1,480, 4,986) before a lockdown on March 14, 2022, which is close to the 3,168 cases reported in real life by March 16, 2022. In a total of 367 prefectures (cities), 127 (35%) had high exportation risks according to the simulation and could transmit the disease to 50% of all other regions within a period from 17 to 94 days. The average time until a new infection arrives in a location in 1 of the 367 prefectures (cities) ranged from 26 to 101 days.ConclusionsEstimating COVID-19 importation and exportation risks is necessary for preparedness, prevention, and control measures of COVID-19 — especially when new variants emerge.

Rapid antigen test for COVID-19: A useful weapon in the arsenal of public health

Rapid antigen test has a very important value as one of tools to address the Covid pandemic. Though this test is not as accurate as polymerase chain reaction (PCR) testing. As viral antigen appears before antibody formation in infected person. It is a specific marker of virus. Therefore, for detection of this highly infectious disease at an early stage, viral antigen testing can be a useful strategy in scenario of community transmission to prevent further spread. In India an advisory was issued by ICMR (on 14th June 2020) regarding usage of RAT for quick detection of COVID-19 positive patients. During second wave, Rapid antigen testing was advised only in symptomatic individuals and immediate contacts of laboratory confirmed positive cases. Though no test is perfect when it comes to the attributes of accuracy, accessibility, affordability, and timeliness of results. However, Rapid antigen test can be used as a useful test in public health that can benefit the larger population in breaking the chain of transmission if used wisely in different settings and according to the timeline of symptoms.

Measurement and Simulation-Based Exposure Assessment at a Far-Field for a Multitechnology Cellular Site up to 5G NR

5G is expected to be the dominant technology for mobile networks in the coming years, but there is concern about the increase in the total electromagnetic field radiation levels due to the deployment of the 5G technology. This paper presents an exposure assessment of electromagnetic field radiation on humans from single base station of a mobile network serving in dense, urban, suburban, and rural area scenarios for single-site transmission with multi-technology, including 2G, 3G, 4G, IoT, and 5G which have recently been deployed. This assessment is performed using simulation to predict the received signal levels and to calculate the related power densities for a typical single site under operating field configurations and settings for each technology. Field measurements were performed using a drive test tool to validate and calibrate the simulation results. The results show the total exposure ratio was very low compared to the international standard exposure limits, and the results show the contribution from each technology for these spesfic sites used in this study.

Fronthaul Optical Links Using Sub-Nyquist Sampling Rate ADC for B5G/6G Sub-THz Ma-MIMO Beamforming

This paper details fronthaul optical links using sub-Nyquist sampling rate analog-to-digital converters (ADCs) for Beyond fifth generation (B5G) and 6G sub-THz massive multiple-input multiple-output (Ma-MIMO) beamforming. Unlike Common Public Radio Interface (CPRI) using high speed ADCs in current fronthaul link, the proposed scheme involves ADCs operating at sub-Nyquist sampling rate for each antenna element. Based on pre-allocated relative time delays, pre-processed orthogonal frequency-division multiplexing (OFDM) signals sent from a baseband unit (BBU) can be deaggregated to different Ma-MIMO OFDM signals by sub-Nyquist sampling rate ADCs. In experiments, we assume that each remote radio unit (RRU) is equipped with 32/64 antenna elements and 32/64 ADCs operating at 1/32 and 1/64 of the Nyquist sampling rate. Furthermore, the received Ma-MIMO OFDM signal is then up-converted to 100-GHz for wireless transmission and defined as Ma-MIMO RF OFDM signal. We simulate the 32/64 antenna elements transmission scenario by individually transmit and demodulate each Ma-MIMO RF OFDM signal with 32/64 times of point-to-point antenna transmission. The error vector magnitude (EVM) and signal-to-noise ratio (SNR) of each received Ma-MIMO RF OFDM signal are less than 8% and 26 dB, respectively. And the total received 64 Ma-MIMO RF OFDM signals will require line rate as high as 393.6374 Gb/s according to CPRI option-7. Notably, the proposed scheme reduces the requirement of sampling rate and enables all the Ma-MIMO OFDM signals at baseband without the insertion of guard band. Thus, the proposed scheme can reduce the complexity of signal deaggregation and power consumption in the demodulation process, leading to an improvement in cost efficiency.

Latency versus Reliability in LEO Mega-Constellations: Terrestrial, Aerial, or Space Relay

Large low earth orbit (LEO) mega-constellation systems have been designed and deployed as a global backbone to provide ubiquitous connectivity across the world. However, due to the high traffic load/congestion arisen from the required numerous information relay and forwarding, it is a challenge for LEO mega-constellation systems to set up long-distance connections between two remote terrestrial users for real-time communications, which requires strict low latency. Other than inter-LEO satellite links (ILSL), introducing third-party relays, such as terrestrial, aerial, and satellite relays, is an alternative way to improve the latency performance for wide-area deliveries of real-time traffic. However, the reliability of the transmitted signal will unavoidably degrade, because of the increased path-loss attributed to long-distance relaying transmissions. Then, to reveal the principle that the third-party relays affect the latency and reliability, in this work, an LEO satellite-terrestrial communication scenario is considered, in which two remote terrestrial users communicate with each other via an LEO mega-constellation system. Analysis models are built up to investigate the end-to-end time delay and outage performance while considering different ILSL, terrestrial, aerial, and satellite relay assisted transmission scenarios. More specifically, by applying geometrical probability theory, exact/approximated closed-form analytical expressions have been derived for average time delay

Simulation modeling of multi-stream data transmission in the AnyLogic environment

The paper considers a simulation model of multi-path data transmission built in the AnyLogic environment. The use of a multi-path data transmission scenario is extremely relevant today since user devices have more than one communication interface, and the amount of traffic is growing. We analyzed the QoS characteristics for a scenario with two sub-paths. It has been shown that a policy of allocation data into subpaths according to the amount of free resources can lead to the problem of incorrect packet order on the receiving side. In addition, it is obvious that the AnyLogic environment can be used to model telecommunication systems at a high level of abstraction.

Projecting the Combined Health Care Burden of Seasonal Influenza and COVID-19 in the 2020-2021 Season.

Background. In mid-2020, there was significant concern that the overlapping 2020–2021 influenza season and COVID-19 pandemic would overwhelm already stressed health care systems in the Northern Hemisphere, particularly if influenza immunization rates were low. Methods. Using a mathematical susceptible-exposed-infected-recovered (SEIR) compartmental model incorporating the age-specific viral transmission rates and disease severity of Austin, Texas, a large metropolitan region, we projected the incidence and health care burden for both COVID-19 and influenza across observed levels of SARS-CoV-2 transmission and influenza immunization rates for the 2020–2021 season. We then retrospectively compared scenario projections made in August 2020 with observed trends through June 2021. Results. Across all scenarios, we projected that the COVID-19 burden would dwarf that of influenza. In all but our lowest transmission scenarios, intensive care units were overwhelmed by COVID-19 patients, with the levels of influenza immunization having little impact on health care capacity needs. Consistent with our projections, sustained nonpharmaceutical interventions (NPIs) in Austin prevented COVID-19 from overwhelming health care systems and almost completely suppressed influenza during the 2020–2021 respiratory virus season. Limitations. The model assumed no cross-immunity between SARS-CoV-2 and influenza, which might reduce the burden or slow the transmission of 1 or both viruses. Conclusion. Before the widespread rollout of the SARS-CoV-2 vaccine, COVID-19 was projected to cause an order of magnitude more hospitalizations than seasonal influenza because of its higher transmissibility and severity. Consistent with predictions assuming strong NPIs, COVID-19 strained but did not overwhelm local health care systems in Austin, while the influenza burden was negligible. Implications. Nonspecific NPI efforts can dramatically reduce seasonal influenza burden and preserve health care capacity during respiratory virus season.HighlightsAs the COVID-19 pandemic threatened lives worldwide, the Northern Hemisphere braced for a potential “twindemic” of seasonal influenza and COVID-19.Using a validated mathematical model of influenza and SARS-CoV-2 co-circulation in a large US city, we projected the impact of COVID-19–driven nonpharmaceutical interventions combined with influenza vaccination on health care capacity during the 2020–2021 respiratory virus season.We describe analyses conducted during summer 2020 to help US cities prepare for the 2020–2021 influenza season and provide a retrospective evaluation of the initial projections.

A Robust Reversible Data Hiding Framework for Video Steganography Applications

Reversible Data Hiding (RDH) is a special form of data hiding approach for data integrity and confidentiality protection where the secret image bits (SI) are embedded into Cover Media (CM) by altering its intrinsic pixel attributes. However, in RDH the CM along with the secret message is recovered at the end of computing phase. However, despite of its potential use-cases for enhancing the embedding performance, when it comes to security for various network standards, the traditional RDH mechanisms cannot fully comply with the standards for different set of attacks during the bit-stream transmission scenarios. Therefore, the proposed study contributes towards a computational framework of a robust RDH framework for Video Steganography (VS) which is modeled and simulated under various attack effects and the observation outcome are produced in before and after attack situations to justify the improvement over Embedding Capacity (EC) and Peak Signal-to-Noise Ratio (PSNR) performance for both CM and secret message unlike traditional difference expansion-based methods (DE). The outcome of the study shows that the formulated RDH method not only achieves better reversibility at lower cost of computing but also ensures effective PSNR and imperceptibility outcome for both CM and secret image.

Update of the Phlebotominae Fauna with New Records for Argentina and Observations on Leishmaniasis Transmission Scenarios at a Regional Scale

Phlebotominae are small insects distributed in the Americas from Canada to Argentina and Uruguay, counting with more than 500 neotropical species. Some of them have a vectorial role in the transmission of Leishmania Ross, the causative agent of leishmaniases, a group of worldwide distributed diseases with different clinical manifestations and transmission cycles. Our aim was to update the Phlebotominae fauna of Argentina and to make observations on the American Cutaneous (ACL) and Visceral Leishmaniasis (AVL) transmission scenarios, according to the distribution of proven or suspected Leishmania vector species and recent changes in land use. Primary data (entomological captures) and secondary data (review of 65 scientific publications with Phlebotominae records) were used. With 9 new records, 46 Phlebotominae species are now recorded through the area comprising 14 political jurisdictions and 6 phytogeographic provinces. Distribution maps were constructed for the 5 proven or incriminated Leishmania vector species, and the evidence supporting the vectorial incrimination of these species is discussed. Three main ACL transmission scenarios are described in the phytogeographic provinces of the Yungas, Chaco, and Paranaense, associated with deforestation processes, while the transmission scenarios of AVL are urban outbreaks and scattered cases in rural areas. We update the available knowledge on the Phlebotominae fauna present in Argentina, emphasizing its epidemiological relevance in the current context of the increasing frequency of ACL outbreaks and geographic spread of AVL.

Differential Transmission Schemes for Generalized Spatial Modulation

Differential modulation schemes are very relevant in receivers having power and processing limitations, as these schemes dispense with the need for knowledge of channel coefficients for symbol detection. Spatial modulation (SM) is a scheme used in multi-antenna transmission scenarios where the data is transmitted in the amplitude, phase and spatial domains through selected antennas. In the coherent domain, generalized SM (GSM) employs multiple antennas in combination during every time slot to enhance the spectral efficiency (SE). In this paper, we propose two differential schemes which activate two or more antennas at a time to transmit the modulated symbol. These schemes achieve higher SE using a lesser number of antennas and lower order modulation schemes instead of the higher number of antennas required for conventional SM schemes based on differential modulation. Simulation studies reveal that the proposed schemes have better bit error rate performance than traditional differential SM schemes. We also derive the analytical union bound for the proposed schemes and is satisfied from medium to high signal-to-noise ratio (SNR) ranges.

Modeling and Performance Analysis of OAM-NFC Systems

Due to its low energy consumption and simplicity, near field communication (NFC) has been extensively used in various short-range transmission scenarios, for example, proximity payment and NFC entrance guard. However, the low data rate of NFC limits its application in high rate demanded scenarios, such as high-resolution fingerprint identification and streaming media transmission as well as the future promising high rate indoor communications among pads, phones, and laptops. In this paper, we model and analyze the performance of the orbital angular momentum based NFC (OAM-NFC) system, which can significantly increase the capacity of NFC. We first give the OAM system model. With coils circularly equipped at the transmitter and receiver, OAM-NFC signals can be transmitted, received, and detected. Then, we develop the OAM-NFC generation and detection schemes for NFC multiplexing transmission. We also analyze the OAM-NFC channel capacity and compare it with those of single-input-single-output (SISO) as well as multi-input-multi-output (MIMO) NFC. Simulation results validate the feasibility and capacity enhancement of our proposed OAM-NFC system. How different variables, such as the transceiver misalignment, the numbers of transceiver coils, and transceiver distance, impact the OAM-NFC capacity are also analyzed.

A comprehensive county level model to identify factors affecting hospital capacity and predict future hospital demand

The sustained COVID-19 case numbers and the associated hospitalizations have placed a substantial burden on health care ecosystem comprising of hospitals, clinics, doctors and nurses. However, as of today, only a small number of studies have examined detailed hospitalization data from a planning perspective. The current study develops a comprehensive framework for understanding the critical factors associated with county level hospitalization and ICU usage rates across the US employing a host of independent variables. Drawing from the recently released Department of Health and Human Services weekly hospitalization data, we study the overall hospitalization and ICU usage—not only COVID-19 hospitalizations. Developing a framework that examines overall hospitalizations and ICU usage can better reflect the plausible hospital system recovery path to pre-COVID level hospitalization trends. The models are subsequently employed to generate predictions for county level hospitalization and ICU usage rates in the future under several COVID-19 transmission scenarios considering the emergence of new COVID-19 variants and vaccination rates. The exercise allows us to identify vulnerable counties and regions under stress with high hospitalization and ICU rates that can be assisted with remedial measures. Further, the model will allow hospitals to understand evolving displaced non-COVID hospital demand.

Potential Impact of Nirsevimab on RSV Transmission and Medically Attended Lower Respiratory Tract Illness Caused by RSV: A Disease Transmission Model.

IntroductionRespiratory syncytial virus (RSV) is associated with significant morbidity worldwide, especially among infants. We evaluated the potential impact of prophylactic nirsevimab, a monoclonal antibody, in infants experiencing their first RSV season, and the number of medically-attended lower respiratory tract infection episodes caused by RSV (RSV-MALRTI) in the USA.MethodsWe developed an age-structured, dynamic, deterministic compartmental model reflecting RSV natural history, incorporating USA demographic data and an age-specific contact matrix. We assumed either no effect of nirsevimab on transmission (scenario 1) or a 50% reduction of viral shedding (scenario 2). Model outcomes were RSV-MALRTIs, ICD-9 coded in the Marketscan® database by month. We focused on age groups corresponding to the first 2 years of life, during seven RSV seasons (2008–2015).ResultsScenario 1 illustrated the direct individual benefit when a universal immunization strategy is applied to all infants. In scenario 2, herd protection was observed across age groups, with 15.5% of all avoided cases due to reduced transmission; the greatest impact was in the youngest age group and a benefit was observed in those aged 65+ years.ConclusionThese preliminary data suggest that single-dose nirsevimab will benefit infants experiencing their first RSV season, with a potential increase in effectiveness dependent on nirsevimab’s mechanism of action.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40121-021-00566-9.

An Effective Communication Prototype for Time-Critical IIoT Manufacturing Factories Using Zero-Loss Redundancy Protocols, Time-Sensitive Networking, and Edge-Computing in an Industry 4.0 Environment

The Industrial Internet of things (IIoT), the implementation of IoT in the industrial sector, requires a deterministic, real-time, and low-latency communication response for its time-critical applications. A delayed response in such applications could be life-threatening or result in significant losses for manufacturing plants. Although several measures in the likes of predictive maintenance are being put in place to prevent errors and guarantee high network availability, unforeseen failures of physical components are almost inevitable. Our research contribution is to design an efficient communication prototype, entirely based on internet protocol (IP) that combines state-of-the-art communication computing technologies principles to deliver a more stable industrial communication network. We use time-sensitive networking (TSN) and edge computing to increase the determinism of IIoT networks, and we reduce latency with zero-loss redundancy protocols that ensure the sustainability of IIoT networks with smooth recovery in case of unplanned outages. Combining these technologies altogether brings more effectiveness to communication networks than implementing standalone systems. Our study results develop two experimental IP-based industrial network communication prototypes in an intra-domain transmission scenario: the first one is based on the parallel zero-loss redundancy protocol (PRP) and the second one using the high-availability seamless zero-loss redundancy protocol (HSR). We also highlight the benefits of utilizing our communication prototypes to build robust industrial IP communication networks with high network availability and low latency as opposed to conventional communication networks running on seldom redundancy protocols such as Media Redundancy Protocol (MRP) or Rapid Spanning Tree Protocol (RSTP) with single-point of failure and delayed recovery time. While our two network communication prototypes—HSR and PRP—offer zero-loss recovery time in case of a single network failure, our PRP communication prototype goes a step further by providing an effective redundancy scheme against multiple link failures.

UAV-Assisted Underwater Sensor Networks Using RF and Optical Wireless Links

Underwater sensor networks (UWSNs) are of interest to gather data from underwater sensor nodes (SNs) and deliver information to a terrestrial access point (AP) in the uplink transmission, and transfer data from the AP to the SNs in the downlink transmission. In this paper, we investigate a triple-hop UWSN in which autonomous underwater vehicle (AUV) and unmanned aerial vehicle (UAV) relays enable end-to-end communications between the SNs and the AP. It is assumed that the SN–AUV, AUV–UAV, and UAV–AP links are deployed by underwater optical communication (UWOC), free-space optic (FSO), and radio frequency (RF) technologies, respectively. Two scenarios are proposed for the FSO uplink and downlink transmissions between the AUV and the UAV, subject to water-to-air and air-to-water interface impacts; direct transmission scenario (DTS) and retro-reflection scenario (RRS). After providing the channel models and their statistics, the UWSN's outage probability and average bit error rate (BER) are computed. Besides, a tracking procedure is proposed to set up reliable and stable AUV– UAV FSO communications. Through numerical results, it is concluded that the RSS scheme outperforms the DTS one with about 200% (32%) and 80% (17%) better outage probability (average BER) in the uplink and downlink, respectively. It is also shown that the tracking procedure provides on average 480% and 170% improvements in the network's outage probability and average BER, respectively, compared to poorly aligned FSO conditions. The results are verified by applying Monte-Carlo simulations.

Мониторинг состояния и использования русского языка и других языков народов Российской Федерации

The article outlines the ideology of monitoring the transgenerational transmission of the Russian language and other languages of the peoples of the Russian Federation for the national-territorial subjects of the Russian Federation, emphasizing the importance of data on the number of speakers of a particular language in different age and social cohorts, on their competence levels, on real bilingualism and multilingualism, on language transmission mechanisms from older to younger generations to determine the viability of minority languages and thus to plan measures to save, support and revive them. The provisions of the "Framework Convention for the Protection of National Minorities" relating to the study of majority and minority languages in the educational systems of multilingual and multinational states are also analyzed, and the leading role of Russian as the national language is shown. Developed a monitoring scenario for transgenerational language transmission (for households), taking into account maximum unification with the program of the General Population Census of the Russian Federation, which was published during the trial census in 2018. The monitoring questions are grouped into three clusters, each of which reflects different aspects of the sociolinguistic situation: the territorial distribution of languages and family relations within the household; the ethnic, socio-age and educational characteristics of the respondent; the linguistic characteristics of the respondent.

Transfer Learning for Neural Networks-Based Equalizers in Coherent Optical Systems

In this work, we address the question of the adaptability of artificial neural networks (NNs) used for impairments mitigation in optical transmission systems. We demonstrate that by using well-developed techniques based on the concept of transfer learning, we can efficaciously retrain NN-based equalizers to adapt to the changes in the transmission system, using just a fraction (down to 1%) of the initial training data or epochs. We evaluate the capability of transfer learning to adapt the NN to changes in the launch power, modulation format, symbol rate, or even fiber plants (different fiber types and lengths). The numerical examples utilize the recently introduced NN equalizer consisting of a convolutional layer coupled with bi-directional long-short term memory (biLSTM) recurrent NN element. Our analysis focuses on long-haul coherent optical transmission systems for two types of fibers: the standard single-mode fiber (SSMF) and the TrueWave Classic (TWC) fiber. We underline the specific peculiarities that occur when transferring the learning in coherent optical communication systems and draw the limits for the transfer learning efficiency. Our results demonstrate the effectiveness of transfer learning for the fast adaptation of NN architectures to different transmission regimes and scenarios, paving the way for engineering flexible and universal solutions for nonlinearity mitigation.