Secure transmission of IRS-UAV buffer-aided relaying system with delay constraint

The paper proposes a new class of traffic profiles that is better suited for metering bursty Internet traffic streams than the traditional token bucket profile. A good traffic profile should satisfy two criteria: first, it should consider packets from a conforming traffic stream as in-profile with high probability to ensure a strong QoS guarantee; second, it should limit the network resources consumed by a non-conforming traffic stream to no more than that consumed by a conforming stream. We model a bursty Internet traffic stream as an ON/OFF stream, where both the ON-period and the OFF-period have a heavy-tailed distribution. Our study shows that the heavy-tailed distribution leads to an excessive randomness in the long-term session rate distribution. Therefore, it is inherently difficult for any profile that limits the long-term average session rate to give a strong QoS guarantee for the conforming traffic streams. Our simulation demonstrates that a token bucket profile that couples the average rate control and the burst size control has a weak QoS guarantee. Based on this result, we propose a new class of traffic profiles that decouples the long term average rate control from the burst size control. Compared to a token bucket profile, this profile improves the level of QoS for a conforming traffic stream, yet limits the effective bandwidth consumed by a non-conforming traffic stream.

This study investigates security issues in a scenario involving a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted unmanned aerial vehicle (UAV) with integrated sensing and communication (ISAC) functionality (UAV-ISAC). In this scenario, both legitimate users and eavesdropping users are present, which makes security a crucial concern. Our research goal is to extend the system's coverage and improve its flexibility through the introduction of STAR-RIS, while ensuring secure transmission rates. To achieve this, we propose a secure transmission scheme through jointly optimizing the UAV-ISAC trajectory, transmit beamforming, and the phase and amplitude adjustments of the STAR-RIS reflective elements. The approach seeks to maximize the average secrecy rate while satisfying communication and sensing performance standards and transmission security constraints. As the considered problem involves coupled variables and is non-convex, it is difficult to solve using traditional optimization methods. To address this issue, we adopt a multi-agent deep reinforcement learning (MADRL) approach, which allows agents to interact with the environment to learn optimal strategies, effectively dealing with complex environments. The simulation results demonstrate that the proposed scheme significantly enhances the system's average secrecy rate while satisfying communication, sensing, and security constraints.

In this letter, we investigate a joint power and rate optimization for a multihop relay network with incremental redundancy hybrid ARQ (HARQ-IR), where multiple relays are serially connected from a source to a destination. The optimization problem is to adjust both transmission rate and power of each node in order to maximize long-term average transmission rate (LATR) for given sum-power and delay constraints, which is unfortunately not mathematically tractable. Hence, we propose a sub-optimal algorithm to improve the LATR, which is computationally efficient and has comparable performance with the exhaustive search algorithm. Simulation results show that the proposed algorithm outperforms the conventional algorithms, including the HARQ-IR scheme with fixed power and rate and the Chase-combining HARQ scheme of which both power and rate are optimized for the same network.

We consider private commons for secondary sharing of licensed spectrum bands with no access coordination provided by the primary license holder. In such environments, heterogeneity in demand patterns of the secondary users can lead to constant changes in the interference levels, and thus can be a source of volatility to the utilities of the users. In this paper, we consider secondary users to be service providers that provide downlink services. We formulate the spectrum sharing problem as a non-cooperative iterated game of power control where service providers change their power levels to fix their long-term average rates at utility-maximizing values. First, we show that in any iterated 2x 2 game, the structure of the single-stage game dictates the degree of control that a service provider can exert on the long-term outcome of the game. Then we show that if service providers use binary actions either to access or not to access the channel at any round of the game, then the long-term rate can be fixed regardless of the strategy of the opponent. We identify these rates and show that they can be achieved using mixed Markovian strategies which will be also identified.

Long-term average mineral weathering rates from watershed geochemical mass balance methods: Using mineral modal abundances to solve more equations in more unknowns

Broadcasting over the fading wiretap channel is investigated for the situation without the channel state information (CSI) at the transmitter and subject to a delay constraint. A new broadcast approach is developed, which integrates secure superposition coding studied in the authors' previous work and embedded coding in a hybrid fashion. This scheme outperforms the previous approaches for the cases when the eavesdropper's channel is fading. The secrecy rate achievable via the new broadcast approach is derived, and the structure of the optimal power allocation function across the secure coding layers is characterized via techniques for solving the problem of constrained calculus of variations. A notion of probabilistic secrecy is introduced and studied, which characterizes the probability that a certain secrecy rate is achieved for any given fading block. Numerical examples are provided to demonstrate the impact of CSI at the transmitter if not available and the channel fluctuation of the eavesdropper on the average secrecy rate.

The rapid advancements of intelligent technologies have brought about the potential vulnerability of confidential gradient information linked to cost functions when solving distributed optimization and its related problems. Within the context of distributed energy management, safeguarding such private information has risen to paramount importance. This article investigates a distributed energy management problem (DEMP) to minimize cost while simultaneously satisfying multiple local constraints and protecting the private gradient information of the cost function. To this end, a new privacy‐preserving distributed optimization algorithm under the framework of gradient tracking over time‐varying graphs is proposed for solving the DEMP. Specifically, the auxiliary variables are designed for each node in the algorithm to update the gradient while the original state variables are responsible for the interaction with original neighbors and auxiliary variables. Consequently, the devised algorithm can protect the confidentiality of private cost gradient information, even in the presence of eavesdroppers within the network. In contrast to the homomorphic encryption, signal masking method, and some other algorithms without utilizing the state decomposition, the designed algorithm does not require extra information or computing resources. Moreover, it is proven that the designed algorithm could theoretically converge to the exact optimum of the DEMP at a rate of under some mild assumptions.

Energy harvesting (EH) wireless communications have become more and more popular due to its capability of effectively reducing the battery replacement time. In this paper, we focus on decode-and-forward-based cooperative wireless communications with an EH relay. The stochastic characteristics of the harvestable energy and the wireless channel make it difficult to optimally manage the energy harvested at the relay for better communication performance. We formulate such a problem as an optimization by minimizing the long-term average symbol error rate (SER) subject to a battery constraint. Based on the Lyapunov optimization theory, we utilize the virtual queue technique and transform the optimization problem into a drift-plus-penalty minimization. Then, we conduct theoretic analysis of the optimal energy strategy derived by the proposed scheme. Specifically, we show the convexity of the drift-plus-penalty minimization problem, and prove that the virtual queue is bounded and the battery constraint is always satisfied. We also show that the proposed optimal energy management strategy is limited by an upper bound that is independent of the operation time index, derive the closed-form expression for the asymptotical average SER, and analyze the corresponding diversity order and EH gain. Finally, simulation results using the real solar irradiance data show that the proposed algorithm can achieve much better performance in terms of both average SER and diversity order, compared with the Markov decision process-based method.

Introduction: The complex of exogenous and endogenous risk factors in multidisciplinary hospitals creates conditions for the development of nosocomial infections induced by ESKAPE pathogens. Objective: To establish epidemiological features and etiological significance of antibiotic resistant strains of the leading pathogens inducing hospital-acquired infections and to determine their prevalence in multidisciplinary clinics of the Republic of North Ossetia–Alania. Materials and methods: We analyzed the incidence of nosocomial infections and results of the microbiological monitoring of antimicrobial drug resistance in leading pathogens for the years 2012–2021. Detection of genes encoding the production of metallo-β-lactamases was performed in P. aeruginosa strains, extended-spectrum β-lactamases and PFGE profiles of E. coli and K. pneumoniae strains. Results: In the Republic of North Ossetia–Alania, the average long-term incidence rate of hospital-acquired infections in the study period was 0.74 per 1,000 inpatients. We established that 44.2 % of all such cases were diagnosed in surgical departments, 32.4 % – in maternity departments, 6.6 % – in pediatric departments, and 16.8 % – in other clinical departments. The average long-term incidence rate of nosocomial infections was the highest (0.85 per 1,000 patients) in departments of surgery, the most prevalent being surgical and injection site infections, lower respiratory tract and urinary tract infections. The leading pathogens in the etiological structure were Enterobacteriaceae spp., P. aeruginosa and Staphylococcus spp. The incidence rates estimated based on microbiological monitoring results were on average 2.5 times higher than those registered within the routine surveillance system. Conclusions: Incidence rates of healthcare-associated infections in the Republic of North Ossetia–Alania are comparable to those in the Russian Federation. Patients of surgery departments are at higher risk for nosocomial infections. Optimization of preventive measures requires a risk-based approach that takes into account in-depth microbiological monitoring data on the most common pathogens resistant to drugs of choice in local hospitals.

Objective: to identify modern epidemiological features of viral acute intestinal infections in children and adolescents in the Sakhalin Region.Materials and methods. Data on acute intestinal infection incidence obtained from statistical reports of the Rospotrebnadzor during 2021-2023 was compared with long-term average incidence rates calculated over the period before the COVID-19 pandemic (2010-2019) to perform epidemiological analysis. Incidence was calculated for different age groups; according to months of the year, monthly long-term average incidence rates were established. Index of seasonality, coefficient of seasonality, and index of seasonal growth were determined.Results and discussion. Manifestations of acute intestinal infections epidemic process in the Sakhalin Region indicate persisting conditions for an increase in the registration of both sporadic cases of diseases and outbreaks of infectious diarrhea. Viruses were prevailing in the structure of cases of known etiology (mainly caused by rotaviruses and noroviruses). Their intra-annual dynamics showed changes in rotavirus and norovirus infection incidence rates: a shift in periods of increased incidence, a decrease in the coefficient of seasonality, and for rotavirus infection, a decrease in the index of seasonal growth. Age-adjusted rotavirus infection incidence showed predominance of the infection among preschool-aged children; norovirus infection was frequently detected among schoolchildren and adolescents. An increase in the focality index may indicate ongoing problems in the public catering sector, non-compliance with sanitary rules and hygiene standards, and untimely detection and isolation of patients with acute intestinal infections.Conclusion. Obtained results confirm the epidemiological significance of viral gastroenteritis and the necessity of anti-epidemic measures optimization.

In this paper, we consider a buffer-aided multiuser multiple-input single-output (MISO) network consisting of one multi-antenna access point (AP) and multiple single-antenna users, in which the AP is provisioned with data buffers for temporarily storing the data for each user either from the upper layer applications or the message by the AP. The data for one specific user must be kept confidential from all other unintended users. For such a system, we aim at maximizing the long-term average achievable secrecy rate region by carefully designing the flow control, the information signal and artificial noise beamforming, as well as the user selection. To address this issue, we first transform the time average optimization problem into a real-time one by using the Lyapunov optimization framework. Then it is proposed to decompose the optimization problem into several sub-problems by using the optimization decomposition technique. Although the information signal and artificial noise beamforming sub-problem is non-convex, we show that it can be decomposed into a two-stage optimization problem to effectively solve it by using the exact line search and DC (difference of two convex functions) algorithms. Moreover, we extend the average secrecy rate region maximization problem to the worst-case scenario, in which all unintended users are colluding in eavesdropping. Our analysis discloses that, there exists an inherent tradeoff between the average achievable secrecy rate region and the average queueing length. It is shown that a better average secrecy rate region can be realized by fully taking advantage of the buffer-aided transmission potentials in the MISO network, if a certain queueing delay is tolerable.

Short and long-term delivery rates of meteoric 10Be to terrestrial soils

The security of a wireless channel between a transmitter and legitimate user(s) in the presence of eavesdroppers can be improved by the addition of artificial noise (AN) transmission. In the case where the channel state information of the eavesdroppers is not known, some AN schemes transmit multiple uncorrelated noise signals via distinct orthogonal beamforming vectors. The vectors are designed to avoid affecting the legitimate links, and mutual orthogonality increases the likelihood that the AN signals are received at the eavesdroppers with high power. Applications in massive-MIMO, where hardware is constrained, motivate us to design vectors whose elements have arbitrary phases but equal magnitudes [1].This work proposes an algorithm that generates multiple such phase-only beamforming vectors via a single optimization problem and significantly increases the number of vectors which can be found compared to the previous work [2]. Consequently, our results demonstrate substantially higher lower-bounds on maximum achievable secrecy rate via this approach compared to the previous work [2] for similar scenarios.

Summary. The consistency of earthquake data and plate tectonic models and other estimates of fault slip, may be tested by estimating rates of motion from the earthquakes using the concept of seismic moment. The contribution of individual events may simply be summed, but a generally better estimate of long-term average slip rate is obtained by integration over magnitudefrequency of occurrence relations. Estimates of fault motion rates associated with earthquakes are possible within about a factor of 2 using this approach if the major sources of uncertainty are given careful consideration; e.g. incompleteness and inaccuracies in the earthquake data; empirical moment-magnitude relations and the effect of their stochasticity; fault ‘widths’ or depth extents; the recurrence relations; maximum magnitudes and the form of truncation at the maximum magnitude. A formulation for the recommended magnitude density truncation is developed. Application of the latter method to the earthquake data of the offshore transform faults of the Juan de Fuca ridge system, the Queen Charlotte fault zone and the northern Vancouver Island area in each case gives good agreement with rates from plate tectonic models. For the southern San Andreas fault and Gulf of California area there is also good agreement with previous estimates obtained by summing the contributions of individual events. However, the displacement rate in the margin convergence zone of southern British Columbia, Washington and Oregon computed from the seismicity is at least a factor of 10 lower than from plate models and from other convergence estimates, and primarily aseismic slip is suggested. The fault motions as a function of time computed from the seismicity records have also been plotted and compared to the longterm average rates. The plots permit estimates of the minimum present accumulated elastic strain, and show if there are any temporal relations among earthquake displacements on different fault zones.

We present an interpolation method for efficient approximation of parametrized functions. The method recognizes and exploits the low‐dimensional manifold structure of the parametrized functions to provide good approximation. Basic ingredients include a specific problem‐dependent basis set defining a low‐dimensional representation of the parametrized functions, and a set of ‘best interpolation points’ capturing the spatial‐parameter variation of the parametrized functions. The best interpolation points are defined as solution of a least‐squares minimization problem which can be solved efficiently using standard optimization algorithms. The approximation is then determined from the basis set and the best interpolation points through an inexpensive and stable interpolation procedure. In addition, an a posteriori error estimator is introduced to quantify the approximation error and requires little additional cost. Numerical results are presented to demonstrate the accuracy and efficiency of the method. Copyright © 2007 John Wiley & Sons, Ltd.