Average Transmission Probability Research Articles

Transition-state theory reexamined.

Two quantum systems, each described as a random-matrix ensemble, are coupled to each other via a number of transition states. Each system is strongly coupled to a large number of channels. The average transmission probability is the product of three factors describing, respectively, formation of the first system from the entrance channel, decay of the second system through the exit channel, and transport through the transition states. Each of the transition states contributes a Breit-Wigner resonance. In general, the resonances overlap.

On multiple handoff blocking‐then‐reaccess for opportunistic spectrum access

AbstractOpportunistic spectrum access (OSA), a promising technology to resolve radio spectrum scarcity, is still faced with some challenges, of which one is potentially frequent channel handoff (CH) even handoff blocking (HB) for secondary user (SU) to avoid primary user (PU). Reaccess is a direct way to resolve HB. However, multiple handoff blocking‐then‐reaccess (H‐BTR) are time consuming. Whether it is worthwhile to make multiple H‐BTR, is an interesting but hardly mentioned issue. To this end, the multiple H‐BTR‐based OSA are focused on here. Three key indices, the average transmission probability, handoff delay, and average reaccess times of SU in the H‐BTR‐based OSA, are deduced as close form first. Then, the effects of H‐BTR frequency and service traffic rate of SU on OSA are discussed. Finally, the H‐BTR‐based OSA is compared to two other schemes, the handoff without BTR (HWBTR)‐based OSA and the stop‐and‐waiting (SW)‐based OSA. Theoretical and simulated results show that the H‐BTR‐based OSA performs best among three schemes. Making H‐BTR in moderate frequency according to service traffic rate can increase transmission opportunity while additional delay of SU is tolerable, thus the performance of OSA can be well improved.

Modelling Analysis of a Novel Frameless Slotted-ALOHA Protocol Based on the Number of Detectable Conflicting Users

To solve the conflict when multi-user packets are transmitted in a shared wireless link, a novel frameless slotted-ALOHA protocol is proposed. Signature codes are used to help the receiver identify the set of transmitting users, and successive interference cancellation technology is employed to recover conflicting packets. Thus, the information in the conflicting slot can be reused to reduce the number of retransmissions. Taking the number of backlogged users in each slot as a system state, a Markov chain model is established to analyze the protocol, in which the state transition probabilities are obtained based on the binomial distribution of packets sent in a slot. Under the maximum number of detectable conflicting users, the best value is taken, traffic balance equations are obtained, and the expressions of throughput, average number of backlogged users, average successful transmission probability and average memory size are derived. Finally, a numerical simulation is carried out to accurately analyze the influence of the first transmission probability of the packets on various performance indexes and the effectiveness of the theoretical analysis is further verified by the simulation results.

Distinct spreading patterns induced by coexisting channels in information spreading dynamics.

In modern society, new communication channels and social platforms remarkably change the way of people receiving and sharing information, but the influences of these channels on information spreading dynamics have not been fully explored, especially in the aspects of outbreak patterns. To this end, based on a susceptible-accepted-recovered model, we examined the outbreak patterns of information spreading in a two-layered network with two coexisting channels: the intra-links within a layer and the inter-links across layers. Depending on the inter-layer coupling strength, i.e., average node degree and transmission probability between the two layers, we observed three different spreading patterns: (i) a localized outbreak with weak inter-layer coupling, (ii) two peaks with a time-delay outbreak appear for an intermediate coupling, and (iii) a synchronized outbreak for a strong coupling. Moreover, we showed that even though the average degree between the two layers is small, a large transmission probability still can compensate and promote the information spread from one layer to another, indicating by that the critical average degree decreases as a power law with transmission probability between the two layers. Additionally, we found that a large gap closed to the critical inter-layer average degree appears in the phase space of theoretical analysis, which indicates the emergence of a global large-scope outbreak. Our findings may, therefore, be of significance for understanding the outbreak behaviors of information spreading in real world.

A Reliable Merging Link Scheme Using Weighted Markov Chain Model in Vehicular Ad Hoc Networks.

The vehicular ad hoc network (VANET) is a potential technology for intelligent transportation systems (ITS) that aims to improve safety by allowing vehicles to communicate quickly and reliably. The rates of merging collision and hidden terminal problems, as well as the problems of picking the best match cluster head (CH) in a merged cluster, may emerge when two or more clusters are merged in the design of a clustering and cluster management scheme. In this paper, we propose an enhanced cluster-based multi-access channel protocol (ECMA) for high-throughput and effective access channel transmissions while minimizing access delay and preventing collisions during cluster merging. We devised an aperiodic and acceptable merge cluster head selection (MCHS) algorithm for selecting the optimal merge cluster head (MCH) in centralized clusters where all nodes are one-hop nodes during the merging window. We also applied a weighted Markov chain mathematical model to improve accuracy while lowering ECMA channel data access transmission delay during the cluster merger window. We presented extensive simulation data to demonstrate the superiority of the suggested approach over existing state-of-the-arts. The implementation of a MCHS algorithm and a weight chain Markov model reveal that ECMA is distinct and more efficient by 64.20–69.49% in terms of average network throughput, end-to-end delay, and access transmission probability.

Per-partnership transmission probabilities for Chlamydia trachomatis infection: evidence synthesis of population-based survey data.

BackgroundChlamydia is the most commonly diagnosed sexually transmitted infection worldwide. Mathematical models used to plan and assess control measures rely on accurate estimates of chlamydia’s natural history, including the probability of transmission within a partnership. Several methods for estimating transmission probability have been proposed, but all have limitations.MethodsWe have developed a new model for estimating per-partnership chlamydia transmission probabilities from infected to uninfected individuals, using data from population-based surveys. We used data on sexual behaviour and prevalent chlamydia infection from the second UK National Study of Sexual Attitudes and Lifestyles (Natsal-2) and the US National Health and Nutrition Examination Surveys 2009–2014 (NHANES) for Bayesian inference of average transmission probabilities, across all new heterosexual partnerships reported. Posterior distributions were estimated by Markov chain Monte Carlo sampling using the Stan software.ResultsPosterior median male-to-female transmission probabilities per partnership were 32.1% [95% credible interval (CrI) 18.4–55.9%] (Natsal-2) and 34.9% (95%CrI 22.6–54.9%) (NHANES). Female-to-male transmission probabilities were 21.4% (95%CrI 5.1–67.0%) (Natsal-2) and 4.6% (95%CrI 1.0–13.1%) (NHANES). Posterior predictive checks indicated a well-specified model, although there was some discrepancy between reported and predicted numbers of partners, especially in women.ConclusionsThe model provides statistically rigorous estimates of per-partnership transmission probability, with associated uncertainty, which is crucial for modelling and understanding chlamydia epidemiology and control. Our estimates incorporate data from several sources, including population-based surveys, and use information contained in the correlation between number of partners and the probability of chlamydia infection. The evidence synthesis approach means that it is easy to include further data as it becomes available.

Tunneling Through a One-Dimensional Square Potential Barrier Under Fluctuations in an Observer’s Frame of Reference

This study reports tunneling through a one-dimensional (1D) square potential barrier (SPB) under fluctuations in an observer’s frame of reference (OFR). To date, tunneling through an SPB has been studied under the assumption that the OFR remains constant throughout the tunneling measurements; therefore, the change of the tunneling probability when the OFR is assumed to fluctuate remains unanswered. In this paper, a 1D SPB is considered under fluctuations of an OFR. The average transmission probability of a particle through an SBP for two types of OFR fluctuations (periodic-square-wave and periodic-sawtooth-wave fluctuations) is formulated in time representations. Under these types of fluctuations, the average transmission probability gradually increases with a particle’s energy, which is saturated to the transmission probability in the case of the stationary OFR at a much greater energy than the amplitude of the fluctuations. The average transmission probability is much higher at the amplitude of the fluctuations in the case of periodic-square-wave fluctuations. Therefore, the average transmission probability with a particle’s energy has the potential to reveal the distribution of OFR fluctuations.

Enhancing Physical Layer Security of Random Caching in Large-Scale Multi-Antenna Heterogeneous Wireless Networks

In this paper, we propose a novel secure random caching scheme for large-scale multi-antenna heterogeneous wireless networks, where the base stations (BSs) deliver randomly cached confidential contents to the legitimate users in the presence of passive eavesdroppers as well as active jammers. In order to safeguard the content delivery, we consider that the BSs transmits the artificial noise together with the useful signals. By using tools from stochastic geometry, we first analyze the average reliable transmission probability (RTP) and the average confidential transmission probability (CTP), which take both the impact of the eavesdroppers and the impact of the jammers into consideration. We further provide tight upper and lower bounds on the average RTP. These analytical results enable us to obtain rich insights into the behaviors of the average RTP and the average CTP with respect to key system parameters. Moreover, we optimize the caching distribution of the files to maximize the average RTP of the system, while satisfying the constraints on the caching size and the average CTP. Through numerical results, we show that our proposed secure random caching scheme can effectively boost the secrecy performance of the system compared to the existing solutions.

A Stochastic Geometry Approach to Model and Analyze Future Vehicular Communication Networks

Safety message dissemination in a vehicular communication network requires vehicle-to-vehicle (V2V) communication with low latency and high reliability. To fulfill the stringent requirements in terms of reliability associated with safety applications, a control information assisted three-step (CIAT) resource selection scheme based on cellular vehicle-to-everything (C-V2X) technology for future vehicular communication network is investigated in this paper. To get a mathematical understanding of the process and performance of the CIAT scheme, in this paper, we develop an effective analytical approach to characterize the properties of the CIAT resource selection scheme in vehicular communication network by using the tool of stochastic geometry. In particular, the resource selection process and the key performances are analyzed mathematically; The closed-form expressions for the key performances are derived, which include the resource exclusion ratio, the average successful transmission probability and the packet inter-reception time; Furthermore, the performances of CIAT resource selection scheme are compared with those of random resource selection scheme mathematically. All the analytical results in this paper are validated through extensive Monte Carlo simulations, and the results provide insights to proper parameter settings for future vehicular communication network.

Effects of two channels on explosive information spreading

Information spreading has been studied for decades, but the underlying mechanism why the information can be accepted by a large number of people overnight is still under debate, especially in the aspects of two-channel effects for information transmission and theoretical analysis. In this study, based on a susceptible-accepted-recovered (SAR) model, we examine the effects of two channels represented by a two-layered network, in which one channel is the intra-links within the same layer and the other is inter-links between layers. Different with the case of one single channel on a one-layered network, in the case of two channels, the spreading can be speeded up by the increase in the coupling strength, i.e., average node degree and transmission probability between the two layers. Strikingly, even if the parameter (social reinforcement) is small, the strongly coupling strength can induce explosive transition in the information spreading process. Additionally, a big gap closed to the critical point for the explosive transition was found in the phase space of theoretical analysis, which indicates the emergency of a global large-scope outbreak. These findings may be of significance on the understanding and controlling explosive information spreading in modern society.

Dual-Mode User-Centric Open-Loop Cooperative Caching for Backhaul-Limited Small-Cell Wireless Networks

The spectral efficiency of small-cell wireless networks is limited by the backhaul capacity of the base stations (BSs) as well as the severe interference from the neighboring BSs. One promising approach to improve the spectral efficiency of small-cell wireless networks is cache-aided cooperative transmission, where caching at the BSs can alleviate the high-speed backhaul capacity requirement and cooperative transmission can enhance the signal-to-interference-plus-noise ratio. A key issue is that the cached content may not be located at the nearest BS, which means that to access such content, a user needs to overcome strong interference from the nearby BSs. We propose an interference-aware dual-mode caching and user-centric open-loop cooperative transmission scheme that embraces spatial caching diversity and user-centric open-loop cooperative transmission, and alleviate the interference issue in the system. Based on the proposed scheme, we derive a tractable expression of the average successful transmission probability (STP) in terms of key system parameters. We then design a low-complexity algorithm to optimize the average STP with respect to the bandwidth and the cache storage capacity allocation. Simulations show that the proposed scheme achieves a higher average STP than the existing caching schemes.

Exploiting Secondary Caching for Cooperative Cognitive Radio Networks

This letter proposes a cache-enabled cooperation scheme to improve the performance of cognitive radio networks. We jointly optimize the content placement and the bandwidth allocation to maximize the secondary users’ average successful transmission probability under the quality of service constraint of the primary user. Although the original problem is not convex, an efficient two-level bisection search algorithm is proposed to find the optimal cache and spectrum allocation solution to the approximated problem. Simulation results verify that the cache-enabled cooperation outperforms existing schemes significantly.

Electrically tunable crossed Andreev reflection in a ferromagnet–superconductor–ferromagnet junction on a topological insulator

We investigate the crossed Andreev reflection in a ferromagnet–superconductor–ferromagnet junction on the surface of a topological insulator, where the magnetizations in the left and right leads are perpendicular to the surface. We find that the nonlocal transport process can be pure crossed Andreev reflection or pure elastic cotunneling, and the switch between the two processes can be controlled electrically. Pure crossed Andreev reflection appears for all bias voltages in the superconducting energy gap, which is independent of the configuration of the magnetizations in the two leads. The spin of the crossed Andreev reflected hole could be parallel to the spin of the incident electron, which is brought by the spin-triplet pairing correlation. The average transmission probability of crossed Andreev reflection can be larger than 90%, so a high efficiency nonlocal splitting of Cooper pairs can be generated, and turned on and off electrically.

Simulating the Transmission and Recovery from Ebola Virus Disease (EVD) to Understand the Impact of Experimental Drug Might Have in Three West African Countries

Ebola Virus Disease (EVD) has become one of the deadly epidemics that have caused the death of many in recent times. Three West African countries; Liberia, Sierra Leone and Guinea have experienced the worst spread of the disease since the disease outbreak recently. There have been suspected, probable and confirmed 17,145 reported cases of the disease in all the affected countries, with 6,070 reported deaths. This paper employs the SIRS (Susceptible, Infected, Recovered and Susceptible) model and cellular automata model (global stochastic contact model) with real parameters that include average contact, recovery period, infectious period and transmission probability to simulate in order to understand how the new Ebola experimental drug (ZMAPP) that is used to cure 3 patients could impact on a population hit by the disease and the period of time it will take to eradicate the epidemic. The study can serve as a basis for understanding the vaccination effect on Ebola virus based on real parameters.

Downlink SINR and rate distribution of ultra-dense HetNets with burst traffic

SINR distribution and rate overage distribution are crucial for optimization of deployment of Ultra-dense HetNets. Most existing literatures assume that BSs have full queues and full-buffer traffic. In fact, due to ultra-dense deployment of small cells, traffic in small cell varies dramatically in time and space domains. Hence, it is more practical to investigate scenario with burst traffic. In this paper, we consider a two-tier non-uniform ultra-dense HetNet with burst traffic, where macro BSs are located according to Poisson Point Process (PPP), and pico BSs are located according to Poisson Hole Process (PHP). The closed-form expressions of SINR distribution and rate distribution are derived, and then validated through simulation. Our study shows that different from the result of full buffer case, the SINR distribution and rate distribution of users depend on the average transmission probabilities of BSs in burst traffic case.

Energy‐optimal base station density considering traffic dynamics

Optimal base station (BS) density, to minimise network energy consumption, is studied. Contrary to previous works, both the spatial randomness of the network topology and the wireless traffic dynamics are taken into consideration. With the technology of cell discontinuous transmission, network energy consumption depends on the average transmission probability of BSs. On the basis of stochastic geometry, it is found that the BS transmission probability and BS density satisfy a nonlinear equation. To reduce overall energy consumption, an iteration algorithm that can converge to the global optimal BS density is proposed.

Random Access Game in Fading Channels With Capture: Equilibria and Braess-like Paradoxes

The Nash equilibrium point of the transmission probabilities in a slotted ALOHA system with selfish nodes is analyzed. The system consists of a finite number of heterogeneous nodes, each trying to minimize its average transmission probability (or power investment) selfishly while meeting its average throughput demand over the shared wireless channel to a common base station (BS). We use a game-theoretic approach to analyze the network under two reception models: one is called power capture, the other is called signal to interference plus noise ratio (SINR) capture. It is shown that, in some situations, Braess-like paradoxes may occur. That is, the performance of the system may become worse instead of better when channel state information (CSI) is available at the selfish nodes. In particular, for homogeneous nodes, we analytically present that Braess-like paradoxes occur in the power capture model, and in the SINR capture model with the capture ratio larger than one and the noise to signal ratio sufficiently small.

Optimal Probabilistic Epidemic Forwarding for Energy Constrained Delay Tolerant Networks

In delay tolerant networks, energy efficient forwarding algorithms are significant to enhance the performance of message transmission probability. In this paper, we focus on the problem of optimal probabilistic epidemic forwarding with energy constraint. By introducing a continuous time model, we obtain the optimal static and dynamic policies for multi-messages forwarding. Extensive numerical results show that the optimal dynamic policy achieves higher transmission probability than the optimal static policy while the number of messages decreases the average transmission probability.

Average transmission probability of a random stack

The transmission through a stack of identical slabs that are separated by gaps with random widths is usually treated by calculating the average of the logarithm of the transmission probability. We show how to calculate the average of the transmission probability itself with the aid of a recurrence relation and derive analytical upper and lower bounds. The upper bound, when used as an approximation for the transmission probability, is unreasonably good and we conjecture that it is asymptotically exact.

Probability of HIV Transmission During Acute Infection in Rakai, Uganda

Accurate estimates of the probability of HIV transmission during various stages of infection are needed to inform epidemiological models. Very limited information is available about the probability of transmission during acute HIV infection. We conducted a secondary analysis of published data from the Rakai, Uganda seroconversion study. Mathematical and computer-based models were used to quantify the per-act and per-partnership transmission probabilities during acute and chronic HIV infection, and to estimate how many of the transmission events reported in the Rakai study were due to acute-phase HIV transmission. The average per-act transmission probability during acute infection equaled 0.03604 vs. 0.00084 for chronic HIV infection. Overall, HIV was transmitted during acute infection in 46.5% of 23 "incident index partner couples." Acute-phase transmission accounted for 89.1% of all transmission events in the first 20 months of follow-up. These results highlight the substantial risk of transmission during acute HIV infection.