Average Number Of Transmissions Research Articles

Modeling Epidemic Routing: Capturing Frequently Visited Locations While Preserving Scalability

This paper investigates the performance of epidemic routing in mobile social networks considering several communities which are frequently visited by nodes. To this end, a monolithic Stochastic Reward Net (SRN) is proposed to evaluate the delivery delay and the average number of transmissions under epidemic routing by considering skewed location visiting preferences. This model is not scalable enough, in terms of the number of nodes and frequently visited locations. In order to achieve higher scalability, the folding technique is applied to the monolithic model, and an approximate folded SRN is proposed to evaluate performance of epidemic routing. Discrete-event simulation is used to validate the proposed models. Both SRN models for predicting the performance of epidemic routing exhibit high accuracy. We also propose an Ordinary Differential Equation (ODE) model for epidemic routing and compare it with the folded model. The obtained results show that the folded model is more accurate than the ODE model. Moreover, it is proved that the number of transmissions by the time of delivery follows a uniform distribution, for a general class of networks, where positions of nodes are always independent and identically distributed.

An Efficient Coded Streaming Using Clients' Cache.

As multimedia traffic has been increasing and is expected to grow more sharply, various technologies using caches have been attracting lots of attention. As one breakthrough technology to deal with the explosively growing traffic, exclusive OR (XOR)-based index coding has been widely investigated because it can greatly enhance the efficiency of network resource by reducing the number of transmissions. In this paper, we investigate how to apply XOR-based index coding to large-scaled practical streaming systems for video traffic that accounts for more than 70% of total Internet traffic. Contrary to most previous studies that have focused on theoretical analysis of optimal performance or development of optimal index coding schemes, our study proposes a new XOR coding-based video streaming (XC). We also propose a new grouping algorithm for creating XC groups while guaranteeing the complete backward compatibility of XC with existing streaming schemes such as unicast (UC), multicast (MC), and broadcast (BC). The performance of the proposed scheme is analyzed in two steps. First, the behavior of video contents in caches at clients is modeled as a Markov chain, and the steady-state probabilities and caching probabilities for each piece of video content are derived. Based on the probabilities, the performance of the proposed system is then analyzed in terms of the average number of connections that each client requires in order to receive one video content. Our numerical results show that the proposed video streaming scheme using XC can reduce the average number of transmissions by up to 18%, compared to the conventional scheme.

Application of deep neural network and deep reinforcement learning in wireless communication.

ObjectiveTo explore the application of deep neural networks (DNNs) and deep reinforcement learning (DRL) in wireless communication and accelerate the development of the wireless communication industry.MethodThis study proposes a simple cognitive radio scenario consisting of only one primary user and one secondary user. The secondary user attempts to share spectrum resources with the primary user. An intelligent power algorithm model based on DNNs and DRL is constructed. Then, the MATLAB platform is utilized to simulate the model.ResultsIn the performance analysis of the algorithm model under different strategies, it is found that the second power control strategy is more conservative than the first. In the loss function, the second power control strategy has experienced more iterations than the first. In terms of success rate, the second power control strategy has more iterations than the first. In the average number of transmissions, they show the same changing trend, but the success rate can reach 1. In comparison with the traditional distributed clustering and power control (DCPC) algorithm, it is obvious that the convergence rate of the algorithm in this research is higher. The proposed DQN algorithm based on DRL only needs several steps to achieve convergence, which verifies its effectiveness.ConclusionBy applying DNNs and DRL to model algorithms constructed in wireless scenarios, the success rate is higher and the convergence rate is faster, which can provide experimental basis for the improvement of later wireless communication networks.

On stiff, fuzzy IRD-14 day average transmission model of COVID-19 pandemic disease

COVID-19, a new pandemic disease is becoming one of the major threats for surviving. Many new models are arrived to study the disease mathematically. Here we are introducing a new model in which instead of studying a day by day changes we are studying the average of 14 day transmission because its life or the patients incubation period is about an average of 14 days. Also, since this is pandemic, and being not aware of susceptible population among the world's population, we considered the model without S-susceptible population. i.e., IRD-Infectious, Recovered, Death-model. In this new model, we are also introducing a new method of calculating new number called <i>N</i>₀-average transmission number. This is used to study the average spread of infection instead of basic reproduction number <i>R</i>₀. The motto of this paper is not to predict the daily cases but to control the current spread of disease and deaths by identifying the threshold number, exceeding which will increase the spread of infection and number of deaths due to this pandemic. Also if the 14 day average IRD-populations are maintained under this threshold number, will definitely control this pandemic disease globally. Stability analysis and test for stiff system of differential equations are studied. Our main aim is to present the medical world, a threshold population of infected, recovered and death cases for every average of 14 days to quickly overcome this pandemic disease COVID-19.

Performance Evaluation of Epidemic Content Retrieval in DTNs With Restricted Mobility

In some applicable scenarios, such as community patrolling, mobile nodes are restricted to move only in their own communities. Exploiting the meetings of the nodes within the same community and the nodes within the neighboring communities, a delay tolerant network (DTN) can provide communication between any two nodes. In this paper, two analytical models based on stochastic reward nets (SRNs) are proposed to evaluate the performance of the epidemic content retrieval in such multi-community DTNs. Performance measures computed by the proposed models are the average retrieval delay and the average number of transmissions. The monolithic SRN model proposed in the first step is not scalable, in terms of the number of communities and nodes, due to the state space explosion in the underlying Markov chain. In order to solve the scalability problem of the monolithic model, an approximate model based on the folding technique is presented which allows us to evaluate the performance of large-scale DTNs. In order to cross-validate the results obtained from the proposed models, we extend the ONE simulator to support our network model. The analytic-numeric results indicate that both models have good accuracy, and the folded model reduces the state space highly, achieving good scalability without any significant loss of accuracy.

An Analytical Model for Rank Distribution in Sparse Network Coding

Random linear network coding is a promising coding scheme to increase the robustness and reliability of network systems. However, one of its major drawbacks is the high computational complexity. Sparse Network Coding (SNC) was proposed to reduce the computational complexity at the expense of larger communication overhead. However, the performance evaluation of SNC is still a major research topic due to an inaccurate expression for the behavior of sparse matrices. In this letter, we present two approximation models to analyze the probability distribution of the rank of sparse matrices. We use our models to derive the average number of required transmissions in the SNC scheme. Our results show that the proposed models predict the rank of sparse matrices and the average number of transmissions with a maximum deviation of 4% and 6%, respectively.

Average Age of Information With Hybrid ARQ Under a Resource Constraint

Scheduling the transmission of status updates over an error-prone communication channel is studied in order to minimize the long-term average age of information at the destination under a constraint on the average number of transmissions at the source node. After each transmission, the source receives an instantaneous ACK/NACK feedback, and decides on the next update without prior knowledge on the success of future transmissions. The optimal scheduling policy is first studied under different feedback mechanisms when the channel statistics are known; in particular, the standard automatic repeat request (ARQ) and hybrid ARQ (HARQ) protocols are considered. The structural results are derived for the optimal policy under HARQ, while the optimal policy is determined analytically for ARQ. For the case of unknown environments, an average-cost reinforcement learning algorithm is proposed that learns the system parameters and the transmission policy in real time. The effectiveness of the proposed methods is verified through the numerical results.

Throughput and Delay Analysis of HARQ With Code Combining Over Double Rayleigh Fading Channels

This paper proposes the use of hybrid automatic repeat request (HARQ) with code combining (HARQ-CC) to offer reliable communications over double Rayleigh channels. The double Rayleigh fading channel is of particular interest to vehicle-to-vehicle communication systems as well as amplify-and-forward relaying and keyhole channels. This paper studies the performance of HARQ-CC over double Rayleigh channels from an information theoretic perspective. Analytical approximations are derived for the $\epsilon$ -outage capacity, the average number of transmissions, and the throughput of HARQ-CC. Moreover, we evaluate the delay experienced by Poisson-arriving packets for HARQ-CC. We provide analytical expressions for the average waiting time, the packets sojourn time, the average consumed power, and the energy efficiency. In our investigation, we take into account the impact of imperfect feedback on different performance metrics. Additionally, we explore the tradeoff between energy efficiency and the throughput. The proposed scheme is shown to maintain the outage probability below a specified threshold $\epsilon$ , which ensures the link reliability. Meanwhile, HARQ-CC adapts implicitly the transmission rate to the channel conditions such that the throughput is maximized. Our results demonstrate that HARQ-CC allows improving the achievable communication rate compared to fixed time diversity schemes. To maximize the throughput of HARQ-CC, the rate per HARQ round should be less than the rate required to meet the outage constraint. Our investigation of the performance of HARQ-CC over Rayleigh and double Rayleigh channels shows that double Rayleigh channels have a higher severity of fading and result in a larger degradation of the throughput. Our analysis reveals that HARQ with incremental redundancy achieves a larger throughput compared to HARQ-CC, whereas HARQ-CC is simpler to implement, has a lower decoding complexity, and requires less memory resources.

A New Adaptive Rate IR-HARQ Combining with AMC

In this paper, we analyze a new cross layer combining scheme of adaptive modulation and coding (AMC) at the physical layer and hybrid automatic repeat request (HARQ) protocol at the data link layer. Our purpose is to improve the performance of the communication system in terms of throughput and errors. We propose a new adaptive HARQ protocol based on the estimated mutual information in addition to signal to noise ratio as channel state information (CSI), which are unavailable at the receiver. Unlike the traditional protocols, the transmitter is aware of the transmission mode only, not the instantaneous CSI, which minimize the load on the feedback channel. The transmission is supposed to be done over block fading channel. Mathematical formulation is improved for the performance criterions, in terms of throughput of the new HARQ, average number of transmissions and the spectral efficiency of the AMC/HARQ. The comparison with the traditional variable rate HARQ shows that our new adaptive HARQ protocol provides an upper bound for the throughput. In addition, the simulation results show that, a small number of transmissions, is enough to reach the maximum spectral efficiency while maintaining the error probabilities under certain acceptable level.

Analysis and Adaptive Design of Polar Coded HARQ Transmission Under SC-List Decoding

A novel polar coded hybrid-ARQ (PC-HARQ) transmission with chase combining utilizing powerful successive cancellation list decoder (HARQ-CC-SCL) is explored. We propose that by applying the distance spectrum of polar code to evaluate its frame error rate, the bounds of throughput and average transmission number can be derived. Then, this letter proposes an adaptive scheme combining the list size-manageable SCL decoding with ARQ protocol. Simulations indicate that the proposed HARQ-CC-SCL obtains a considerable throughput improvement of PC-HARQ-CC system, and approaches those of HARQ schemes with incremental redundancy through less transmission times for each packet. Meanwhile, the adaptive version achieves high throughput and good flexibility in practical applications without significant increase of complexity.

Design of Rate-Compatible Parallel Concatenated Punctured Polar Codes for IR-HARQ Transmission Schemes

In this paper, we propose a rate-compatible (RC) parallel concatenated punctured polar (PCPP) codes for incremental redundancy hybrid automatic repeat request (IR-HARQ) transmission schemes, which can transmit multiple data blocks over a time-varying channel. The PCPP coding scheme can provide RC polar coding blocks in order to adapt to channel variations. First, we investigate an improved random puncturing (IRP) pattern for the PCPP coding scheme due to the code-rate and block length limitations of conventional polar codes. The proposed IRP algorithm only select puncturing bits from the frozen bits set and keep the information bits unchanged during puncturing, which can improve 0.2–1 dB decoding performance more than the existing random puncturing (RP) algorithm. Then, we develop a RC IR-HARQ transmission scheme based on PCPP codes. By analyzing the overhead of the previous successful decoded PCPP coding block in our IR-HARQ scheme, the optimal initial code-rate can be determined for each new PCPP coding block over time-varying channels. Simulation results show that the average number of transmissions is about 1.8 times for each PCPP coding block in our RC IR-HARQ scheme with a 2-level PCPP encoding construction, which can reduce half of the average number of transmissions than the existing RC polar coding schemes.

Ordering for Reduced Transmission Energy Detection in Sensor Networks Testing a Shift in the Mean of a Gaussian Graphical Model

Detection of a shift in the mean of a vector following a decomposable Gaussian graphical model (DGGM) is considered, where each component of the vector is measured at a different sensor in a network. We provide a new method eliminating transmissions normally needed in an optimum clustering approach by using ordered transmissions while achieving the same Bayes risk as the optimum clustering approach. In the new approach, the Bayes optimum test statistic is represented as a sum of local test statistics, where each local test statistic depends only on the observations made at one clique in a generalization of the ordered transmission approach previously suggested for statistically independent observations. Hence, we propose to organize the sensors into clusters based on the clique of the DGGM they belong to, and each cluster selects one sensor to be its cluster head (CH). After collecting and summarizing the observed data at each cluster, the ordered transmission approach is employed over the CHs in an attempt to reduce the number of communications from the CHs to the fusion center where the decision is made. It is shown that the developed approach can guarantee a lower bound on the average number of transmissions saved from the ordered transmission approach for any given DGGM which approaches approximately half the number of cliques when the norm of the mean-shift vector in each clique becomes sufficiently large. In all the cases considered, numerical results imply that a significant portion of the transmissions can be saved, and the developed lower bound is obeyed. The development of the appropriate local processing and the proof of savings are highly nontrivial generalizations of ordering for statistically independent observations and this paper represents the first justification of an ordering approach for cases with statistically dependent observations.

Fundamental Limits of Remote Estimation of Autoregressive Markov Processes Under Communication Constraints

The fundamental limits of remote estimation of autoregressive Markov processes under communication constraints are presented. The remote estimation system consists of a sensor and an estimator. The sensor observes a discrete-time autoregressive Markov process driven by a symmetric and unimodal innovations process. At each time, the sensor either transmits the current state of the Markov process or does not transmit at all. The estimator estimates the Markov process based on the transmitted observations. In such a system, there is a trade-off between communication cost and estimation accuracy. Two fundamental limits of this trade-off are characterized for infinite horizon discounted cost and average cost setups. First, when each transmission is costly, we characterize the minimum achievable cost of communication plus estimation error. Second, when there is a constraint on the average number of transmissions, we characterize the minimum achievable estimation error. Transmission and estimation strategies that achieve these fundamental limits are also identified.

Remote-state estimation with packet drop

Abstract: In the remote estimation system, a transmitter observes a discrete-time symmetric countable state Markov process and decides to either transmit the current state of the Markov process or not transmit. The transmitted packet gets dropped in the communication channel with a probability e. An estimator estimates the Markov process based on the received observations. When each transmission is costly, we characterize the minimum achievable cost of communication plus estimation error. When there is a constraint on the average number of transmissions, we characterize the minimum achievable estimation error. Transmission and estimation strategies that achieve these fundamental limits are also identified.

Analysis of HARQ-IR Over Time-Correlated Rayleigh Fading Channels

In this paper, performance of hybrid automatic repeat request with incremental redundancy (HARQ-IR) over Rayleigh fading channels is investigated. Different from prior analysis, time correlation in the channels is considered. Under time-correlated fading channels, the mutual information in multiple HARQ transmissions is correlated, making the analysis challenging. By using polynomial fitting technique, probability distribution function of the accumulated mutual information is derived. Three meaningful performance metrics including outage probability, average number of transmissions, and long term average throughput (LTAT) are then derived in closed-forms. Moreover, diversity order of HARQ-IR is also investigated. It is proved that full diversity can be achieved by HARQ-IR, i.e., the diversity order is equal to the number of transmissions, even under time-correlated fading channels. These analytical results are verified by simulations and enable the evaluation of the impact of various system parameters on the performance. Particularly, the results unveil the negative impact of time correlation on the outage and throughput performance. The results also show that although more transmissions would improve the outage performance, they may not be beneficial to the LTAT when time correlation is high. Optimal rate design to maximize the LTAT is finally discussed and significant LTAT improvement is demonstrated.

Network Coding-Based Real-Time Retransmission Scheme in Wireless Sensor Networks

In wireless sensor networks (WSNs), wireless links are unreliable and sensor nodes may be in sleep mode. Thus, many applications which require reliable broadcast cannot work properly if they lost some packets. In order to make sure every sensor node in the network receives all packets completely and correctly, retransmission of lost packets is indispensable. Many retransmission methods with network coding have been proposed but they do not catch coding opportunity. In this paper, real-time retransmission algorithm based on network coding (NCRR) is proposed to make the average number of transmissions as less as possible. During the transmission of original packets, we detect whether a certain time slot is suitable for retransmitting a coded packet based on recovery ratio. We analyze the number of transmissions with traditional retransmission and with network coding. Compared with existing approaches, simulation results show that our algorithm can effectively reduce the average number of transmissions and improve the transmission efficiency.

Quick, Decentralized, Energy-Efficient One-Shot Max Function Computation Using Timer-Based Selection

In several wireless sensor networks, it is of interest to determine the maximum of the sensor readings and identify the sensor responsible for it. We propose a novel, decentralized, scalable, energy-efficient, timer-based, one-shot max function computation (TMC) algorithm. In it, the sensor nodes do not transmit their readings in a centrally pre-defined sequence. Instead, the nodes are grouped into clusters, and computation occurs over two contention stages. First, the nodes in each cluster contend with each other using the timer scheme to transmit their reading to their cluster-heads. Thereafter, the cluster-heads use the timer scheme to transmit the highest sensor reading in their cluster to the fusion node. One new challenge is that the use of the timer scheme leads to collisions, which can make the algorithm fail. We optimize the algorithm to minimize the average time required to determine the maximum subject to a constraint on the probability that it fails to find the maximum. TMC significantly lowers average function computation time, average number of transmissions, and average energy consumption compared to approaches proposed in the literature.

Performance and Delay Analysis of Hybrid ARQ With Incremental Redundancy Over Double Rayleigh Fading Channels

In this paper, we study the performance of hybrid automatic repeat request (HARQ) with incremental redundancy over double Rayleigh channels, a common model for the fading amplitude of vehicle-to-vehicle communication systems. We inves- tigate the performance of HARQ from an information theoretic perspective. Analytical expressions are derived for the -outage capacity, the average number of transmissions, and the average transmission rate of HARQ with incremental redundancy assum- ing a maximum number of HARQ rounds. Moreover, we evaluate the delay experienced by Poisson arriving packets for HARQ with incremental redundancy. We provide analytical expressions for the expected waiting time, the packet's sojourn time in the queue, the average consumed power, and the energy efficiency. In our study, the communication rate per HARQ round is adjusted to the average signal-to-noise ratio (SNR) such that a target outage prob- ability is not exceeded. This setting conforms with communication systems in which a quality of service is expected regardless of the channel conditions. Our analysis underscores the importance of HARQ in improving the spectral efficiency and reliability of communication systems. We demonstrate as well that the explored HARQ scheme achieves full diversity. Additionally, we investigate the tradeoff between energy efficiency and spectral efficiency. Index Terms—Hybrid automatic repeat request (HARQ), incre- mental redundancy, energy efficiency, delay analysis, information outage capacity, average transmission rate, average number of transmissions.

On the Performance Analysis of Hybrid ARQ With Incremental Redundancy and With Code Combining Over Free-Space Optical Channels With Pointing Errors

In this paper, we investigate the performance of hybrid automatic repeat request (HARQ) with incremental redundancy (IR) and with code combining (CC) from an information-theoretic perspective over a point-to-point free-space optical (FSO) system. First, we introduce new closed-form expressions for the probability density function, the cumulative distribution function, the moment generating function, and the moments of an FSO link modeled by the Gamma fading channel subject to pointing errors and using intensity modulation with direct detection technique at the receiver. Based on these formulas, we derive exact results for the average bit error rate and the capacity in terms of Meijer's G functions. Moreover, we present asymptotic expressions by utilizing the Meijer's G function expansion and using the moments method, too, for the ergodic capacity approximations. Then, we provide novel analytical expressions for the outage probability, the average number of transmissions, and the average transmission rate for HARQ with IR, assuming a maximum number of rounds for the HARQ protocol. Besides, we offer asymptotic expressions for these results in terms of simple elementary functions. Additionally, we compare the performance of HARQ with IR and HARQ with CC. Our analysis demonstrates that HARQ with IR outperforms HARQ with CC.

On the Performance of Hybrid-ARQ with Incremental Redundancy and with Code Combining over Relay Channels

In this paper, we consider a relay network consisting of a source, a relay, and a destination. The source transmits a message to the destination using hybrid automatic repeat request (HARQ). The relay overhears the transmitted messages over the different HARQ rounds and tries to decode the data packet. In case of successful decoding at the relay, both the relay and the source cooperate to transmit the message to the destination. The channel realizations are independent for different HARQ rounds. We assume that the transmitter has no channel state information (CSI). Under such conditions, power and rate adaptation are not possible. To overcome this problem, HARQ allows the implicit adaptation of the transmission rate to the channel conditions by the use of feedback. There are two major HARQ techniques, namely HARQ with incremental redundancy (IR) and HARQ with code combining (CC). We investigate the performance of HARQ-IR and HARQ-CC over a relay channel from an information theoretic perspective. Analytical expressions are derived for the information outage probability, the average number of transmissions, and the average transmission rate. We illustrate through our investigation the benefit of relaying. We also compare the performance of HARQ-IR and HARQ-CC and show that HARQ-IR outperforms HARQ-CC.