Transmission Outage Research Articles

Transmission Outage Cost Analysis Using Value of Loss Load Approach Based on Macro Economic Data

The West Nusa Tenggara (NTB) electricity system, which consists of the Lombok System and the Sumbawa-Bima System, has an important role in supporting the country's economy, especially in the tourism segment. Quantitatively, there has been no measurement of the impact of electricity disruption on the macro economy. Value of Loss Load (VoLL) is a useful quantity parameter in the economic evaluation of electric power systems. It can be represented as the value of losses borne by customers in case of electricity service interruptions. For policy makers and electricity management, the size of the VoLL would affect decisions regarding investment. A low VoLL requires for a low reliability level and a high VoLL for a high reliability level. This research will calculate Transmission outage costs using the Value of Loss Load approach based on macro economic data and predicting VoLL 2024 - 2030. The outcome of the research shows that The Lombok System VoLL is lower than Bima – Sumbawa System. Outage costs due to disruptions on the Transmission System side affect GDP by 0.001% / year. The trend of VoLL 2024 – 2030 is estimated to decrease by an average of 2.29% / year which is indicate it is is inline with Rencana Usaha Penyediaan Tenaga Listrik 2021 - 2030.

An Efficient Block Successive Upper-Bound Minimization Algorithm for Caching a Reconfigurable Intelligent Surface-Assisted Downlink Non-Orthogonal Multiple Access System

With the booming rollout of 5G communication, abundant new technologies have been proposed for quality of service requirements. In terms of the betterment in transmission coverage, mobile edge caching (MEC) has shown potential in reducing the transmission outage. The performance of MEC, meanwhile, can be promisingly enhanced by reconfigurable intelligent surfaces (RIS). Under this context, we explore a system comprising a small base-station (SBS) with limited cache capacity, two users, and one RIS. The SBS transmits the contents from the cache or fetches them from the remote backhaul hub to communicate with users through directional and possibly reflective channels. In this point-to-multipoint connection, non-orthogonal multiple access (NOMA) is applied, improving the capacity of the system. To minimize the outage probability, we first propose a caching policy from entropy perspective, based on which we investigate the beamforming and power allocation problem. The issue, however, is non-convex and involves multi-dimensional optimization. To address this, we introduce an efficient block successive upper-bound minimization algorithm, grounded in Gershgorin’s circle theorem. This algorithm aims to find the globally optimal solution for power allocation and RIS beamformer, considering both the channel condition and content popularity. Numerical studies are performed to verify the effectiveness of the proposed algorithm.

Free-Space Optical (FSO) Satellite Networks Performance Analysis: Transmission Power, Latency, and Outage Probability

Free-Space Optical (FSO) Satellite Networks Performance Analysis: Transmission Power, Latency, and Outage Probability

A Comprehensive Reliability Strategy for Managing Assets of Redundant Customer Delivery Systems

A reliability strategy was developed in 2020 for the purpose of improving the reliability of the dual element spot network (DESN) stations. The strategy utilized the transmission outage data system (TODS) data-base and some reliability models to identify DESN stations with the worst reliability performance so that investment dollars can be directed towards the reliability improvement of those stations. Recently, a comprehensive reliability strategy has been developed to do a similar task of improving the overall reliability of the DESN stations. The new strategy first maps the delivery point interruption data to the TODS outage data to determine the frequencies of the main causes of supply interruptions to delivery points. Then, it identifies action plans (or remedial actions) that are needed in order to reduce the frequencies of the dominant outage causes. Finally, the strategy uses a benefit/cost analysis to select the preferred action plans in order to improve the overall reliability of the DESN stations. The new strategy is more practical and has numerous advantages over the existing one. The purpose of this paper is to describe the new reliability strategy, its advantages over the existing one and to show how to apply it in the DESN stations.

Outage Probability Analysis of Multi-hop Relay Aided IoT Networks

This study delves into Internet of Things (IoT) networks wherein a transmitting source communicates information to a designated recipient. The presence of signal attenuation challenges the direct transmission of information from the source to the recipient. To surmount this obstacle, we investigate IoT network communication facilitated by multi-hop relays, whereby multiple relays collaboratively enable the conveyance of data from the source to the recipient across intermediate stages. For the considered IoT networks augmented by multi-hop relays, we assess the performance of the system by analyzing the probability of transmission outage. This analysis entails the derivation of an analytical expression for evaluating the occurrence of IoT network outage. Additionally, we gauge the system's effectiveness by examining the attainable transmission rate, wherein an analytical expression is furnished to assess the IoT data rate. The empirical results, along with the analytical findings, are subsequently presented to validate the formulated expressions in the context of IoT networks empowered by multi-hop relays. Notably, the utilization of multi-hop relaying emerges as a efficacious strategy for substantially expanding the coverage scope of IoT networks.

Cache‐aided UAV‐assisted relaying networks: Performance analysis and system optimization

AbstractThe utilization of distributed multi‐agent unmanned aerial vehicles (UAVs) for computing tasks in remote areas has gained significant traction in recent years due to their adaptability and capability to access hard‐to‐reach regions that are inaccessible to ground‐based methods. However, establishing wireless communication between UAVs and ground‐based data sources in remote areas presents considerable challenges, particularly when UAVs are in motion. To tackle this challenge, this article investigates a cache‐aided relaying system in the presence of UAVs, wherein a ground‐based decode‐and‐forward relay equipped with cache space is deployed to facilitate wireless communication between UAVs and a central data source. Within the scope of this system, we first analyze the probability of transmission outage, providing an analytical expression for performance evaluation. We commence with the case of a single stationary UAV, subsequently expanding to multiple stationary UAVs, and ultimately incorporating multiple dynamic UAVs. Subsequently, we enhance the system performance by minimizing the outage probability through efficient power resource allocation among users. By means of mathematical modeling and simulations, this research examines the influence of various factors, including the cache size at the relay and the working mode of the UAV, on the system performance. Finally, simulations are conducted to validate the proposed analysis.

Covert Rate Study for Full-Duplex D2D Communications Underlaid Cellular Networks

Device-to-device (D2D) communications underlaid cellular networks have emerged as a promising network architecture to provide extended coverage and high data rate for various Internet of Things (IoT) applications. However, because of the inherent openness and broadcasting nature of wireless communications, such networks face severe risks of data privacy disclosure. This paper investigates the covert communications in such networks for providing enhanced privacy protection. Specifically, this paper explores the critical covert rate performance in a full-duplex D2D communication underlaid cellular network consisting of a base station, a cellular user, a D2D pair with a transmitter and a full-duplex receiver, and a warden, where the D2D receiver can operate over either the full-duplex (FD) mode or the half-duplex (HD) mode. We first derive transmission outage probabilities of cellular and D2D links under the FD and HD modes, respectively. Based on these probabilities, we further provide theoretical modelling for the covert rate under each mode and explore the corresponding covert rate maximization by jointly optimizing the transmit powers of the D2D pair and the cellular user. To improve the covert rate performance, we propose a general mode in which the D2D receiver can flexibly switch between these two modes. Under the general mode, we also investigate the theoretical modelling and maximization problems of covert rate. Finally, we present extensive numerical results to illustrate the covert rate performances under the FD, HD, and general modes.

Energy-efficient power control strategy of the delay tolerable service based on the reinforcement learning

In recent years, the rapid development of Internet technology and its applications has led to an exponential growth in the number of Internet users and wireless terminal devices, resulting in a corresponding increase in energy consumption. This has necessitated the need to reduce energy consumption while maintaining the quality of communication services. To this end, we investigate the possibility of improving energy efficiency (EE) of delay tolerable (DT) services by allocating resources based on the time-domain water-filling algorithm. We first transform the non-convex problem of maximizing EE into a convex problem of minimizing transmission power to obtain the optimal solution, and then use the greedy algorithm to obtain an upper bound. Furthermore, to capture a more realistic scenario, an Approximate Statistical Dynamic Programming (ASDP) algorithm is introduced, but its effect on enhancing EE is limited. To overcome this limitation, three Deep Reinforcement Learning (DRL) algorithms are implemented. The simulations results show that the settings of maximum transmit power and SNR during agent training have an impact on the performance of the agent. Finally, by comparing the mean values of transmission power, outage probability, equilibrium power and performance improvement percentage of several algorithms, we conclude that the Deep Deterministic Policy Gradient (DDPG) algorithm produces the best agent performance in the environment with a fixed SNR of 2 (dB).

Joint selection of FD/HD and AF/DF for covert communication in two-hop relay systems

This paper focuses on the covert communication in a two-hop relay system consisting of a transmitter, a relay, a receiver and a warden, where the relay can flexibly select between the transmission modes of full-duplex (FD)/half-duplex (HD) as well as between the forwarding modes of amplify-and-forward (AF)/decode-and-forward (DF). For a given combination of transmission mode and forwarding mode, we first provide theoretical modeling for the covert outage probability, transmission outage probability and covert rate. Under such a combination, we then explore the optimal designs of the transmitter transmission rate and the relay transmit power for covert rate maximization, subjecting to the constraints of covert outage probability and upper bound on relay transmit power. Finally, we provide extensive numerical results to illustrate the performance comparison among different combinations of transmission mode and forwarding mode, and how to jointly select a proper combination of transmission mode and forwarding mode to achieve the maximum covert rate in a relay system with given settings of transmitter transmission rate, self-interference coefficient of FD, constraints of covert outage probability, and upper bound on relay transmit power.

Energy-Efficient Covert Wireless Communication Through Probabilistic Jamming

In this work, we propose a novel energy-efficient covert wireless communication scheme through probabilistic jamming, where a jammer probabilistically transmits artificial noise (AN) with variable power against a warden’s detection. For the proposed scheme, the closed-form expressions for the warden’s detection error probability, the transmission outage probability, and the system energy efficiency are derived to reveal the impacts of the prior AN transmission probability on communication covertness, reliability, and system energy efficiency. To further improve the system energy efficiency, an optimization problem is formulated to determine the optimal prior AN transmission probability and the optimal transmit power of private information subject to a covertness constraint, which shows that continuous jamming is generally not optimal to maximize the energy efficiency in covert communication systems. Simulation results verify our analysis and show the superiority of proposed scheme comparing to a widely adopted scheme where the jammer always transmits AN with random transmit power.

Continuous Operation of Wind Power Plants Under Pole-to-Ground Fault in an HVDC System Consisting of Half-Bridge MMCs and Disconnecting Switches

This article focuses on a multicircuit HVDC system which can localize the dc line fault without dc circuit breakers. The conventional fault clearing method causes the shutdown and the restart of the wind power plants, which results in the suspension of the power supply. The suspension may affect the balance of supply and demand, and may cause frequency drop in the onshore ac power system. To solve the problem, this article proposes a system switching method to enable the continuous operation of the wind power plants under the dc line fault. The proposed method utilizes the half-bridge modular multilevel converter to clear the fault while keeping the wind power plants operating. As a result, the proposed method realizes the continuous operation of wind power plants and shorten the transmission outage to 0.2 s. Thus, it greatly increases the supply reliability. Experimental results demonstrate the validity of the proposed method.

Machine learning evaluation of storm-related transmission outage factors and risk

This paper develops several machine learning models to evaluate the significance and correlation between variables related to vegetation, weather, infrastructure, the physical environment and storm-related outages in transmission networks, and acts as a proof of concept for machine learning to improve outage risk forecasting. The analysis covers the Eversource Energy transmission network territories in Connecticut, Western Massachusetts and New Hampshire. Random forest models are trained on 44 storms between May 2015 and December 2020, with 111 sustained outages incurred in total. Variable importance is performed to determine and remove insignificant variables, and for those remaining variables the correlations with transmission outages are plotted using partial dependence plots. The risk forecasting results more than doubled the number of transmission lines with outages classified in the top 20% of risk-score predictions for the best machine learning model relative to a baseline risk sorting algorithm, from 25 to 51. The variable importance and partial dependence plots demonstrate infrastructure related variables are significant predictors of transmission outage risk, with a magnitude of influence on outage levels on the same scale as significant vegetation and weather-related predictors.

Partial Relay Selection for Covert Communication in Two-Hop Relay Systems

This paper investigates the impact of relay selection on covert communication performance in a two-hop wireless relay system, where a transmitter intends to transmit messages to a receiver via a selected relay, subjecting to detection from a warden. To this end, we first propose a partial relay selection scheme based on the signal-to-interference-plus-noise-ratio (SINR) at the relay. We then provide theoretical models for the detection error probability, transmission outage probability, and covert rate. We further explore the optimal designs of the transmit power and target transmission rate for the covert rate, subjecting to the constraints of covertness and the upper bound of transmit power. Finally, we provide extensive numerical results to illustrate the covert rate performance via the partial relay selection scheme in a two-hop relay system.

When the User-Centric Network Meets Mobile Edge Computing: Challenges and Optimization

As an emergent computing paradigm, mobile edge computing (MEC) can provide users with strong computing, storage, and communication services by moving the server to the user side. In recent years, applications such as virtual reality and augmented reality have brought higher requirements on transmission and computing capabilities. However, in the traditional cellular-based MEC, users at the edge of the cell will suffer severe signal attenuation and inter-cell interference, leading to a great reduction in achievable rate and proneness to transmission outage and offloading failure. To overcome this limitation, we combine the user-centric network (UCN) with MEC computing services and propose a novel framework called user-centric MEC (UCMEC). Through the dense deployment of access points, UCMEC can provide users with efficient, reliable, low-cost user-centric wireless transmission and edge computing services. To further exploit the benefits of UCMEC, we jointly optimize the task partition, transmit power control, and computing resource allocation decision to minimize the total energy consumption under delay constraints. Simulation results show that our proposed optimization scheme can bring users lower energy consumption and delay, and higher successful offloading probability than traditional MEC.

Achieving Near Ideal Covertness in NOMA Systems With Channel Inversion Power Control

In this letter, we propose two resource allocation schemes for covert communication in a downlink NOMA system, where the transmitter can send information simultaneously both to the public and the covert receiver, while maintaining ideal (or near-ideal) covertness with respect to the warden. The covert transmission is concealed by combining NOMA and channel inversion power control, acting as a random source of uncertainty at the warden. The transmission scheme supports zero outage transmission to the public user and non-zero outage transmission to the covert user, while guaranteeing an ideal or near-ideal covertness at the warden, depending on whether the covert user employs single-user decoding or successive interference cancellation (SIC) decoding. In the latter case, we determine the optimal power sharing factor between the public and covert signals that maximizes the average covert throughput, given a predefined fixed transmission rate to the public user. If the channel between the transmitter and the covert receiver is moderate or strong, the SIC decoding, compared to the single-user decoding, leads to much higher covert throughput at the cost of minor degradation of covertness.

Integrated generation-transmission expansion planning considering power system reliability and optimal maintenance activities

This paper evaluates lines repair and maintenance impacts on generation-transmission expansion planning (GTEP), considering the transmission and generation reliability. The objective is to form a balance between the transmission and generation expansion and operational costs and reliability, as well as lines repair and maintenance costs. For this purpose, the transmission system reliability is represented by the value of loss of load (LOL) and load shedding owing to line outages, and generation reliability is formulated by the LOL and load shedding indices because of transmission congestion and outage of generating units. The implementation results of the model on the IEEE RTS show that including line repair and maintenance as well as line loading in GTEP leads to optimal generation and transmission plans and significant savings in expansion and operational costs.

Age-of-Information Minimization in Healthcare IoT Using Distributionally Robust Optimization

In this article, we consider a cellular-based healthcare Internet of Things (IoT) system with imperfect channel state information (CSI), where a healthcare IoT device first receives radio frequency (RF) energy from the small cell base station (SBS) and then transmits physiological status updates to the corresponding SBS as timely as possible. A newly proposed metric, named Age of Information (AoI), will be introduced to characterize the data freshness, which is determined by the status updates generation probability and the information transmission outage probability. To minimize the average AoI, we formulate a distributionally robust optimization problem under an energy harvesting probability (chance) constraint and an information transmission probability constraint. Since the distributionally robust probability constraints are nonconvex, we use the conditional value-at-risk (CVaR)-based method to express constraint specifications related to distributional ambiguity. To tackle the NP-hard problem efficiently, we decompose the AoI minimization problem into two subproblems and propose a low-complexity iterative algorithm to obtain a suboptimal solution. Simulation results show that there exists an AoI-energy tradeoff in the considered healthcare IoT, and the CVaR-based method can achieve a better performance than the nonrobust method.

Performance Analysis of Product Channel for Relaying-Assisted Edge Computing in IoT Networks

In this paper, we analyze the typical product channel which is often encountered in wireless relaying channels, for relaying-assisted edge computing in Internet of Things (IoT) networks. Such analysis is of vital importance, as it is often encountered in wireless transmission. Specifically, we firstly derive a closed-form expression of the transmission outage probability in product channels, through solving involved complicated multivariate integral. We then simplify the expression through some approximation to the involved Bessel function, which can help obtain some meaningful findings to the system design. We finally provide some numerical results to verify that the presented analysis on the production channels is effective.

UAV-Enabled Data Collection for Wireless Sensor Networks With Distributed Beamforming

This paper studies an unmanned aerial vehicle (UAV)-enabled wireless sensor network, in which one UAV flies in the sky to collect the data transmitted from a set of ground nodes (GNs) via distributed beamforming. We consider two scenarios with delay-tolerant and delay-sensitive applications, in which the GNs send the common/shared messages to the UAV via adaptive- and fixed-rate transmissions, respectively. For the two scenarios, we aim to maximize the average data-rate throughput and minimize the transmission outage probability, respectively, by jointly optimizing the UAV’s trajectory design and the GNs’ transmit power allocation over time, subject to the UAV’s flight speed constraints and the GNs’ individual average power constraints. However, the two formulated problems are both non-convex and thus generally difficult to be optimally solved. To tackle this issue, we first consider the relaxed problems in the ideal case with the UAV’s flight speed constraints ignored, for which the well-structured optimal solutions are obtained to reveal the fundamental performance upper bounds. It is shown that for the two approximate problems, the optimal trajectory solutions have the same multi-location-hovering structure, but with different optimal power allocation strategies. Next, for the general problems with the UAV’s flight speed constraints considered, we propose efficient algorithms to obtain high-quality solutions by using the techniques from convex optimization and approximation. Finally, numerical results show that our proposed designs significantly outperform other benchmark schemes, in terms of the achieved data-rate throughput and outage probability under the two scenarios. It is also observed that when the mission period becomes sufficiently long, our proposed designs approach the performance upper bounds when the UAV’s flight speed constraints are ignored.

Covert Communication for Wireless Networks with Full-Duplex Multiantenna Relay

In this work, we investigated a covert communication method in wireless networks, which is realized by multiantenna full-duplex single relay. In the first stage, the source node sends covert messages to the relay, and the relay uses a single antenna to send interference signals to the adversary node to protect the covert information being transmitted. In the second stage, the relay decodes and forwards the covert information received in the first stage; at the same time, the relay uses zero-forcing beamforming to send interference signals to the warden to ensure covert transmission. The detection error rate, transmission outage probability, maximum effective covert rate, and other performance indicators are derived in two stages, and the total performance of the system is derived and analyzed. Then, the performance indicators are verified and analyzed by simulation. Our analysis shows that the maximum effective covert rate of using the characteristics of multiantenna to interfere with Willie in the second stage is taken as the total covert performance of the system, and the transmission interruption probability is significantly less than that of the first stage, so the corresponding maximum effective concealment efficiency will be greater.