Power Outage Probability Research Articles

Enhancing longevity: Sustainable channel modeling for wireless-powered implantable BANs

Wireless body area network (WBAN) has revolutionized the healthcare sector by enabling remote monitoring and control of wearable and implantable devices, providing freedom of mobility to patients. However, wireless channel modeling in BAN is a crucial aspect for designing an efficient off-body, on-body and in-body communication. Due to the unique characteristics of the human body, it aims to characterize the signal propagation through skin, tissues, internal organs and biological fluids of a patient’s body. Moreover, it is important to enhance the battery life of the low-powered devices for a sustainable BAN. In this work, we provide a hybrid communication channel model for wireless power transfer in a BAN including both off-body and in-body communication channels. An indoor room scenario is considered in which a movable patient having an implant inside its body is present along with an RF power source (for example, a Wi-Fi access point) situated in a ceiling corner. Implant is assumed to inhibit energy harvesting capability. For practicability, we have considered the effect of path loss, partition walls, floor attenuation factor along with other important body parameters. Specifically, we aim to statistically characterize this hybrid communication system, for which unique closed-form expressions of the probability distribution functions of the received power have been derived, thereby first calculating the instantaneous power at different layers of human body and then obtaining the closed-form expression for average received power. All the derived mathematical expressions have been verified via numerical simulations. Further, for elongating the lifespan of implants, we investigated the average power harvested by an implant and its power outage probability for analyzing the sustainability of implants. The results are numerically validated, considering different types of indoor room scenarios, in addition to providing key design insights.

Numerical Solution of Reliability Index based on Performance Evaluation for Yola Electrical Distribution Company

A steady power system in the power sector is a way of meeting the energy demand of customers, to achieve this; there is a need to measure the level of interruption which contributes greatly to unreliability that faltered the business of the power industry. The effect of the interruption associated with the university, Bulumkutu, and Water treatment board of Yerwa Business Unit Distribution Maiduguri, Borno State said to affect likely most businesses situated in the aforementioned locations led to a reduction in economic viability and waste of billions of Naira. In this study, we made use of reliability indices to obtain its numerical solution based on the Institution of Electrical and Electronic Engineer (IEEE), to determine the level to which the performance of the system can serve and maintain the continuity of distribution of electrical energy to customers. The numerical results show that customers connected to Bulumkutu had the highest probability of power outage while the University and water treatment board had the lowest power outage. This clearly shows that the Bulumkutu energy distribution network is unreliable. This implies that Yerwa Business Unit distribution needs to improve operations and maintenance to meet the energy demand of the aforementioned locations.

Design, dynamic simulation, and optimal size selection of a hybrid solar/wind and battery-based system for off-grid energy supply

Remote energy systems are applicable, especially in critical circumstances like earthquakes, floods, etc. Besides, renewable energy systems are suitable energy sources in remote areas. Therefore, Due to high solar and wind potential and its location as an earthquake-prone, a solar-wind energy system for a remote application on a Conex is presented in this study. Considered wind turbines have power production of 1 kW and 3 kW. PV panels have an efficiency of about 20%. This Conex has 12 m2 of the area and resides three to five people and supplies 520 W power consumption of equipment except for the HVAC unit. A considered lifetime of the Conex is 20 years. The considered capacity of batteries is about 100–200 Ah. Six cities are selected as representatives of the six major climate types in Iran. The studied system is optimized for each city. The heating and cooling demand of Conex in cities are specified using TRNSYS software. The heat pump's electricity requirement as a cooling and heating unit with COP of four, lighting (20 W), laptops (140 W), and refrigerators (360 W) is calculated for Conex in each city. Mixed-integer linear programming is employed to optimize an off-grid renewable energy system to supply this electricity demand. The system's total cost, which includes the initial and O&M cost of PV panels and wind turbines, and the capital and replacement cost of the batteries together with the loss of power supply probability during a year, are considered two objective functions. The interest rate is assumed to be 15%. Achieved results show that Iran's solar and wind potential can balance the required load of the Conex with a probability of power outage as low as 1% of a year. However, there is a variance in the cost of the required renewable energy system for supplying Conex power consumption for different climate zones: in the Mediterranean region, the system costs 500–5000 $ as the most expensive one, and in the hot coastal dry region, it costs 900 $-2000 $ as the most cost-efficient region. Finally, results show that wind turbines can be cost-effective energy suppliers for most considered climates, especially considering O&M costs. This study can fill the gap of requiring off-grid temporary portable residences in different climates after disasters, which destroy buildings. Therefore, the lack of these temporary residences can be supplied without adding greenhouse gases to the environment, which reduces greenhouse emissions and electrical grid dependence of the building sector.

An optimized power allocation algorithm for cognitive radio NOMA communication

The primary objective of cognitive radio network is to effectively utilize the unused spectrum bands. In cognitive radio networks, spectrum sharing between primary and secondary users is accomplished using either underlay or interweave cognitive radio approach. Non orthogonal multiple access (NOMA) is the proven technology in the present wireless developments, which allows the coexistence of multiple users in the same orthogonal block. The new paradigm cognitive radio NOMA (CR-NOMA) is one of the potential solutions to fulfill the demands of future wireless communication. This paper emphasizes on practical implementation of NOMA in cognitive radio networks to enhance the spectral efficiency. The goal is to increase the throughput of the secondary users satisfying the quality of service (QOS) requirements of primary users. To achieve this, we have presented the optimized power allocation strategy for underlay downlink scenario to support the simultaneous transmission of primary and secondary users. Furthermore, we have proposed QOS based power allocation scheme for CR-NOMA interweave model to support the coexistence of multiple secondary networks. Also, the changes adopted in implementing superposition coding (SC) and successive interference cancellation (SIC) for CR-NOMA are highlighted. Finally, simulation results validate the mathematical expressions that are derived for power allocation coefficient and outage probability.

Uplink Power Allocation for Throughput and Energy Efficiency Over Nakagami-m Fading Channels

In this article, power allocation in cellular networks considering Nakagami- m fading is proposed. The objective is to optimize the network energy efficiency and throughput subject to user outage probability constraints. The moment generating function (MGF) is used to derive the exact outage probability over Nakagami- m fading channels. Further, tight upper and lower bounds on the outage probability are derived using the Weierstrass, Bernoulli and exponential inequalities. These bounds are used to characterize the relationship between outage probability and normalized signal to interference plus noise ratio (SINR) in Nakagami- m fading. Power allocation algorithms for throughput maximization and energy efficiency are proposed. The throughput maximization problem has a logarithmic form so a differential method is used to solve this problem. The proposed energy efficiency problem has a nonconvex fractional program form so a parametric transformation is used to convert it to a subtractive optimization problem which can be solved iteratively. Simulation results are presented which show that the proposed schemes provide better performance than existing methods in terms of power consumption, throughput, energy efficiency and outage probability.

Throughput and Outage Probability Analysis for Cognitive Radio-Non-Orthogonal Multiple Access in Uplink and Downlink Scenarios

Non orthogonal multiple access (NOMA) in cognitive radio (CR) network has been recognized as potential solution to support the simultaneous transmission of both primary and secondary users. In addition, CR-NOMA can also be used to serve multiple secondary networks in overlay cognitive radio networks. The aim of our work is to increase the secondary user’s throughput without compromising in QoS requirements of the primary users. Our presented work analyses the performance of power domain NOMA in cognitive radio networks for both uplink and downlink scenarios. The primary aspect of the work is to investigate the impact of power allocation on spectrum efficiency and fairness performance of CR-NOMA. Objective function is to maximize the overall throughput under the QOS constraints of the users. We have derived closed form expressions for optimized power allocation coefficient(α) for CR-NOMA uplink and downlink communications. Parameters causing the channel outage, have been examined and conditions for outage probability is derived for CR-NOMA communication. Finally, we have presented the simulation results to validate the mathematical models that are developed for power allocation coefficient and outage probability.

Outage Probability and Normalized SINR-Based Power Allocation over Rician Fading Channels

This paper considers power allocation in cellular networks over Rician fading channels. The goal is to improve the power consumption and energy efficiency as well as satisfy as many users as possible subject to user outage probability and normalized signal to interference plus noise ratio (SINR) constraints. The exact outage probability over Rician fading channels is determined using the moment-generating function (MGF). Further, upper and lower bounds on the outage probability are derived. These are used to characterize the relationship between outage probability and normalized SINR in Rician fading channels. Power allocation algorithms for power minimization and energy efficiency are proposed. Simulation results are presented to compare the performance of the proposed schemes with existing methods in terms of power consumption, throughput, energy efficiency, outage probability, and number of unsatisfied users.

Zero-Forcing Oriented Power Minimization for Multi-Cell MISO-NOMA Systems: A Joint User Grouping, Beamforming, and Power Control Perspective

Future wireless communication systems have been imposed high requirement on power efficiency for operator's profitability as well as to alleviate information and communication technology (ICT) global carbon emission. To meet these challenges, the power consumption minimization problem for a generic multi-cell multiple input and single output non-orthogonal multiple access (MISO-NOMA) system is studied in this work. The associated joint user grouping, beamforming (BF) and power control problem is a mixed integer non-convex programming problem, which is tackled by an iterative distributed methodology. Towards this end, the near-optimal zero-forcing (ZF) BF is leveraged, wherein the semiorthogonal user selection (SUS) strategy is applied to select BF users. Based on these, the BF vectors and BF users are determined for each cell using only local information. Then, two distributed user grouping strategies are proposed. The first one, called channel condition based user clustering (CCUC), performs user grouping in each cell based on the channel conditions. This is conducted independently of the power control part and has low computational complexity. Another algorithm, called power consumption based user clustering (PCUC), uses both the channel conditions and inter-cell interference information to minimize each cell's power consumption. In contrary to CCUC, PCUC is optimized jointly with the power control. Finally, with the obtained user grouping and BF vectors, the resultant power allocation problem is optimally solved via an iterative algorithm, whose convergence is mathematically proven given that the problem is feasible. We perform Monte-Carlo simulation and numerical results show that the proposed resource management methods outperform various conventional MISO schemes and the non-clustered MISO-NOMA strategy in several aspects, including power consumption, outage probability, energy efficiency, and connectivity efficiency.

Hybrid Precoding for an Adaptive Interference Decoding SWIPT System With Full-Duplex IoT Devices

In this article, a simultaneous wireless information and power transfer (SWIPT) system with full-duplex (FD) Internet of Things (IoT) nodes is considered and investigated. We induce the adaptive interference decoding (AID) strategy as well as the switch and inverter structure with antenna selection (SIAS)-based hybrid precoding scheme to the SWIPT system. A joint optimization of hybrid precoder, decoding rule, and power splitting (PS) ratio problem is formulated to minimize the total transmission power, while satisfying the data rate and harvested energy constraints. As it is a nonconvex problem, we propose a suboptimal solution with three stages. In the first stage, a search algorithm which can reduce the complexity of exhaustive search is proposed to decide the sending mode of each node. In the second stage, we utilize the semidefinite relaxation (SDR) approach to find the optimal digital precoder and PS ratios. In the last stage, we propose an alternate minimization algorithm to obtain the hybrid precoding vectors. The simulation results show that our proposed suboptimal solutions can achieve a better performance in terms of power consumption and outage probability compared with those for treating interference as noise (IAN) systems and the digital precoding schemes. Both AID strategy and SIAS-based hybrid precoding are beneficial to the FD SWIPT system. Moreover, the self-interference causes little effect on the system performance as long as it can be eliminated up to 30 dB, which can be easily achieved by the antenna separation technique.

Simultaneous Wireless Information and Power Transfer for Dynamic Cooperative Spectrum Sharing Networks

In this paper, we provide a comprehensive performance analysis of simultaneous wireless information and power transfer (SWIPT) for cognitive relay networks with different relay schemes. In the considered system, the energy-constrained secondary transmitter harvests the energy from the primary signal and then employs the harvested energy to forward the primary signal along with the secondary signal simultaneously. To improve the spectral efficiency, we propose a novel cooperative spectrum sharing protocol with dynamic time-slot allocation based on energy harvesting, namely, dynamic time-power-based cooperative spectrum sharing protocol. Considering the delay-limited transmission mode, we analytically derive the exact closed-form expressions of outage probabilities and achievable throughput for both the primary and secondary networks with amplify-and-forward and decode-and-forward relaying schemes, respectively. More importantly, different from the existing works, we take into account the power outage probability at the energy-constrained secondary transmitter to better match the reality. Finally, the numerical results are provided to evaluate the effect of different key parameters on the system performance, which demonstrate that the dynamic cooperative spectrum sharing protocol improves the outage performance compared with the uniform time-slot allocation scheme.

Self-organized Critical Characteristics Analysis Based on Complex Network Theory

The distribution of line load rate and the node's inhomogeneity to withstand the transmission of power will have an important impact on the self-organized critical state of the system. For the characteristic of load rate distribution of transmission lines, an improved average semi-variance index is used to characterize changes in the self-organized critical state of the power system. Simulation calculations show that under the same nodal power flow distribution, the larger the value of the average semi-variance, the higher the probability of a large-scale power outage. The curve of probability distribution of blackouts obtained by simulation shows that with the increase of variance value, the tail gradually rises, and the system tends to evolve in the self-organized critical state. The improvement of the average semi-variance index has a good identification effect on the system state after the cascading failure.

Energy-Efficient Secure Transmission for Wireless Powered Internet of Things With Multiple Power Beacons

In this paper, we investigate the energy-efficient secure uplink transmission for the wireless powered Internet of Things (IoT), where one energy-constrained source and multiple energy-constrained relays harvest energy from multiple power beacons (PBs) in the presence of a passive eavesdropper. To perform energy-efficient secure communications, we consider three relay selection schemes with the best PB selected by the source, i.e., the best relay is selected randomly, the best relay is selected by the source, and the best relay is selected by the best PB (BRBP), respectively. For each scheme, the exact closed-form expressions of power outage probability (POP), secrecy outage probability (SOP), and secure energy efficiency (SEE) are derived over the Rayleigh fading channel. Furthermore, we formulate the SEE maximization problem under the transmit power constraint to optimize the transmit power in PBs and the time-switching factor. Considering the resource limitation for IoT devices, we adopt a low-complexity Dinkelbach algorithm combined with Brent’s method to solve this multi-parameter fractional optimization problem. Simulation results demonstrate that the BRBP scheme achieves the best SOP performance and either increasing the number of PBs or decreasing the threshold of POP can significantly improve the SEE of the considered system.

Power Allocation and Outage Probability Analysis for SDN-based Radio Access Networks

In this paper, performance of Access network Architecture based SDN (Software Defined Network) is analyzed with respect to the power allocation issue. A power allocation scheme PSO-PA (Particle Swarm Optimization-power allocation) algorithm is proposed, the proposed scheme is subjected to constant total power with the objective of minimizing system outage probability. The entire access network resource configuration is controlled by the SDN controller, then it sends the optimized power distribution factor to the base station source node (SN) and the relay node (RN). Simulation results show that the proposed scheme reduces the system outage probability at a low complexity.

Prioritizing Data/Energy Thresholding-Based Antenna Switching for SWIPT-Enabled Secondary Receiver in Cognitive Radio Networks

Simultaneous wireless power and information transfer is considered in cognitive radio networks with a multi-antenna energy harvesting (EH) secondary receiver (SR). The SR harvests the energy from the secondary transmitter and primary transmitter. The SR uses the antenna switching (AS) technique which selects a subset of antennas to decode the information [namely, the information decoding (ID) antennas] and the rest to harvest the energy (namely the EH antennas). The AS technique is performed via a thresholding-based strategy inspired from the maximum ratio combining technique with an output threshold which is proposed in two ways: 1) the prioritizing data selection (PDS) scheme and 2) the prioritizing energy selection (PES) scheme. For both schemes, we study the expressions and the asymptotic results of the probability mass function of the selected ID antennas, the average harvested energy, the power outage probability, and the data outage probability. We deduce the performance of the joint PDS and PES scheme. We evaluate all performance metrics for the Rayleigh and Nakagami fading channels. Through the simulation results, we show the impact of different simulation parameters on the performance metrics. We also show that there is a tradeoff between the data and energy performance metrics.

Distributed Power Control for the Downlink of Multi-Cell NOMA Systems

This paper investigates the power control problem for the downlink of a multi-cell non-orthogonal multiple access system. The problem, called P-OPT, aims to minimize the total transmit power of all the base stations subject to the data rate requirements of the users. The feasibility and optimality properties of P-OPT are characterized through a related optimization problem, called Q-OPT, which is constituted by some relevant power control subproblems. First, we characterize the feasibility of Q-OPT and prove the uniqueness of its optimal solution. Next, we prove that the feasibility of P-OPT can be characterized by the Perron-Frobenius eigenvalues of the matrices arising from the power control subproblems. Subsequently, the relationship between the optimal solutions to P-OPT and that to Q-OPT is presented, which motivates us to obtain the optimal solution to P-OPT through solving the corresponding Q-OPT. Furthermore, a distributed algorithm to solve Q-OPT is designed, and the underlying iteration is shown to be a standard interference function. According to Yates’s power control framework, the algorithm always converges to the optimal solution if exists. Numerical results validate the convergence of the distributed algorithm and quantify the improvement of our proposed method over fractional transmit power control and orthogonal multiple access schemes in terms of power consumption and outage probability.

Resource Allocation and Outage Analysis for an Adaptive Cognitive Two-Way Relay Network

In this paper, an adaptive two-way relay cooperation scheme is studied for multiple-relay cognitive radio networks to improve the performance of secondary transmissions. The power allocation and relay selection schemes are derived to minimize the secondary outage probability where only statistical channel information is needed. Exact closed-form expressions for secondary outage probability are derived under a constraint on the quality of service of primary transmissions in terms of the required primary outage probability. To better understand the impact of primary user interference on secondary transmissions, we further investigate the asymptotic behaviors of the secondary relay network including power allocation and outage probability, when the primary signal-to-noise ratio goes to infinity. Simulation results are provided to illustrate the performance of the proposed schemes.

Modeling and analysis of simultaneous information and energy transfer in Internet of Things

AbstractThe Internet of Things (IoT) will allow unprecedented connectivity among devices and is predicted to make our world smarter. However, due to battery constraints, energy efficiency of IoT with numerous smart devices is a key challenge. Simultaneous information and energy transfer (SIET) is a promising method to provide green energy for energy‐constrained wireless networks. This paper, for the first time, investigates the modeling and analysis of SIET in a network where IoT nodes are powered via IoT gateways. Specifically, a Ginibre point process that captures the repulsion between spatially distributed nodes is used to model the IoT gateway network. The goal of our work is to uncover a strategy to balance the trade‐off between power outage probability and transmission outage probability by a careful design of the power split ratio of SIET. To achieve that, we derive closed‐form expressions for these 2 probabilities in IoT for a practical case. The simulation results verify our theoretical results and illustrate the effects of different network parameters (eg, transmit power and density of gateways and signal‐to‐interference‐plus‐noise ratio threshold) on SIET.

Power-Availability-Aware Cell Association for Energy-Harvesting Small-Cell Base Stations

Energy harvesting brings a key solution to the increasing energy bill and environmental concerns but, at the same time, potential energy shortage may deteriorate the network availability. In this paper, we analyze the performance of off-grid small-cell base stations (scBS) with finite battery capacity and design a new power-availability-aware cell association based on periodical broadcast of the scBS battery level. Each mobile terminal (MT) targets its own set of available scBSs before association, i.e., the set of scBSs that can guarantee service provided 1) the scBS battery level; 2) the power required to satisfy a received power constraint at each MT, given the scBS-MT distance and the shadowing attenuation; and 3) the estimated power consumed to serve other MTs potentially associated to the same scBS, which is computed using stochastic geometry tools. Next, we develop for it a tractable performance analysis and derive closed-form expressions for the probability of power outage and the coverage probability. By dynamically adapting to the fluctuations of the base station battery and the MT received power requirement, the proposed cell association allows a more even distribution of the available energy in the network, brings robustness against harvesting impairment and thereby, significantly outperforms conventional strategies.

Wireless Powered Cognitive Radio Networks With Compressive Sensing and Matrix Completion

In this paper, we consider cognitive radio networks in which energy constrained secondary users (SUs) can harvest energy from the randomly deployed power beacons. A new frame structure is proposed for the considered networks. In the considered network, a wireless power transfer model is proposed, and the closed-form expressions for the power outage probability are derived. In addition, in order to reduce the energy consumption at SUs, sub-Nyquist sampling are performed at SUs. Subsequently, compressive sensing and matrix completion techniques are invoked to recover the original signals at the fusion center by utilizing the sparsity property of spectral signals. Throughput optimizations of the secondary networks are formulated into two linear constrained problems, which aim to maximize the throughput of a single SU and the whole cooperative network, respectively. Three methods are provided to obtain the maximal throughput of secondary networks by optimizing the time slots allocation and the transmit power. Simulation results show that the maximum throughput can be improved by implementing compressive spectrum sensing in the proposed frame structure design.

Energy Harvesting-Based D2D Communications in the Presence of Interference and Ambient RF Sources

This paper considers a device-to-device (D2D) network with time-splitting protocol, where a D2D transmitter ( $ \text {T}_{\text {x}}$ ) first harvests energy from a multiple-antenna power beacon (PB) and ambient radio frequency sources, and then uses that harvested energy to transmit data to the D2D receiver ( $ \text {R}_{\text {x}}$ ). To improve the energy transfer efficiency, the PB is equipped with multiple antennas for energy transfer, and $ \text {T}_{\text {x}}$ is equipped with multiple antennas for energy harvesting. Two beamforming techniques, called best antenna-based beamforming and optimal beamforming vector, are proposed to use at the PB. We derive novel analytical expressions for the average harvested energy, power outage probability, and the outage probability of the information transfer link, considering the effect of co-channel interference from homogeneous Poison distributed interferes and the short-range propagation model for the path loss. We show that by deploying multiple harvesting energy antennas at $ \text {T}_{\text {x}}$ and by implementing optimal beamforming vector scheme at the PB, the system performance improves substantially. Furthermore, Monte-Carlo simulations are provided and verify the accuracy of our analytical results.