Secrecy Outage Probability Minimization in Wireless-Powered Communications Using an Improved Biogeography-Based Optimization-Inspired Recurrent Neural Network

This paper focuses on wireless-powered communication systems,which are increasingly relevant in the Internet of Things(IoT)due to their ability to extend the operational lifetime of devices with limited energy.The main contribution of the paper is a novel approach to minimize the secrecy outage probability(SOP)in these systems.Minimizing SOP is crucial for maintaining the confidentiality and integrity of data,especially in situations where the transmission of sensitive data is critical.Our proposed method harnesses the power of an improved biogeography-based optimization(IBBO)to effectively train a recurrent neural network(RNN).The proposed IBBO introduces an innovative migration model.The core advantage of IBBO lies in its adeptness at maintaining equilibrium between exploration and exploitation.This is accomplished by integrating tactics such as advancing towards a random habitat,adopting the crossover operator from genetic algorithms(GA),and utilizing the global best(Gbest)operator from particle swarm optimization(PSO)into the IBBO framework.The IBBO demonstrates its efficacy by enabling the RNN to optimize the system parameters,resulting in significant outage probability reduction.Through comprehensive simulations,we showcase the superiority of the IBBO-RNN over existing approaches,highlighting its capability to achieve remarkable gains in SOP minimization.This paper compares nine methods for predicting outage probability in wireless-powered communications.The IBBO-RNN achieved the highest accuracy rate of 98.92%,showing a significant performance improvement.In contrast,the standard RNN recorded lower accuracy rates of 91.27%.The IBBO-RNN maintains lower SOP values across the entire signal-to-noise ratio(SNR)spectrum tested,suggesting that the method is highly effective at optimizing system parameters for improved secrecy even at lower SNRs.

Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.

Outage Analysis of Optimal UAV Cooperation with IRS via Energy Harvesting Enhancement Assisted Computational Offloading

The utilization of mobile edge computing(MEC)for unmanned aerial vehicle(UAV)communication presents a viable solution for achieving high reliability and low latency communication.This study explores the potential of employing intelligent reflective surfaces(IRS)andUAVs as relay nodes to efficiently offload user computing tasks to theMEC server system model.Specifically,the user node accesses the primary user spectrum,while adhering to the constraint of satisfying the primary user peak interference power.Furthermore,the UAV acquires energy without interrupting the primary user’s regular communication by employing two energy harvesting schemes,namely time switching(TS)and power splitting(PS).The selection of the optimal UAV is based on the maximization of the instantaneous signal-to-noise ratio.Subsequently,the analytical expression for the outage probability of the system in Rayleigh channels is derived and analyzed.The study investigates the impact of various system parameters,including the number of UAVs,peak interference power,TS,and PS factors,on the system’s outage performance through simulation.The proposed system is also compared to two conventional benchmark schemes:the optimal UAV link transmission and the IRS link transmission.The simulation results validate the theoretical derivation and demonstrate the superiority of the proposed scheme over the benchmark schemes.

Outage Behaviors of Active Intelligent Reflecting Surface Enabled NOMA Communications

Active intelligent reflecting surface(IRS)is a novel and promising technology that is able to overcome the multiplicative fading introduced by passive IRS.In this paper,we consider the application of active IRS to nonorthogonalmultiple access(NOMA)networks,where the incident signals are amplified actively through integrating amplifier to reflecting elements.More specifically,the performance of active/passive IRS-NOMA networks is investigated over large and small-scale fading channels.Aiming to characterize the performance of active IRSNOMA networks,the exact and asymptotic expressions of outage probability for a couple of users,i.e.,near-end user n and far-end user m are derived by exploiting a 1-bit coding scheme.Based on approximated analyses,the diversity orders of user n and user m are obtained for active IRS-NOMA.In addition,the system throughput of active IRS-NOMA is discussed in the delay-sensitive transmission.The simulation results are carried out to verify that:i)The outage behaviors of active IRS-NOMAnetworks are superior to that of passive IRS-NOMAnetworks;ii)As the reflection amplitude factors increase,the active IRS-NOMAnetworks are capable of furnishing the enhanced outage performance;and iii)The active IRS-NOMA has a larger system throughput than passive IRS-NOMA and conventional communications.

System Outage Probability and Diversity Analysis of a SWIPT Based Two-Way DF Relay Network Under Transceiver Hardware Impairments

This paper investigates the system outage performance of a simultaneous wireless information and power transfer(SWIPT)based two-way decodeand-forward(DF)relay network,where potential hardware impairments(HIs)in all transceivers are considered.After harvesting energy and decoding messages simultaneously via a power splitting scheme,the energy-limited relay node forwards the decoded information to both terminals.Each terminal combines the signals from the direct and relaying links via selection combining.We derive the system outage probability under independent but non-identically distributed Nakagami-m fading channels.It reveals an overall system ceiling(OSC)effect,i.e.,the system falls in outage if the target rate exceeds an OSC threshold that is determined by the levels of HIs.Furthermore,we derive the diversity gain of the considered network.The result reveals that when the transmission rate is below the OSC threshold,the achieved diversity gain equals the sum of the shape parameter of the direct link and the smaller shape parameter of the terminalto-relay links;otherwise,the diversity gain is zero.This is different from the amplify-and-forward(AF)strategy,under which the relaying links have no contribution to the diversity gain.Simulation results validate the analytical results and reveal that compared with the AF strategy,the SWIPT based two-way relaying links under the DF strategy are more robust to HIs and achieve a lower system outage probability.

Secrecy Outage Probability for Two-Way Integrated Satellite Unmanned Aerial Vehicle Relay Networks with Hardware Impairments

In this paper,we investigate the secrecy outage performance for the two-way integrated satellite unmanned aerial vehicle relay networks with hardware impairments.Particularly,the closed-form expression for the secrecy outage probability is obtained.Moreover,to get more information on the secrecy outage probability in a high signalto-noise regime,the asymptotic analysis along with the secrecy diversity order and secrecy coding gain for the secrecy outage probability are also further obtained,which presents a fast method to evaluate the impact of system parameters and hardware impairments on the considered network.Finally,Monte Carlo simulation results are provided to show the efficiency of the theoretical analysis.

Outage performance analysis of multiple users in cognitive networks

A cooperative model of multiple primary and secondary users coexisting cognitive network is presented. In this model, the control center is aware of all the users＇ locations in order to allocate the nearest secondary user to the primary user. The control center is aware of the information of the unused spectral resources in terms of the feedback of the sensing results from the secondary users. It allocates idle frequency bands among the secondary users. The primary user accesses the base station （BS） in orthogonal subchannels, and it cooperatively transmits packets with the secondary user and exploits the free band assigned by the control center to amplify-and-forward what it receives immediately. Under this scenario, the outage probability of the cooperative transmission pair of the primary and secondary transmitters is derived. The numerical simulation of the outage probabilities as a function of primary transmission probability ps, power allocation ratio ξ between the primary and secondary users, and the numbers of the primary and secondary users are given respectively. The results show that the optimal system performance is achieved under the conditions of ξ=0.5 and the numbers of the primary and the secondary users being equal.

Multi-Layer Optimization for Load Scheduling to Manage Unreliable Grid Outages in Developing Countries

This paper describes the significant cost saving opportunities for consumers in developing countries by the use of computational intelligence and demand-side-management techniques to mitigate the massive use of diesel back-up during grid outages. Application of load scheduling optimization is investigated during scheduled power outages, for residential consumer in India. The specific load shifting approaches explored include a day ahead predicted load schedule which is generated by performing a DSM referring to the forecasted day ahead outage. Whereas in reality the predicted may not match the actual outage, thus in these cases a fuzzy logic rule base is referred on real time basis to take corrective action & reach the best optimal load schedule possible to attain the lowest cost. The load types modeled include passive loads and schedulable, i.e. typically heavy loads. It is found that this multi-level DSM schemes show excellent benefits to the consumer. The maximum diesel savings for the consumer due to load shifting can be approximately ranging from 45% to as high as 75% for a flat-tariff grid. The study also showed that the actual savings potential depends on the timing of power outage, duration and the specific load characteristics.

Power Control for Fading Channels in Cognitive Radio Networks with Outage-Probability Minimization

Cognitive radio allows Secondary Users （SUs） to dynamically use the spectrum resource licensed to Prirmry Users （PUs）, and significantly improves the efficiency of spectrum utilization and is viewed as a promising technology. In cognitive radio networks, the problem of power control is an important issue. In this paper, we mainly focus on the problem of power control for fading channels in cognitive radio networks. The spectrum sharing underlay scenario is considered, where SUs are allowed to coexist with PUs on the condition that the outage probability of PUs is below the maximum outage probability threshold limitation due to the interference caused by SUs. Moreover, besides the outage probability threshold which is defined to protect the performance of PUs, we also consider the maximum transmit power constraints for each SU. With such a setup, we emphasize the problem of power control to minimize the outage probability of each SU in fading channels. Then, based on the statistical information of the fading channel, the closed expression for outage probability is given in fading channels. The Dual-Iteration Power Control （DIPC） algorithm is also proposed to minimize the outage probability based on Perron-Frobenius theory and gradient descent method under the constraint condition. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme.

Outage Performance of Non-Orthogonal Multiple Access Based Unmanned Aerial Vehicles Satellite Networks

With rapid development of unmanned aerial vehicles(UAVs), more and more UAVs access satellite networks for data transmission. To improve the spectral efficiency, non-orthogonal multiple access(NOMA) is adopted to integrate UAVs into the satellite network, where multiple satellites cooperatively serve the UAVs and mobile terminal using the Ku-band and above. Taking into account the rain fading and the fading correlation, the outage performance is first analytically obtained for fixed power allocation and then efficiently calculated by the proposed power allocation algorithm to guarantee the user fairness. Simulation results verify the outage performance analysis and show the performance improvement of the proposed power allocation scheme.

Outage Probability and Achievable Rate Analysis for Massive MIMO Downlink with Mixed-DAC and MF Precoding

This paper analyses of the outage probability and the achievable rate of massive multi-input-multi-output(MIMO) systems, in which the base station(BS) is equipped with digital-to-analog-converters(DACs) of mixed-level resolution. And the matched-filter(MF) precoding is used on the BS. Closedform expressions are derived by the distribution of user-interference power and other statistical properties in the signal-to-interference-plus-noise-ratio. Then, the combination of mixed-DACs resolution profile is chosen about outage probability and achievable rate with the BS energy consumption. And the resolution configurations between the outage probability and the achievable rate and the BS energy consumption are given. Meanwhile, Effects of related parameters and channel errors are analysed about outage probability and achievable rate. The numerical results show that the correctness of the formula derivations. As the number of users increases the system's achievable rate increases and the outage probability decreases. The selected resolution configuration system has better comprehensive performance.

Bridging GPS outages of tightly-coupled GPS/SINS using GMDH neural network

A tightly coupled GPS （ global positioning system ）/SINS （ strap down inertial navigation system） based on a GMDH （ group method of data handling） neural network was presented to solve the problem of degraded accuracy for less than four visible GPS satellites with poor signal quality. Positions and velocities of the satellites were predicted by a GMDH neural network, and the pseudo ranges and pseudo range rates received by the GPS receiver were simulated to ensure the regular op eration of the GPS/SINS Kalman filter during outages. In the mathematical simulation a tightly cou pled navigation system with a proposed approach has better navigation accuracy during GPS outages, and the anti jamming ability is strengthened for the tightly coupled navigation system.

A Distributed Cell Outage Compensation Mechanism Based on RS Power Adjustment in LTE Networks

To solve the coverage and quality problems caused by cell outage in LTE networks, this paper proposes a distributed self-organizing networks management architecture and a distributed cell outage compensation management mechanism. After detecting and analyzing the outage, a cell outage compensation algorithm based on reference signal power adjustment is proposed. The simulation results show that the proposed mechanism can mitigate the performance degradation significantly. Compared with other algorithms, the proposed scheme is more effective in compensating the coverage gap induced by cell outage

Radio resource management scheme and outage analysis for network- assisted multi-hop D2D communications

In a cellular network it＇s very difficult to make spectrum resource more efficiently. Device-to-Device （D2D） technology enables new service opportunities, and provides high throughput and reliable communication while reducing the base station load. For better total performance, short-range D2D links and cellular links share the same radio resource and the management of interference becomes a crucial task. Here we argue that single-hop D2D technology can be used to further improve cellular networks performance if the key D2D radio resource management algorithms are suitably extended to support multi-hop D2D communications. Aiming to establish a new paradigm for the analysis and design of multi-hop D2D communications, We propose a radio resource allocation for multi-hop D2D routes based on interference avoidance approach in LTE-A networks. On top of that, we investigate the outage probability of D2D communication. We first introduce a new definition of outage probability by considering the maximum distance to be allowable for single-hop transmission. Then we study and analyze the outage performance of a multi-hop D2D route. We derive the general dosed form expression of outage probability of the multi-hop D2D routes. The results demonstrate that the D2D radio, sharing the same resources as the cellular network, provide higher capacity compared to pure cellular communication where all the data is transmitted through the base station. They also demonstrate that the new method of calculation of D2D multi hop outage probability has better performance than classical method defined in the literature.

An Anti-Eavesdrop Transmission Scheduling Scheme Based on Maximizing Secrecy Outage Probability in Ad Hoc Networks

In this paper,we consider a wireless ad hoc network consisting of multiple source nodes transmitting to their respective destinations,where an eavesdropper attempts to intercept their transmissions.We propose an optimal transmission scheduling scheme to defend against the eavesdropper,where a source node having the highest secrecy rate is scheduled to access the wireless medium for transmitting to its destination in an opportunistic manner.To be specific,the secrecy rate between a pair of the source and destination in the presence of an eavesdropper varies temporally due to the wireless fading effect.The proposed optimal transmission scheduling scheme opportunistically selects a source node with the highest secrecy rate to transmit its data for the sake of maximizing the security of the ad hoc network against eavesdropping attacks.For comparison purposes,we also consider the conventional round-robin scheduling as a benchmark,where multiple source nodes take turns in accessing their shared wireless medium for transmitting to their respective destinations.We derive closed-form secrecy outage probability expressions of both the round-robin scheduling and the proposed optimal scheduling schemes over Rayleigh fading environments.Numerical results show that the proposed transmission scheduling scheme outperforms the conventional round-robin method in terms of its secrecy outage probability.Additionally,upon increasing the number of source-destination pairs,the secrecy outage probability of the round-robin scheme keeps unchanged,whereas the secrecy outage performance of the proposed transmission scheduling significantly improves,showing the security benefits of exploiting transmission scheduling for protecting wireless ad hoc networks against eavesdropping.

Outage Analysis of Distributed Antenna Systems over Shadowed Nakagami-m Fading Channels

This paper presents an outage analysis of distributed antennas system(DAS) suffering from shadowed Nakagami-m fading environment where the desired signal also suffers from co-channel interference. The desired signal and interfering signal are subjected to path loss,multipath and shadowing fading. Based on Wilkinson's method,the signal to interference ratio(SIR) probability density function(PDF) of fixed DAS is obtained. Some numerical results of outage probability with different parameters are analyzed. The analysis results can provide sufficient precision for evaluating the outage performance of DAS.

Outage Probability Analysis for Modified Decode-and-Forward Model over Nakagami-m Fading Channels

This paper proposes a modified decodeand-forward(DAF) protocol with a three-node model,which contains two users and one destination.Each user can be either the source or the relay in different frames.We analyze the four cooperative cases in the first frame and run simulations to obtain the optimal power allocation coefficients in the second frame.The closed-form expression of outage probability is derived over Nakagami-m fading channels.Furthermore,we show that the proposed model has better performance than the non-cooperation system and traditional DAF strategy based on the derived outage probability.

OPTIMAL POWER ALLOCATION FOR COGNITIVE RADIO UNDER INTERFERENCE OUTAGE CONSTRAINT

Cognitive radio is able to share the spectrum with primary licensed user,which greatly improves the spectrum efficiency.We study the optimal power allocation for cognitive radio to maximize its ergodic capacity under interference outage constraint.An optimal power allocation scheme for the secondary user with complete channel state information is proposed and its approxi-mation is presented in closed form in Rayleigh fading channels.When the complete channel state in-formation is not available,a more practical transmitter-side joint access ratio and transmit power constraint is proposed.The new constraint guarantees the same impact on interference outage prob-ability at primary user receiver.Both the optimal power allocation and transmit rate under the new constraint are presented in closed form.Simulation results evaluate the performance of proposed power allocation schemes and verify our analysis.

Investigating Practical Measures to Reduce Power Outages and Energy Curtailments

This work attempts to investigate some practical measures that may reduce severe power outages that lead to energy curtailments. The first step of this attempt is to explore, from the consumer’s perspective, the adverse effects of the energy curtailments that reflect enormous damages (tangible and intangible) to the residential sector in the city of Riyadh (the capital of the Kingdom of Saudi Arabia). The second step is to propose, analyze, and employ energy conservation strategies that lead to both energy conservation and costs savings. The study results show that some customers will suffer enormous tangible and intangible losses should these outages occur during specific times, seasons, and for prolonged durations. In order to reduce these power outages and hence mitigate their adverse effects and consequences, the study proposes proper practical measures and solutions without compromising the consumers’ needs, satisfaction, and convenience.

Outage Performance of Cognitive Relay Networks with Best Relay Selection in Nakagami-m Channels

This paper investigates the outage performance of a cognitive relay network considering best relay selection in Nakagami-m fading environment. The secondary user is allowed to use the spectrum when it meets the interference constraints predefined by primary user. Due to deep fading, cognitive source is unable to communicate directly with cognitive destination. As such, multiple relays are ready to deliver the signal from the cognitive source to cognitive destination. We select a single best relay and the selected relay uses decode-and-forward protocol. Specifically, we derive the exact outage probability expression, which provides an efficient means to evaluate the effects of several parameters. Finally, numerical simulation results are presented, which validate the correctness of the analytical analysis.