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The intelligent terminals deployed in hydropower IoT can quickly sense the status of hydropower equipment, thus improving the efficiency of system control and operation. However, communication security between the base station and intelligent terminals challenges the IoT hydropower plant. In this paper, we propose a UAV-assisted covert communication system (CCS), where a UAV acts as the base station to provide communication service to ground terminals monitored by malicious users. To improve access effectiveness, we adopt non-orthogonal multiple access (NOMA) for intelligent terminals to access the hydropower IoT. Since two devices can synchronously access the communication system with the NOMA scheme, we select one terminal to receive covert messages and the other to interfere with the malicious users to detect confidential communications. To maximize the covert rate, we formulate the optimization problem that jointly optimizes the transmit power, the altitude of the UAV, and trajectory under the constraints of covertness and the finite length of the transmission message block. Additionally, we transform the optimization problem into a geometric planning one, which is solved by a developed sequential geometric planning (SGP) approximation algorithm. Simulation results show the proposed algorithm can improve the covert rate compared to the traditional methods.

Driven by the rapidly growing demand for information security, covert wireless communication has become an essential technology and attracted tremendous attention. However, traditional wireless covert communication is continuously exposing the inherent limitations, creating challenges around deployment in environments with a large number of obstacles, such as cities with high-rise buildings. In this paper, we propose an intelligent reflecting surface (IRS)-assisted covert communication system (CCS) for communicating with a friendly unmanned aerial vehicle (UAV) in which the UAV generates artificial noise (AN) to interfere with monitoring. Furthermore, we model the power of AN emitted by the UAV using an uncertainty model, through which the closed-form detection error probability (DEP) of the covert wireless communication for monitoring is derived. Under the derived DEP, we formulate the optimization problem to maximize the covert rate, then design an iterative algorithm to solve the optimization problem and obtain the optimal covert rate using Dinkelbach method. Simulation results show that the proposed system achieves the maximum covert rate when the phase of the IRS units and the trajectory and transmit power of the UAV are optimized jointly.

Hybrid analog and digital (HAD) beamforming has been recently receiving considerable deserved attention for practical implementation on the large-scale antenna systems. Compared to fully-digital beamforming, partially-connected HAD beamforming can significantly reduce the hardware cost, complexity, and power consumption. This paper aims to mitigate interference and increase robustness against direction-of-arrival (DOA) mismatch along with lowering hardware complexity, cost, and power dissipation. To achieve these goals, a novel robust HAD beamforming receiver with partially-connected structure is proposed. It is based on methods of an improved bat algorithm (I-BA) and robust adaptive beamformers (RABs) in the digital domain. Since most of the RAB methods are sensitive to the DOA mismatch and depending on the complex weights which lead to an expensive receiver, the I-BA is proposed. In the analog part, analog phase alignment by linear searching (APALS) with sufficiently fine grid points is employed to optimize the analog beamforming matrix. The performance of the proposed I-BA is assessed using MATLAB simulation and compared with BA, and particle swarm optimization (PSO) algorithms. It shows better performance in terms of convergence speed, stability, and convergence rate. Besides, the proposed hybrid I-BA-APALS approach showed better performance compared to other proposed robust hybrid techniques, i.e., diagonal loading (DL) APALS (DL-APALS) and DL spatial matched filter (SMF) APALS (DL-SMF-APALS).

Power line communication (PLC) is an attractive approach to provide information transfer services for the smart home. The PLC network inherently suffers from the severe channel fading and impulsive noise. According to the mode of impulsive and the impulsive occurrence, the PLC channel can be modeled as the channel with memory. We compute the achievable rate by employing the Markov process with a finite number of states based on the dependence among the impulsive occurrence numbers in different time slots. Furthermore, the cumulative distribution function (CDF) for the received signal-to-noise ratio is derived with the statistical characteristics of the PLC channel. This helps in obtaining the ergodic capacity and outage probability for the PLC channels. We finally present the simulation results to verify the analytical results.

Evidence indicates that requesting video clips on demand accounts for a dramatic increase in data traffic over cellular networks. Caching part of popular videos in the storage of small-cell base stations (SBS) in cellular networks is an efficient method to reduce transmission latency and mitigate redundant transmissions. In this paper, we propose a commercial caching system consisting of a video retailer (VR) and multiple network service providers (NSPs). Each NSP leases its SBSs, with some price, to the VR for the purpose of making profits, and the VR, after storing popular videos in the rented SBSs, can provide better local video services to the mobile users, thereby gaining more profits. We conceive this system within the framework of a Stackelberg game by treating the SBSs as a specific type of resources. Then, we establish the profit models for both the NSPs and the VR based on stochastic geometry. We further investigate the Stackelberg equilibrium by solving the optimization problems in two cases, i.e., whether or not the VR has a budget plan on renting the SBSs. Numerical results are provided for quantifying the proposed framework by showing its efficiency on pricing and resource allocation.

The dissimilar steel welded joint is divided into three pieces, parent material−weldmetal−parent material, by the integrity identification of BS7910-2013. In reality, the undermatchedwelded joint geometry is dierent: parent material−heat aected zone (HAZ)−fusion line−weld metal.A combination of the CF62 (parent material) and E316L (welding rod) was the example undermatchedwelded joint, whose geometry was divided into four pieces to investigate the fracture toughness of thejoint by experiments and the extended finite element method (XFEM) calculation. The experimentalresults were used to change the fracture toughness of the undermatched welded joint, and the XFEMresults were used to amend the fracture toughness calculation method with a new definition of thecrack length. The research results show that the amendment of the undermatched welded jointgeometry expresses more accuracy of the fracture toughness of the joint. The XFEM models wereverified as valid by the experiment. The amendment of the fracture toughness calculation methodexpresses a better fit by the new definition of the crack length, in accordance with the crack routesimulated by the XFEM. The results after the amendment coincide with the reality in engineering.

Unmanned Aerial Vehicle (UAV) communication networks are vulnerable to malicious jamming and co-channel interference, deteriorating the performance of the networks. Therefore, the exploration of anti-jamming methods to enhance communication security becomes a significant challenge. In this paper, we propose a novel anti-jamming channel selection scheme in a multi-channel multi-UAV network. We first formulate the anti-jamming problem as a Partially Observable Stochastic Game (POSG), where the UAV pairs with partial observability compete for a limited number of communication channels against a Markov jammer. To ensure rapid adaptation to the dynamic jamming environment, we propose a Meta-Mean-Field Q-learning (MMFQ) algorithm, which provides a Nash Equilibrium (NE) solution to the POSG problem. Furthermore, we derive the expressions of the upper bound for the loss function of MMFQ and prove the convergence of the proposed algorithm. Simulation results demonstrate that the proposed algorithm can achieve a superior average reward compared to the benchmark algorithms, facilitating throughput enhancement and resource utilization increase, especially for large-scale UAV communication networks. [ABSTRACT FROM AUTHOR]