With recent developments in wireless communication technologies, malicious users can use them to commit crimes or launch terror attacks, thus imposing new threats on public security. To quickly respond to these attacks, authorized parities need to intervene in the malicious communication links over the air. This paper investigates the emerging wireless communication intervention problem at the physical layer. Unlike prior studies using jamming to disrupt or disable the targeted wireless communications, we propose a new physical-layer spoofing approach to change their communicated information. Consider an abstract three-node model over additive white Gaussian noise channels, in which a legitimate spoofer aims to spoof a malicious communication link from a malicious transmitter to a malicious receiver, such that the received message at the receiver is changed from the transmitter's originally sent message to the one desired by the spoofer. We propose a new symbol-level spoofing scheme, where the spoofer designs the spoofing signal by exploiting the symbol-level relationship between each original constellation point of the transmitter and the desirable one of the spoofer. In particular, the spoofer aims to minimize the average spoofing-symbol-error-rate (SSER), which is defined as the average probability that the symbols decoded by the malicious receiver fail to be changed or spoofed, by designing its spoofing signals over symbols subject to the average transmit power constraint. By considering two cases when the malicious transmitter employs the widely-used binary phase-shift keying and quadrature phase-shift keying modulations, we obtain the respective optimal solutions to the two average SSER minimization problems. Numerical results show that the symbol-level spoofing scheme with optimized transmission achieves a much lower average SSER, as compared with other benchmark schemes.
Lightning activity causes the different lightning impacts to transmission lines varying with the time and region,accordingly,the lightning protection performance has a great difference in time and space.In order to completely master the lightning protection performance of transmission lines,we presented an evaluation method which takes the time-space-difference lightning protection performance of transmission lines into account especially.On the basis of the long-term lightning data detected by lightning location system,we adopted the grid statistical method of lightning parameters to carry out the lightning parameter analysis along the transmission line corridor in the appointed time period.With the obtained lightning parameters including ground flash density and cumulative probability distribution of lightning current,the lightning trip-out rate of transmission line as well as each line section were calculated in the appointed time period.Compared with the evaluation grade determined from the designed value,defined value or operating value of the lightning trip-out rate of the line,the time-space-difference of lightning protection performance of the transmission line was evaluated with detailed grades.The evaluation results can be used in taking more appropriate and selective lightning protection measures to improve the lightning protection performance of transmission lines.
This paper considers a wireless relay network where two nodes S1 and S2 exchange their information through a relay node RL. It is assumed that both S1 and S2 are equipped with single antenna and RL is equipped with multi-antennas. Based on the principle of physical layer network coding (PNC), we study the optimal design for the analogue relaying, also known as amplify-and-forward (AF), at RL so as to maximize the sum- rate of bi-directional information exchange between S1 and S2. Optimal solution for the multi-antenna linear processing at RL is presented and low-complexity suboptimal schemes are proposed. Simulation results show that the proposed methods perform better than the conventional zero-forcing (ZF) and minimum- mean-squared-error (MMSE) -based linear relaying, and the performance gain is very significant when the two channels from S1 and S2 to RL are highly correlated.
Energy consumption has emerged as a key issue for designing next generation wireless networks. Having to periodically recharge mobile devices using power cords hampers the mobile operation of the devices. On the other hand, energy-constrained wireless networks, such as sensor networks, have limited lifetime due to the difficulty in replacing or recharging batteries in the nodes. Energy harvesting is a promising approach that addresses these issues as it powers mobile devices and, in general, wireless networks by scavenging energy from the ambient environment. Specifically, the networks can be made self-sustaining by harvesting energy from rich sources including solar power, electromagnetic waves, thermal energy, wind energy, salinity gradients, and kinetic energy. The recent emphasis on green communications also provides a strong motivation for developing energy harvesting based communication techniques. This has become all the more urgent because the electricity consumption of the fast expanding networks that handle mobile devices has grown rapidly, and will soon contribute significantly to global warming.
Curve is one of important spatial objects on GIS spatial data.It is the base of describing surface and body.In current GIS products,GIS spatial curve is described by mathematics and interpolation. Its visualization is implemented in computer.In this paper,GIS spatial curve is described by ant colony algorithms.This method is intelligent.Through theory analysis and simulation experiment,feasibility and availability of the method are indicated by the result.
Ambient backscatter communication (AmBC) enables radio-frequency (RF) powered backscatter devices (BDs) (e.g., sensors and tags) to modulate their information bits over ambient RF carriers in an over-the-air manner. This technology, also called "modulation in the air," has emerged as a promising solution to achieve green communication for future Internet of Things. This paper studies an AmBC system by leveraging the ambient orthogonal frequency division multiplexing (OFDM) modulated signals in the air. We first model such AmBC system from a spread-spectrum communication perspective, upon which a novel joint design for BD waveform and receiver detector is proposed. The BD symbol period is designed as an integer multiplication of the OFDM symbol period, and the waveform for BD bit "0" maintains the same state within the BD symbol period, while the waveform for BD bit "1" has a state transition in the middle of each OFDM symbol period within the BD symbol period. In the receiver detector design, we construct the test statistic that cancels out the direct-link interference by exploiting the repeating structure of the ambient OFDM signals due to the use of cyclic prefix. For the system with a single-antenna receiver, the maximum-likelihood detector is proposed to recover the BD bits, for which the optimal threshold is obtained in closed-form expression. For the system with a multi-antenna receiver, we propose a new test statistic which is a linear combination of the per-antenna test statistics and derive the corresponding optimal detector. The proposed optimal detectors require only knowing the strength of the backscatter channel, thus simplifying their implementation. Moreover, practical timing synchronization algorithms are proposed for the designed AmBC system, and we also analyze the effect of various system parameters on the transmission rate and detection performance. Finally, extensive numerical results are provided to verify that the proposed transceiver design can improve the system bit-error-rate performance and the operating range significantly and achieve much higher data rate, as compared with the conventional design.
The results of a wideband measurement campaign aimed at investigating the diffuse scattering characteristics of rough materials at 40-50 GHz are shown in this paper. Scattering coefficients are derived based on the Fresnel formula theory and Gaussian rough surface model. The results indicate that the calculated coefficients agree well with the measured data, and the backscattering phenomena and the Fabry-Pérot resonance characteristic are obvious.
This paper investigates an unmanned aerial vehicle (UAV)-enabled multiuser wireless power transfer (WPT) system, where a UAV-mounted energy transmitter (ET) is dispatched to broadcast wireless energy to charge multiple energy receivers (ERs) on the ground. To ensure efficient and fair WPT, we maximize the minimum of the energy harvested by all ERs during a given charging period, by optimizing the UAV's trajectory subject to its maximum speed constraints. Such a min-energy maximization problem, however, is non-convex, and thus is challenging to be directly solved. To tackle this problem, we first consider an ideal case by ignoring the UAV's maximum speed constraint, and show that the relaxed problem can be optimally solved via the Lagrange dual method. The obtained trajectory solution implies that the UAV should hover over a set of fixed locations with optimal allocation of the hovering time among them. Then, for the general case with the UAV's maximum speed constraint considered, we propose a new successive hover-and-fly trajectory motivated by the optimal trajectory in the ideal case, and obtain efficient trajectory designs by applying the successive convex programing (SCP) optimization technique. Numerical results show that our proposed trajectory designs significantly improve the min-energy transferred to all ERs, as compared to other benchmark schemes.
This paper investigates the real-time energy management in power system with distributed microgrids, which are independently operated and each is modeled to comprise of a renewable generation system, an energy storage system and an aggregated load. We jointly optimize the energy charged/discharged to/from the storage system and that drawn from the main grid over a finite horizon to minimize the total energy cost of conventional generation subject to given load and storage constraints. We assume that the renewable energy offset by the load over time, named net energy profile, is predictable but with finite errors. First, we consider the "off-line" optimization under an idealized assumption that the net energy profile is known ahead of time, and derive its optimal closed-form solution. Next, by applying the off-line solution combined with a sliding-window based sequential optimization, we propose a new "online" algorithm for real-time energy management under the practical setup with noisy predicted net energy profile subject to arbitrary errors. Finally, through simulations, we compare the performance of our proposed online algorithm against the conventional dynamic programming based solution as well as a heuristically designed myopic algorithm under a practical setup.
Frequency control is essential to maintain the stability and reliability of power systems. Traditionally, generation side controllers have been used to stabilize the system frequency upon contingencies; however, they incur high operational cost. Enabling demand response in next generation smart grids is thus a promising alternative to reduce the power system dependency on expensive controllers. In particular, demand response of distributed electric vehicles (EVs) via controlled charging/discharging power from/to the grid can be an effective method to help stabilize the system frequency. In this paper, we propose a new distributed frequency control algorithm for EVs with randomized responses and characterize its performance in a large-scale dynamic power system in terms of the mean of the system frequency over time, the mean frequency recovery time, and the expected number of responded EVs upon a contingency. Finally, we validate our analysis via simulations under a practical power system setup.
In this study, a terahertz dual-band–high-gain, multi-input–multi-output (MIMO) antenna with two and four input ports was realized, with gain values of up to 7.16[Formula: see text]dBi and 6.44[Formula: see text]dBi, respectively. This represents an increase in gain of 102.4% and 81.8%, respectively, compared to single-input port antennas. By calculating and analyzing the voltage standing wave ratio (VSWR), gain, envelope correlation coefficient (ECC), and diversity gain, the two MIMO antennas achieved perfect impedance matching at their resonance points. Moreover, the interference between the elements of the MIMO antenna was small, and an isolation effect between the units was realized. These MIMO antennas can achieve multiple input signals to regulate the antenna radiation performance and improve signal strength and quality. In addition, they possess good development prospects for achieving high-speed data transmission in the terahertz band and in mobile communication.
Wireless power transfer (WPT) technology enables a cost-effective and sustainable energy supply in wireless networks. However, the broadcast nature of wireless signals makes them non-excludable public goods, which leads to potential free-riders among energy receivers. In this study, we formulate the wireless power provision problem as a public goods provision problem, aiming to maximize the social welfare of a system of an energy transmitter (ET) and all the energy users (EUs), while considering their private information and self-interested behaviors. We propose a two-phase all-or-none scheme involving a low-complexity Power And Taxation (PAT) mechanism, which ensures voluntary participation, truthfulness, budget balance, and social optimality at every Nash equilibrium (NE). We propose a distributed PAT (D-PAT) algorithm to reach an NE, and prove its convergence by connecting the structure of NEs and that of the optimal solution to a related optimization problem. We further extend the analysis to a multi-channel system, which brings a further challenge due to the non-strict concavity of the agents' payoffs. We propose a Multi-Channel PAT (M-PAT) mechanism and a distributed M-PAT (D-MPAT) algorithm to address the challenge. Simulation results show that our design is most beneficial when there are more EUs with more homogeneous channel gains.
A new universal algorithm based on the criterion of MMSE is presented to estimate timing error and frequency offset for most signals of digital phase-related modulation schemes such as M-DPSK, MSK and FSK. It can easily deal with signals with different modulation schemes and data rates by only setting a few input arguments of the versatile software modules. The algorithm consumes far less operating resources than the traditional methods and the average processing capacity of the algorithm is about 40 instructions per symbol. It is applied to process signals with high data rate in software radios.
