Since mmWave signals are sensitive to blockages, prior channel models including the LoS probability function for ultra high frequency (UHF) band can not be applied directly to analyze mmWave cellular networks. Compared with the empirical LoS probability model obtained from the computationally intensive simulations and measurements, the theoretical LoS probability model in mmWave cellular networks still remains unclear. According to the Huygens-Fresnel principle for the wave propagation, the LoS probability is closely related to the carrier frequency. In this paper, the 3D frequency-dependent LoS probability model incorporated with the Fresnel zone is presented, and shows good agreement with the empirical models adopted in the 3GPP standard for various scenarios.

Free space optical (FSO) relay communication systems based on unmanned-aerial-vehicle (UAV) play an important role in various communication scenarios. In this paper, a UAV-assisted FSO relay system with a decode-and-forward (DF) relaying scheme is analyzed. We examine the effects of path loss, atmospheric turbulence, nonzero boresight pointing errors, angle-of-arrival (AoA) fluctuations, and other parameters on the performance of the system. Using Málaga distribution as the atmospheric turbulence model, closed-form expressions are derived for channel fading coefficient probability density function (PDF), outage probability, bit error rate (BER) and other parameters. Based on the closed-form expression, numerical results are then utilized in order to determine the optimal values for various tunable parameters to maximize system performance. The results indicate that the performance metrics are strongly dependent on tunable parameters, such as beamwidth, UAV's position and receiver's field-of-view (FoV) angle, the optimal UAV's position is highly correlated with the beamwidth at the receiver of destination. Moreover, when using DF relaying, we observe that the end-to-end system performance is dependent on the link with inferior performance. Therefore, when other tunable parameters are already determined, the UAV's position should be adjusted to balance the performance of two links for the purpose of improving the end-to-end system performance.

In-depth insights into the profound impacts of climate change and human activities on water resources are garnered through the dynamic changes in surface water, a crucial aspect of effective water resource management and the preservation of aquatic ecosystems. This paper introduces an innovative approach employing the random forest algorithm for the systematic extraction and monitoring of surface water at large regional or national scales. This method integrates spectral bands, spectral indices, and digital elevation model data, offering a novel perspective on this critical task. A data-filling model is proposed to mitigate the impact of missing data due to cloud cover. Leveraging the capabilities of the Google Earth Engine (GEE), detailed information on surface water dynamics during the rainy and dry seasons in the Yangtze River Basin (YRB) from 1991 to 2021 is extracted using Landsat time series imagery. The analysis encompasses spatial-temporal variation characteristics and trends, with a specific focus on the intricate interplay between the areal extent of surface water and hydro-meteorological factors in each sub-basin of the YRB. Importantly, this includes considerations of potential groundwater contributions to surface water. Key findings from our research include: (1) Achieving a remarkable overall classification accuracy of 0.96 ± 0.03 in obtaining reliable surface water datasets with the support of GEE. (2) Identifying significant trends, such as a noteworthy increase in rainy season surface water bodies (+248.0 km²·yr⁻¹) and a concerning decrease in surface ice/snow cover during both rainy and dry seasons, with change rates of −39.7 km²·yr⁻¹ and −651.3 km²·yr⁻¹, respectively. (3) Uncovering the driving mechanisms behind these changes, revealing positive correlations between the areal extent of rainy season surface water bodies and precipitation, as well as negative correlations between surface ice/snow cover area and average surface skin temperature. It is crucial to note that these driving factors exhibit variation among secondary river systems, underscoring the complexity of surface water dynamics. Furthermore, comparative analyses with existing surface water products are conducted, contributing to a deeper understanding of the advantages and uncertainties inherent in our proposed extraction method. The proposed method for large-scale surface water extraction not only enhances the monitoring of spatio-temporal surface water dynamics in the YRB but also provides valuable insights for the sustainable utilization and protection of water resources, considering the potential role of groundwater in supplementing surface water.

This letter aims to maximize the average throughput via the joint design of the transmit power and trajectory for unmanned aerial vehicle (UAV)-enabled network. The conventional way to tackle this problem is based on the alternating optimization (AO) method by iteratively updating power and trajectory until convergence, resulting in a non-convex trajectory subproblem which is difficult to deal with. To develop more efficient methods, we propose a novel AO method by incorporating both power and trajectory into an intermediate variable, and then iteratively updating power and the newly introduced variable. This novel variable transformation makes it easier to decompose the original problem into two convex subproblems, namely a throughput maximization subproblem and a feasibility subproblem. Consequently, both of these subproblems can be solved in a globally optimal fashion. We further propose a low-complexity algorithm for the feasibility subproblem by exploiting the alternating directional method of multipliers (ADMM), whose updating step is performed in closed-form solutions. Simulation results show that our proposed method reduces the computation time by orders of magnitude, while achieving higher performance than the conventional methods.

This paper focuses on greedy approaches to select the most informative $k$ sensors from $N$ candidates to maximize the Fisher information, i.e., the determinant of the Fisher information matrix (FIM), which indicates the volume of the information ellipsoid (VIE) constructed by the FIM. However, it is a critical issue for conventional greedy approaches to quantify the Fisher information properly when the FIM of the selected subset is rank-deficient in the first $(n-1)$ steps, where $n$ is the problem dimension. In this work, we propose a new metric, i.e., the Fisher information intensity (FII), to quantify the Fisher information contained in the subset $\mathcal {S}$ with respect to that in the ground set $\mathcal {N}$ specifically in the subspace spanned by the vectors associated with $\mathcal {S}$ . Based on the FII, we propose to optimize the ratio between VIEs corresponding to $\mathcal {S}$ and $\mathcal {N}$ . This volume ratio is composed of a nonzero (i.e., the FII) and zero part. Moreover, the volume ratio can be easily calculated based on a change of basis. A cost function is developed based on the volume ratio and proven monotone submodular. A greedy algorithm and its fast version are proposed accordingly to guarantee a near-optimal solution with a complexity of $\mathcal {O}(Nkn^{3})$ and $\mathcal {O}(Nkn^{2})$ , respectively. Numerical results demonstrate the superiority of the proposed algorithms under various measurement settings.

Impulsive noise is considered a type of interference that may significantly affect the performance of communication systems and thus cannot be neglected. In this letter, the probability density function (PDF) of impulsive noise passing through the Discrete Fourier Transform-Spread-Orthogonal Frequency Division Multiplexing (DFT-S-OFDM) systems is derived, and the bit error rate (BER) of the DFT-S-OFDM systems under impulsive noise is analyzed. Based on the PDF of impulsive noise, we derive an explicit expression of the BER. In addition, an approximated BER expression is further derived for computational efficiency. Numerical results demonstrate that the derived theoretical BER results show good agreement with the simulated BERs under various impulsive noise scenarios.