In the Fifth Generation (5G) era, different operators keep their Base Stations (BS) active in the same area to ensure user service coverage. However, this high level of redundant coverage leads to significant energy waste, especially given the high power consumption of 5G BSs. To address this issue, this paper proposes the Collaborative Operator Partnership based Energy-efficient framework (COPE), a 5G network optimization approach based on multi-operator collaboration. COPE encourages operator cooperation through revenue incentives, combines time series analysis to predict user distribution and service demand, and uses deep reinforcement learning to guide BS leasing, facilitating cross-operator resource collaboration. Extensive experimental results demonstrate that COPE reduces total BS energy consumption by approximately 19% and optimizes costs by about 9% in multi-operator scenarios.

Rainfall over the ocean strongly influences microwave remote sensing by altering electromagnetic scattering mechanisms, complicating radar backscatter interpretation and its relationship to surface wind. However, in-depth understanding of these effects under different surface and frequency conditions remains limited. In this study, for the first time, coordinated multi-frequency radar observations at C-, X-, and Ku-bands were carried out to investigate scattering from (i) airborne raindrops, (ii) rain perturbed windless water surface, and (iii) wind-driven sea surface agitated by rain. Field measurements combined radar backscatter intensity with Doppler spectral signatures to elucidate the underlying scattering mechanisms. Synchronized radar and optical imaging enabled joint characterization of scattering signatures and geometric features of wind waves and rain-induced ring waves. Results reveal pronounced variations in both airborne raindrop scattering and surface backscattering under different rainfall rates, frequency bands and polarizations. Under low sea-state conditions, Doppler spectra exhibit a distinct dual-peak structure attributable to ring wave backscattering, whereas at higher sea states this feature is masked by the dominant spectral energy of wind waves. Using rain-induced ring wave theory and the small-slope approximation (SSA), Doppler spectra due to ring waves were simulated and validated against experimental measurements. This study clarifies the mechanisms of rain-induced scattering and demonstrate the dominant role of ring waves in shaping the observed Doppler spectral signatures.

It is of great theoretical and practical significance to study the multidimensional statistical characteristics of sea clutter at different range resolutions, such as optimizing clutter modeling and suppression, improving radar system design and remote sensing data interpretation ability. The analysis of the effect of range resolution based on different sea clutter datasets poses a significant challenge in the drawing of reliable conclusions, owing to the variability in radar parameters and sea state conditions. In this paper, a new method is proposed to obtain sea clutter data with different range resolutions based on high resolution radar data by reducing the sampling time of the original intermediate frequency (IF) signal. Base on this method, the statistical characteristics of sea clutter at different range resolutions are analyzed for the first time, including the amplitude distribution, coherence length of sea texture, phase difference distribution, Doppler spectrum, and wave radial velocity of sea clutter at three range resolutions: high (0.75m), moderate (7.5m), and low (25m), while all other environmental parameters and radar parameters remain constant. The results clearly show the effect of range resolution on sea clutter properties and can be used to guide development of clutter models.

Accurate mapping of oil concentrations is essential for effective response to oil spill emergencies. The complexity of microwave scattering over oil-contaminated sea surfaces poses substantial challenges for synthetic aperture radar (SAR) applications, primarily due to the limited understanding of non-Bragg scattering mechanisms. This knowledge gap restricts the development of robust retrieval algorithms for quantifying oil spill concentrations. To address this issue, a novel retrieval approach is proposed based on the co-polarization difference (PD), which is independent of non-Bragg scattering. The influence of oil on the sea surface is attributed to two dominant factors: suppression of short gravity-capillary waves and reduction in the effective dielectric constant. By analyzing SAR imagery of oil spills with varying concentrations, it is found that the damping effect of oil spills on small-scale waves can be predicted using the Marangoni damping model. Once the contribution of wave suppression to PD reduction is isolated, the residual PD variation is attributed to changes in the dielectric constant. Oil concentration is then retrieved by comparing the PD of each pixel within the contaminated area to a theoretical PD lookup table. The proposed method is validated using simulated SAR datasets representing different oil concentrations and subsequently applied to SAR data acquired during the Deepwater Horizon oil spill in the Gulf of Mexico.

Estimating the M (the proportion of oil in the oil-water mixture) is crucial for the emergency response to oil spill pollutions. Synthetic aperture radar (SAR) has been extensively utilized in monitoring oil spills. Previous studies predominantly focused on distinguishing oil spills from sea backgrounds. In contrast, the objective of this study is to evaluate the ability of a fully polarimetric SAR to quantitatively estimate the M of marine oil spills and develop a method to achieve this goal. This paper analyzes the correlation between different polarimetric features, such as polarization scattering entropy, mean scattering angle, and more, and their relationship with the M values using L-band fully polarimetric SAR images obtained during the 2010 Deepwater Horizon (DWH) oil spill accident. The results indicate that the mean scattering angle is the most suitable polarization feature for inverting the oil-water mixing ratio. Based on these findings, a novel method for estimating the M of marine oil spills using fully polarimetric SAR images is proposed. This study represents the initial endeavor to explore the benefits of employing a fully polarimetric SAR for the purpose of inverting oil-water mixing ratios.

Retrieving the oil-water mixture ratio (M, the proportion of oil in an oil-water mixture) of the marine oil spill is of vital importance for the emergency treatment of oil pollution, which can be achieved by a copolarization ratio (PR) method. In the framework of the PR method, it is assumed that Bragg scattering dominates at moderate incidence angles, and the relative contribution of non-Bragg scattering to total scattering (RCNT) is typically neglected. However, in this work, it is found that the RCNT cannot be neglected for L-band, especially for HH polarization at higher wind speeds (the RCNT is approximately 0.6~0.8 for wind speeds of 10~12 m/s). The significant impact of non-Bragg scattering results in the PR method not being accurate enough for retrieving M. After separately investigating the influences of the damping effect and effective dielectric constant reduction on the RCNT, a novel approach is proposed for more accurately estimating the M of marine oil spills by eliminating the impact of non-Bragg scattering. The proposed method was applied to UAVSAR images collected during the Deepwater Horizon (DWH) oil spill accident. The inversion results of our approach show that the M of most oil spill areas ranges from approximately 0.3 to 0.6, which matches the reality better than that of a traditional PR method (ranging from approximately 0.6 to 0.8).

In this article, a theoretical study is carried out to seek an approach to remotely measure the thickness of the oil film. It is known that it is difficult to probe the oil thickness using a microwave radar due to the fact the dielectric constant of oil is very small compared with seawater for microwave frequencies. While in the range of terahertz (THz) electromagnetic (EM) wave frequency, the dielectric constants of oil and seawater are comparable, resulting in the THz EM fields scattered from the air-oil interface and those from the oil-water interface can produce constructive and destructive interference with the variation in the oil film thickness. Based on this principle, the sensitivity of the THz EM wave to the oil thickness is investigated in this work. First, the oil-seawater two-layer medium is equivalent to a single-layer medium by an equivalent dielectric constant model. Then, the THz EM scattering from the oil-covered sea surface is simulated using the first-order small slope approximation method (SSA-1) and the obtained equivalent dielectric constant. Meanwhile, the influences caused by the damping effect of the oil film, the reduction for friction velocity, and the change in equivalent permittivity on the normalized radar cross section (NRCS) are analyzed. The numerical results show that the NRCSs of THz frequencies are more sensitive to the change in oil thickness than that of microwave frequencies. This property makes the THz EM wave have the potential to probe the thickness of the oil film.

This article is devoted to investigating the microwave scattering mechanisms of oil-free and oil-covered sea surfaces for an incidence angle smaller than 30° in a backscattering configuration. The Elfouhaily spectrum is used to simulate an oil-free sea surface, whereas the Elfouhaily spectrum combined with the Jenkins damping model is applied to the simulation of an oil-covered sea surface. Then, the Kirchhoff approximation-stationary phase approximation (KA-SP) and the first order of small-slope approximation (SSA-1) are employed to simulate the scattering coefficients induced by specular scattering and total scattering, respectively. Importantly, a new parameter defined as specular scattering to total scattering ratio (STR) is proposed in this article, which can be used to measure the ratio of specular backscattered power to total backscattered power. The dependencies of the scattering coefficient and the STR on incidence angles, wind speeds, wind directions, oil thicknesses, and so on, are investigated. This article provides new insights for a better understanding of the evolution of microwave scattering mechanisms from oil-free and oil-covered sea surfaces in the transition region of incidence angles (from about 15° to 30°).

The two-scale model (TSM) has been frequently used in the study of EM (electromagnetic) scattering from rough surface due to its simple and practical merit. However, for microwave scattering from sea surface, it cannot provide accurate predictions for hh (horizontal) polarization. To overcome this problem, an improved version of the TSM (ITSM) which can be better used for predicting microwave scattering from sea surface is proposed in this paper. In the ITSM, we propose to use two cutoff parameters to separate sea surface roughness. For kwcs, the KA-SP (Kirchhoff approximation-stationary phase approximation) rather than KA-GO (Kirchhoff approximation-geometric optics approximation) is employed to simulate the specular scattering component. For kw>kcb, the SPM modulated by tilts of large-scale waves is employed to simulate the Bragg scattering component. The values of kcsand kcbare chosen according to the validity conditions of the KA and the SPM. The numerical comparisons illustrate that the ITSM performs better than the TSM and the SSA-1, especially in the prediction of hh polarized scattering coefficient.

In this paper, the microwave (5GHz) and terahertz (1THz) EM (electromagnetic) wave scattering from sea surface covered with oil are studied in theory. The sea surface covered with oil can be regarded as a two-layered structure, the upper layer is oil and the lower layer is seawater. For microwave scattering, it is known that the oil covered on sea surface mainly influence the sea surface from two aspects: the damping effect for small scale wave and the reduction for friction velocity. In this work, the modification for Fresnel scattering coefficient due to the presentation of oil film is also taken into account. The numerical simulations show that the NRCS (normalized radar cross section) of microwave is not sensitive to the thickness of oil film. On the contrary, the NRCS of terahertz wave is more sensitive to the thickness of oil film, which provides us more information to probe oil slicks on sea surface with terahertz EM waves.

C band microwave radars have been widely used in ocean observations, e.g. oil spill monitoring, ship detection, wind speed retrieval, etc. All these applications rely on the measured normalized radar cross section (NRCS) of sea surface. Therefore, it is necessary to develop accurate models to predict the radar cross sections of sea surface. In this paper, based on the six commonly used sea spectra models, i.e. Elfouhaily, Hwang, Romeiser, Apel, Fung and Pierson spectra, the normalized radar cross sections are calculated by Small Perturbation Method (SPM), Two Scale Model (TSM) and the first order Small Slope Approximation (SSA-1), respectively. Meanwhile, to better evaluate the accuracy of different sea spectra, comparisons between numerical calculations and the empirical CMOD5 model are made for various incident angles, wind speeds, and wind directions. The comparisons show that the normalized radar cross sections calculated based on Romeiser spectrum agree better with CMOD5 in some specific cases. The works presented in this paper will be helpful for applications of C band microwave radars in ocean observations.

Compared with single-polarization synthetic aperture radar (SAR), full-polarization SAR can not only collect the echo intensity of backscattered from the sea surface, but also can collect the phase information. For oil spill detection, polarimetric SAR has more advantages. Features extraction is a crucial step for oil spill discrimination. In this paper, eight kinds of polarimetric features, such as the polarimetric entropy, average scatter angle and so on, have been investigated to analyze the capability of the polarimetric features to observe an oil spill at C-band and L-band, and to identify the most powerful multi-polarimetric SAR descriptors for oil spill detection. And a systematic comparison of the eight multi-polarization features is provided. Here, the analysis is conducted on the quad-pol SAR images acquired by the SIR-C/X-SAR. The experiment results show that the pedestal height and the parameter P perform better than the other polarimetric features at C-band.