A tutorial review is provided of forward and inverse radiative transfer in coupled atmosphere-snow/ice-water systems. The coupled system is assumed to consist of two adjacent horizontal slabs separated by an interface across which the refractive index changes abruptly from its value in air to that in ice/water. A comprehensive review is provided of the inherent optical properties of air and water (including snow and ice). The radiative transfer equation for unpolarized as well as polarized radiation is described and solutions are outlined. Several examples of how to formulate and solve inverse problems encountered in environmental optics involving coupled atmosphere-water systems are discussed in some detail to illustrate how the solutions to the radiative transfer equation can be used as a forward model to solve practical inverse problems.

Self-Organizing Networks (SON) is an automation technology in the wireless industry implemented to simplify the planning, deployment, operation, optimization, and healing of networks. However, legacy SON functions are targeted at network automation and network optimization through certain optimization rules and policies which are globally applied in the entire networks. Therefore, scalable and targeted optimization is not supported in these existing SON solutions. Furthermore, such existing SON schemes are driven by performance optimization rather than ultimately improving user Quality of Experience (QoE). The impact of application characteristics on network performance and further on QoE are also not considered in SON defined by 3GPP. This paper presents an application characteristics-driven SON system (APP-SON) to optimize 4G/5G network performance and user Quality of Experience. APP-SON leverages a scalable big data platform for targeted optimization through profiling cell application characteristics with an incremental manner in temporal space. A Hungarian Algorithm Assisted Clustering (HAAC) algorithm and a deep learning-assisted regression algorithm are developed to profile the cell application characteristics and find the targeted KPIs to be optimized for each cell in a network. A similarity-based parameter-tuning algorithm is designed to tune the corresponding engineering parameters to optimize the targeted KPIs which further improve the QoE. Experimental results demonstrated that the APP-SON system can precisely profile cell traffic and application characteristics to find the targeted KPIs for optimization. APP-SON can also automatically tune the corresponding engineering parameters to improve corresponding KPIs, ultimately improving QoE. APP-SON has been successfully implemented in production and applied in a tier-1 operator's 4G network. As a universal SON solution, it will be smoothly transitioned and applied in 5G networks for this operator.

An optimized discrete-ordinate radiative transfer model (DISORT3) with a pseudo-two-dimensional bidirectional reflectance distribution function (BRDF) is used to simulate and validate ocean glint reflectances at an infrared wavelength (1036 nm) by matching model results with a complete set of BRDF measurements obtained from the NASA cloud absorption radiometer (CAR) deployed on an aircraft. The surface roughness is then obtained through a retrieval algorithm and is used to extend the simulation into the visible spectral range where diffuse reflectance becomes important. In general, the simulated reflectances and surface roughness information are in good agreement with the measurements, and the diffuse reflectance in the visible, ignored in current glint algorithms, is shown to be important. The successful implementation of this new treatment of ocean glint reflectance and surface roughness in DISORT3 will help improve glint correction algorithms in current and future ocean color remote sensing applications.

The treatment of strongly anisotropic scattering phase functions is still a challenge for accurate radiance computations. The new delta-M+ method resolves this problem by introducing a reliable, fast, accurate, and easy-to-use Legendre expansion of the scattering phase function with modified moments. Delta-M+ is an upgrade of the widely used delta-M method that truncates the forward scattering peak with a Dirac delta function, where the “+” symbol indicates that it essentially matches moments beyond the first M terms. Compared with the original delta-M method, delta-M+ has the same computational efficiency, but for radiance computations, the accuracy and stability have been increased dramatically.