Energy-Efficient Traffic Offloading for RSMA-Based Hybrid Satellite Terrestrial Networks with Deep Reinforcement Learning

As the demands of massive connections and vast coverage rapidly grow in the next wireless communication networks, rate splitting multiple access(RSMA) is considered to be the new promising access scheme since it can provide higher efficiency with limited spectrum resources. In this paper, combining spectrum splitting with rate splitting, we propose to allocate resources with traffic offloading in hybrid satellite terrestrial networks. A novel deep reinforcement learning method is adopted to solve this challenging non-convex problem. However, the neverending learning process could prohibit its practical implementation. Therefore, we introduce the switch mechanism to avoid unnecessary learning. Additionally, the QoS constraint in the scheme can rule out unsuccessful transmission. The simulation results validates the energy efficiency performance and the convergence speed of the proposed algorithm.

Deep Unfolding for Cooperative Rate Splitting Multiple Access in Hybrid Satellite Terrestrial Networks

Rate splitting multiple access(RSMA)has shown great potentials for the next generation communication systems.In this work,we consider a two-user system in hybrid satellite terrestrial network(HSTN)where one of them is heavily shadowed and the other uses cooperative RSMA to improve the transmission quality.The non-convex weighted sum rate(WSR)problem formulated based on this model is usually optimized by computational burdened weighted minimum mean square error(WMMSE)algorithm.We propose to apply deep unfolding to solve the optimization problem,which maps WMMSE iterations into a layer-wise network and could achieve better performance within limited iterations.We also incorporate momentum accelerated projection gradient descent(PGD)algorithm to circumvent the complicated operations in WMMSE that are not amenable for unfolding and mapping.The momentum and step size in deep unfolding network are selected as trainable parameters for training.As shown in the simulation results,deep unfolding scheme has WSR and convergence speed advantages over original WMMSE algorithm.

Numerical simulation of three dimensional concrete printing based on a unified fluid and solid mechanics formulation

Deformation control constitutes one of the main technological challenges in three dimensional(3D)concrete printing,and it presents a challenge that must be addressed to achieve a precise and reliable construction process.Model-based information of the expected deformations and stresses is required to optimize the construction process in association with the specific properties of the concrete mix.In this work,a novel thermodynamically consistent finite strain constitutive model for fresh and early-age 3D-printable concrete is proposed.The model is then used to simulate the 3D concrete printing process to assess layer shapes,deformations,forces acting on substrate layers and prognoses of possible structural collapse during the layer-by-layer buildup.The constitutive formulation is based on a multiplicative split of the deformation gradient into elastic,aging and viscoplastic parts,in combination with a hyperelastic potential and considering evolving material properties to account for structural buildup or aging.One advantage of this model is the stress-update-scheme,which is similar to that of small strain plasticity and therefore enables an efficient integration with existing material routines.The constitutive model uses the particle finite element method,which serves as the simulation framework,allowing for modeling of the evolving free surfaces during the extrusion process.Computational analyses of three printed layers are used to create deformation plots,which can then be used to control the deformations during 3D concrete printing.This study offers further investigations,on the structural level,focusing on the potential structural collapse of a 3D printed concrete wall.The capability of the proposed model to simulate 3D concrete printing processes across the scales—from a few printed layers to the scale of the whole printed structure—in a unified fashion with one constitutive formulation,is demonstrated.

Multi-Product Expansion with Suzuki’s Method: Generalization

In this paper we discuss the extension to exponential splitting methods withrespect to time-dependent operators. We concentrate on the Suzuki’s method, whichincorporates ideas to the time-ordered exponential of [3, 11, 12, 34]. We formulate themethods with respect to higher order by using kernels for an extrapolation scheme. Theadvantages include more accurate and less computational intensive schemes to specialtime-dependent harmonic oscillator problems. The benefits of the higher order kernelsare given on different numerical examples.