In this paper, we propose an integrated micro-optical light guide plate (MOLGP), of which the top surface is designed as aspheric semi-cylindrical micro-concentrator structure (ASCMCS) arrays and the bottom surface is fused with micro-prism arrays coated with a high-reflective film. And we also present the optimized structural parameters and distribution pattern of the MOLGP. By the simulation of the professional optical software Lighttools, it's verified that the integrated MOLGP we proposed can achieve the functions of five complex-structure films in current typical backlight module (BLM), and the Five Parameters (light energy utilization efficiency, average illuminance and luminance, uniformity of illuminance and uniformity of luminance) in the BLM with integrated MOLGP are respectively 1.49, 1.40, 1.07, 0.91 and 0.97 times than those in the typical BLM. Obviously, the performance parameters of the MOLGP exceed the traditional design. Moreover, we design two sets of four-step masks of the ASCMCS by the graphical user interface (GUI). At last, we fabricate a 1.8 inch integrated MOLGP sample. Comparative experiments show that the Five Parameters of the fabricated MOLGP sample are respectively 1.43, 1.43, 0.97, 0.89 and 0.70 times than those of the typical BLM. The experimental results verify the feasibility of the concept of the integrated MOLGP proposed in this paper.

The luminance uniformity of the backlight module (BLM) importantly depends on the microstructure distribution on the bottom surface of the light guide plate (LGP). Based on the small-size integrated LGP (ILGP) proposed, we put forward a distribution expression of micro-prisms on the bottom surface of the ILGP, and present the relational expressions between the coefficients of the analytical expression and the structural parameters of the ILGP, such as the light guide length L, width of the ILGP W, thickness of the ILGP H, and space between light emitting diodes (LEDs) d. Then, the research results above are applied to the design of the small-size ILGPs. Not only can the micro-structure distributions on the bottom surface of the ILGPs be directly given, but also the simulation results show that the luminance uniformities of the integrated BLMs are higher than 85%. The research indicates that the expressions proposed in this paper are correct and effective, and have important guiding significances and referential value.

Based on the backlight module (BLM) with an integrated micro-optical light guide plate (MOLGP) that we proposed [Opt. Express21, 20159 (2013)], an optical model that maps the relationship between the distribution of microprisms on the bottom surface of the integrated MOLGP and the luminance of the output light is established by a backpropagation neural network in this paper. Then the optimized distribution of the microprisms for high luminance uniformity of the output light is obtained by a genetic algorithm. Finally, the integrated BLM with the optimized distribution of microprisms on the bottom surface of the integrated MOLGP is set up in optical software, and the simulation results show that the luminance uniformity of the output light in this BLM reaches 93%.

The industrial Internet of Things (IIoT) has been viewed as a typical application for the fifth generation (5G) mobile networks. This paper investigates the energy efficiency (EE) optimization problem for the device-to-device (D2D) communications underlaying unmanned aerial vehicles (UAVs)-assisted IIoT networks with simultaneous wireless information and power transfer (SWIPT). We aim to maximize the EE of the system while satisfying the constraints of transmission rate and transmission power budget. However, the designed EE optimization problem is non-convex involving joint optimization of the UAV's location, beam pattern, power control and time scheduling, which is difficult to tackle directly. To solve this problem, we present a joint UAV location and resource allocation algorithm to decouple the original problem into several sub-problems and solve them sequentially. Specifically, we first apply the Dinkelbach method to transform the fraction problem to a subtractive-form one, and propose a mulitiobjective evolutionary algorithm based on decomposition (MOEA/D) based algorithm to optimize the beam pattern. We then optimize UAV's location and power control using the successive convex optimization techniques. Finally, after solving the above variables, the original problem can be transformed into a single-variable problem with respect to the charging time, which is linear and can be tackled directly. Numerical results verify that significant EE gain can be obtained by our proposed algorithm as compared to the benchmark schemes.

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