Fuel-powered UAVs have long endurance of flight, heavy payload and adaptation to extreme environment. The mechanical operation and communication power are supported independently by fuel and batteries. In the paper, we study the energy efficiency of the communication system with a fuel-powered UAV relay. We consider a three-node communication network, consisting of a mobile relay, a source node, and a destination node. The UAV relay is able to change its 3-D trajectory to maintain high probability of LoS channels, receiving information from the fixed source node and transmitting it to the fixed destination node. The power allocation scheme and UAV’s trajectory are designed to maximize the system energy efficiency, considering the constraints of speeds, UAV’s altitudes, communication and mechanical energy consumption, the required data rates of the destination node and information-causality. We solve the power allocation sub-problem by splitting the domain of variables and transforming it into a convex optimization problem. And then a suboptimal scheme is provided to design the trajectory based on successive convex approximation method. Numerical results show the convergence of the proposed schemes and the performance of the proposed algorithms. The influences of time slots, constraints of fuel, communication power and required data rates are discussed.

In this paper, we consider a single cell downlink non-orthogonal multiple access (NOMA) network and aim at maximizing the energy efficiency. The energy-efficient resource allocation problem is formulated as a non-convex and NP-hard problem. To decrease the computation complexity, we decouple the optimization problem as a subchannel matching scheme and power allocation subproblems. In the subchannel matching scheme, a non-cooperative game is applied to model this problem. To discuss the existence of Nash equilibrium (NE), we introduce a super-modular game and then design an algorithm to converge to the NE point. Moreover, a greed subchannel matching algorithm with low complexity is given through a two-way choice between users and subchannels. However, for given subchannel matching scheme, power allocation is still a non-convex problem, which is difficult to get the optimal solution. We then transform the non-convex problem to a convex problem by applying a successive convex approximation method. Afterward, we provide an algorithm to converge to suboptimal solution by solving a convex problem iteratively. Finally, simulation result demonstrates that the energy efficiency performance of the NOMA system is better than the orthogonal frequency division multiple access system.

This paper investigates the admission control problem on the satellite multi-beam networks with non-orthogonal multiple access (NOMA). The goal is to maximize the number of supported users on the premise of ensuring the quality of service (QoS) by optimizing the subchannel and power allocation. We provide the system model and then formulate the admission control problem as a mixed integer non-convex optimization problem. The non-convexity and existence of integer variable make the optimal solution difficult to get. Therefore, we propose a joint subchannel matching and power allocation algorithm to obtain the suboptimal solution so as to reduce the computation complexity. The proposed algorithm can be used for both NOMA and orthogonal frequency division multiplexing access (OFDMA). Specifically, the subchannel matching problem is solved by a two-stage matching process where users are accessed to subchannel dynamically. The power allocation problem is modeled as a super-modular game where the existence and uniqueness of Nash equilibrium (NE) are analyzed. Moreover, an iterative power allocation algorithm is proposed based on the NE searching method. Finally, simulation results are provided for demonstrating the effectiveness and feasibility of the proposed algorithm.

Satellite network is a resource-limited system. How to fully explore the transmission capacity of a satellite network by integrating advanced communication technologies is a hot research topic. This paper focuses on network coding based single-source to multi-destination transmission problem in satellite networks and attempts to design a joint link adaption and resource allocation scheme to maximize the entire network's transmission capacity. We first apply time expanded graph (TEG) to depict the satellite network's dynamic and formulate the network coding involved joint data flow allocation, inter-satellite link (ISL) establishment, and power allocation issue into a non-convex mixed integer programming problem. To efficiently solve the problem, we then use Lagrange method to decouple it into two sub-problems: network coding based data flow routing problem and joint ISL establishment and power allocation problem. The former is proved to be convex problem which is solved by solving a minimum-cost routing problem and designing a trisection method, while the latter is solved by Lagrange dual method. Considering the relaxation solution is not necessarily optimal or even feasible, we finally propose an alternating optimization method to further improve the network capacity on the basis of the obtained relaxation solution. Simulation results validate the effectiveness of the proposed algorithm and indicates the significance of designing network coding based transmission schemes for satellite networks.

The measurement precision of a line-structured light measurement system is directly affected by the accuracy of extracting the center points of the laser stripes. When the measured object’s surface has significant undulations and severe reflections, existing algorithms are prone to issues such as significant susceptibility to noise and the extraction of false center points. To address these issues, an improved unilateral tracing-based structured light centerline extraction algorithm is proposed. The algorithm first performs unilateral and bidirectional tracing on the upper boundary of the preprocessed laser stripes, then uses the grayscale centroid method to extract the initial coordinates of the center points, and finally corrects them by calculating the stripe’s normal direction using the Hessian matrix. Experimental results show that the proposed algorithm can still extract the stripe center points well under strong interference, with the RMSE reduced by 37% compared to the Steger method and the running speed increased by almost 4 times compared to the grayscale centroid method. The algorithm’s strong robustness, high accuracy, and efficiency provide a viable solution for real-time measurement of line-structured light and high-precision three-dimensional reconstruction.