The deployment of low-Earth orbit (LEO) constellations, combined with inter-satellite link (ISL) technology, will drive the development of future sixth-generation (6G) and satellite Internet of Things (SIoT). However, the deployment of a large number of LEO satellites and corresponding ISLs intensifies the spectrum resource scarcity in space, which may result in severe ISL interference (ISLI). Therefore, this paper proposes a theoretical framework for optimal design of LEO satellite constellations to mitigate ISLI. Specifically, the system average signal-to-interference-plus-noise ratio (SA-SINR) metric is introduced to depict ISLI, and deterministic analysis expression for SA-SINR is derived. Meanwhile, an integral merging algorithm (IMA) is proposed to accurately calculate the ground coverage area of satellite networks, considering the need to cover ground users in a wide distribution range. Then, the optimal constellation design issue is formulated into a mathematical multi-objective optimization problem, and an improved particle swarm optimization (PSO) scheme is designed to solve it. Simulation results show that the constellation designed based on the proposed approach outperforms the existing Starlink and OneWeb constellations in terms of ISLI and coverage performances, validating the effectiveness of our proposal.

The advantages of Low Earth Orbit (LEO) satellite navigation in addressing the increasing demand for high-precision and universally accessible positioning have garnered widespread attention. Our work builds upon our previous development of the Zadoff-Chu non-orthogonal multiple access (ZC-NOMA) waveform for integrated communication and navigation (ICAN). Expanding on this foundation, we conceive the ICAN-oriented multi-satellite asynchronous transmission (ICAN-MSAT) framework, which allows users to concurrently receive communication and navigation signals from multiple satellites without synchronization, thus increasing communication flexibility and leveraging the geometric distribution and robust signals of LEO satellite constellations to enhance navigation performance. Within the ICAN-MSAT framework, we propose a novel multi-satellite asynchronous transmission oriented subcarrier and power allocation (MSASP) algorithm to manage mutual interference between communication and navigation components and inter-satellite interference (INSI) caused by asynchronous transmission, with the latter often overlooked in most existing work. Simulation results demonstrate that the proposed algorithm meets the performance requirements of both navigation and communication, achieving higher communication rates under the same navigation accuracy constraints compared to current benchmarks.

The underwater sensor network plays a critical role in the ocean data collection owing to its capability of providing reliable and wide communication coverage. How to assure the lifetime performance of the network with a limited energy supply has always been a key research issue. In this article, we propose an underwater acoustic sensor network model which supports data delivery from each underwater sensor node (USN) to the sea surface sink node (SN) in either direct or relay-assisted transmission mode, i.e., transmission mode between each USN and the SN can be dynamically selected according to network’s current state. To optimize its lifetime performance, we model the mode selection and resource allocation issues jointly into a nonconvex and mixed-integer programming problem. In order to efficiently solve it, we further divide the original problem into two subproblems: 1) resource allocation subproblem and 2) joint mode and relay selection subproblem. We prove that the reformulated nonconvex resource allocation problem can be equivalent to a convex optimization problem, and its optimal solution can be found by using Lagrange dual decomposition method. For the second subproblem, some critical conditions are analyzed to determine optimal relays with the criterion of balancing energy consumption between USNs, and a matching approach is designed to obtain the mode and relay selection results based on USNs’ priorities. Simulation results validate that the proposed transmission scheme is effective and superior to the traditional time division multiple access scheme.

For the increasingly strong demand for low-orbit navigation enhancement, a novel navigation and communication integrated (NAVCOM) waveform for the LEO constellation is proposed, which can conduct communication and navigation simultaneously. Zadoff-Chu (ZC) sequence with controllable power is superimposed on the communication signal in the frequency domain as the positioning signal. Furthermore, positioning can be conducted with both time-domain correlation detection (TDCD) and frequency-domain phase estimation (FDPE) for higher ranging accuracy benefits from the Fourier invariance of ZC sequence. Interference between positioning and communication components is analyzed, and the Cramer-Rao low bound (CRLB) of ranging error is given. The performance evaluations show that the novel waveform can achieve high-precision positioning without signifilcantly affecting communication performance.

In the past several years, various visual object tracking benchmarks have been proposed, and some of them have been used widely in numerous recently proposed trackers. However, most of the discussions focus on the overall performance, and cannot describe the strengths and weaknesses of the trackers in detail. Meanwhile, several benchmark measures that are often used in tests lack convincing interpretation. In this paper, 12 frame-wise visual attributes that reflect different aspects of the characteristics of image sequences are collated, and a normalized quantitative formulaic definition has been given to each of them for the first time. Based on these definitions, we propose two novel test methodologies, a correlation-based test and a weight-based test, which can provide a more intuitive and easier demonstration of the trackers’ performance for each aspect. Then these methods have been applied to the raw results from one of the most famous tracking challenges, the Video Object Tracking (VOT) Challenge 2017. From the tests, most trackers did not perform well when the size of the target changed rapidly or intensely, and even the advanced deep learning based trackers did not perfectly solve the problem. The scale of the targets was not considered in the calculation of the center location error; however, in a practical test, the center location error is still sensitive to the targets’ changes in size.

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.