In this paper, a method for designing super-massive sparse phased arrays (SMSPAs) known as the unitary modified matrix enhancement and matrix pencil (UMMEMP) method is proposed. In this method, an eigenvalue pairing method, which is inspired by the modified MEMP, effectively pairs the repeated eigenvalues intractable in the unitary matrix pencil method, and it is more effective in determining the locations of elements in the sparse array. Three numerical examples and a full-wave validation are presented to demonstrate the effectiveness of the method, implemented via SMSPA, in achieving low sidelobe level wide-angle scanning radiation patterns, circular flat-top radiation patterns, and ultra wide-angle scanning radiation patterns.
Due to the advantages of high mobility and line-of-sight transmission, unmanned aerial vehicles (UAVs) equipped with mobile edge computing (MEC) servers can effectively reduce the computational burden and task delay of ground users (GUs). However, the offloading data from GU to UAV is vulnerable to be eavesdropped by malicious users in the network. Thus, this paper proposes a secure cooperative offloading scheme in a multi-UAV-assisted MEC network, where each UAV has the capability to partially distributing the tasks to other idle UAVs. Specifically, we first model the task offloading decision process of GUs based on the multi-agent Markov Decision Process (MDP) framework. Then we optimize the offloading decision of GUs by adopting multi-agent deep determined policy gradient (MADDPG) to minimize the overall system latency for task processing and computation offloading. Simulation results verify that the proposed cooperative offloading scheme can effectively reduce the system latency compared with the benchmark.
Satellite and terrestrial cellular networks can be integrated together to achieve extended broadband coverage for, e.g., maritime communication scenarios, in the upcoming sixth-generation (6G) era. To counter spectrum scarcity, collaborative spectrum sharing is considered for hybrid satellite-terrestrial networks (HSTNs) in this paper. With only slowly-varying large-scale channel state information (CSI), joint power and channel allocation is implemented for terrestrial mobile terminals (MTs) which share the same frequency band with the satellite MTs opportunistically. Specially, strict quality service assurance is adopted for terrestrial MTs under the constraint of leakage interference to satellite MTs. With the target of maximizing both the number of served terrestrial MTs and the average sum transmission rate, a double-target spectrum sharing problem is formulated. To solve the complicated mixed integer programming (MIP) problem efficiently, user-centric channel pools are introduced. Simulations demonstrate that the proposed spectrum sharing scheme could achieve a significant performance gain for the HSTN.
With the widespread application of communication technology in the non-terrestrial network (NTN), the issue of the insecure communication due to the inherent openness of the NTN is increasingly being recognized. Consequently, safeguarding communication information in the NTN has emerged as a critical challenge. To address this issue, we propose a beamforming and horizontal trajectory joint optimization method for unmanned aerial vehicle (UAV) covert communications in the NTN. First, we formulate an optimization problem that considers constraints such as the transmitting power and the distance. Moreover, we employ the integrated communication and jamming (ICAJ) signal as Alice’s transmitting signal, further protecting the content of communication information. Next, we construct two subproblems, and we propose an alternate optimization (AO) algorithm based on quadratic transform and penalty term method to solve the proposed two subproblems. Simulation results demonstrate that the proposed method is effective and has better performance than benchmarks.
In this paper, a $4 \times 4$ wideband linearly polarization (LP) antenna array is proposed by using planar dual-arm spiral structures. Wideband balun structures, composed of microstrip line-fed coupling slots, are adopted to feed two dual-arms spiral structures with opposite phases. Then, by combining the left- and right- hand circular polarizations, a linearly polarization is achieved. The proposed antenna has a wide operating bandwidth due to the wideband nature of the spiral structure. Simulated results show that the antenna element can achieve a 68.73$\%$ impedance bandwidth and a maximum gain of 6.64 dBi within 19.44 - 38.83 GHz. A $4 \times 4$ array prototype is designed to verify the concept. Measured results show that an impedance bandwidth of 63.73$\%$ is obtained. The proposed array has the merits of a wide bandwidth, a low profile, a low cost, and a small size, which is promising for the application in millimeter wave wireless systems.
In recent years, load balancing routing algorithms have been extensively studied in satellite networks. Most existing studies focus on path selection and hop-count optimization for end-to-end transmission, while overlooking congestion issues on feeder links caused by the limited number and centralized distribution of ground stations. Hence, a multi-service routing algorithm called the Multi-service Load Balancing Routing Algorithm for Traffic Return (MLB-TR) is proposed. Unlike traditional approaches, MLB-TR aims to achieve a broader and more comprehensive load balancing objective. Specifically, based on the service type, an appropriate landing satellite is first selected by considering factors such as shortest path hop count and satellite load. Then, a set of candidate paths from the source satellite to the selected landing satellite is computed. Finally, using the regional load balancing index as the optimization objective, the final transmission path is selected from the candidate path set. Simulation results show that the proposed algorithm outperforms the existing works.
Due to the extraordinary advantages, unmanned aerial vehicle (UAV) can be utilized as aerial base station (BS) to provide temporary and on-demand wireless connections for user equipments in the coverage area. This article specifically considers the UAV-enabled orthogonal frequency division multiple access (OFDMA) wireless communication network. Considering a practical scenario, a joint resource allocation and trajectory design optimization problem with the constraints on UAV mobility, limited total resource and backhaul link rate has been formulated, which aims to maximize the minimum achievable average rate of the users. To tackle the coupling and non-convexity of the proposed problem, an efficient optimization algorithm has been proposed based on alternating optimization, successive convex approximation and introducing slack variable techniques. Simulation results illustrate that the proposed optimization algorithm can effectively improve the system performance. Also, the numerical results unveil that joint optimization is superior to baseline schemes.
Multispectral low earth orbit (LEO) satellites are characterized by a large volume of captured data and high spatial resolution, which can provide rich image information and data support for a variety of fields, but it is difficult for them to satisfy low-delay and low-energy consumed task processing requirements due to their limited computing resources. To address the above problems, this paper presents the LEO satellites cooperative task offloading and computing resource allocation (LEOC-TC) algorithm. Firstly, a LEO satellites cooperative task offloading system was designed so that the multispectral LEO satellites in the system could leave their tasks locally or offload them to other LEO satellites with servers for processing, thus providing high-quality information-processing services for multispectral LEO satellites. Secondly, an optimization problem with the objective of minimizing the weighted sum of the total task processing delay and total energy consumed for multispectral LEO satellite is established, and the optimization problem is split into an offloading ratio subproblem and a computing resource subproblem. Finally, Bernoulli mapping tuna swarm optimization algorithm is used to solve the above two sub-problems separately in order to satisfy the demand of low delay and low energy consumed by the system. Simulation results show that the total task processing cost of the LEOC-TC algorithm can be reduced by 63.32%, 66.67%, and 80.72% compared to the random offloading ratio algorithm, the average resource offloading algorithm, and the local computing algorithm, respectively.
