In this paper, an integrated navigation and communication system assisted by rate-splitting multiple access (RSMA) is considered. An on-board robust beamforming and rate optimization algorithm is proposed to enhance the system performance. With imperfect channel state information (CSI) in satellite–terrestrial channels, the total transmit power is minimized subject to communication quality-of-service and navigation accuracy constraints. To capture reliability requirements, an outage probability constraint is further imposed. The resulting problem is tackled via a block coordinate descent framework, which decomposes it into beamforming optimization and rate allocation subproblems. Non-convex constraints are handled using the S-procedure and Bernstein-type inequalities, while Boole’s inequality is adopted to decouple joint probabilistic constraints. Simulation results demonstrate the advantage of the proposed robust RSMA design over other schemes. In particular, non-robust RSMA shows the largest performance loss in Monte Carlo evaluations, orthogonal resource allocation trades efficiency for enhanced stability, the low-complexity RSMA scheme exhibits a restricted feasibility region, and robust space-division multiple access becomes increasingly suboptimal in terms of transmit power as CSI uncertainty grows.

Multi-access Edge Computing (MEC) technology has been widely considered as a paradigm for offloading computation-intensive and latency-sensitive tasks from ground devices (GDs). However, the deployment of ground edge servers to provide ubiquitous computing services for GDs may incur extremely high costs, primarily due to the uneven distribution of devices and the complexity of geographical environments. As a promising solution, deploying edge servers on Low Earth Orbit (LEO) satellites can offer superior coverage and reduced latency for processing remote terrestrial computational tasks. Nevertheless, considering the limitations in computing resources and energy supply on LEO satellites, it is crucial to enhance task processing efficiency while taking energy consumption into account. In this paper, we consider a multi-satellite cooperative edge computing network (MSCECN) where time-sensitive tasks can be offloaded to an Access Satellite (AS) and multiple Edge Satellites (ESs) through Inter-Satellite Links (ISLs). We formulate a delay-minimization offloading problem by jointly optimizing satellite selection, computing resource allocation, task scheduling, and transmit power control. To solve this problem effectively, we propose a novel joint iterative algorithm called Multi-Satellite Cooperative Resource Allocation (MSCRA), which integrates the relaxation method, the Lagrangian multiplier framework, and the CVX toolbox. Simulation results demonstrate that the proposed optimization scheme achieves a 35.5% reduction in total delay compared to benchmark algorithms and effectively minimizes offloading latency across various resource constraints.

Covert communication has become a hot topic in the wireless transmission field due to the ability to secure transmitted data by hiding the wireless transmissions. Given the extensive use of drone communications and its urgent demand for security, we investigate covert communications in aerial terrestrial integrated networks (ATINs), where an unmanned aerial vehicle (UAV) tries to send private messages to a remote user via multiple terrestrial relays under the supervisions of the warden. On this foundation, one covert scheme for joint power control and relay selection has been proposed. Subsequently, we derive the detection capabilities at warden, and the effective covert rate (ECR) of link from UAV to user. Furthermore, a power optimization problem is designed to maximize ECR with covertness constraint. Finally, numerical results are presented to verify the achievable covert performance of system and prove the effectiveness of the proposed scheme.

Ensuring massive access for a large number of devices is essential to realize the full potential of satellite Internet of Things (IoT), promising to bridge connectivity gaps and provide services in previously unreachable regions. However, traditional terrestrial access methods have been found inadequate for satellite-terrestrial communications, primarily due to their inability to account for the unique characteristics of space-ground links, such as signal propagation delays and the dynamic nature of satellite orbits. To tackle this issue, we propose an innovative access scheme based on grant-free random access. In order to meet the demand for simultaneous access of multiple terminals, joint detection and parameter estimation are carried out by collaborative satellites, through the linear minimum mean square error (LMMSE) algorithm and Newton's algorithm. Then, this scheme empowers users to select several short sequences to form their own preamble signal. The new scheme can meet the access requirements of a large number of users while reducing computational complexity and the impact of carrier frequency offset (CFO). Additionally, choosing multiple short sequences can effectively lower the probability of preamble conflict. Simulation results demonstrate that the collision probability of the proposed strategy can be reduced by 70 percent and the detection probability can be improved by 38 percent with an equal number of users and preambles.

Low-earth orbit (LEO) satellite Internet of Things (IoT) has emerged as a promising solution to address the limitations of terrestrial IoT by providing global coverage and seamless connectivity. Among the various techniques enhancing LEO satellite IoT, beam hopping (BH) stands out as an efficient approach that dynamically adjusts beam illumination to match the varying traffic demands of diverse IoT devices. This flexibility enables optimal utilization of limited on-board resources. However, while BH allows adaptive beam illumination planning, it can also introduce severe inter-beam interference, particularly when adjacent beams are simultaneously activated. To address this challenge, we propose a novel rate-splitting multiple access (RSMA)-enabled cluster-based beam hopping (CBH) LEO satellite IoT system. By leveraging RSMA, the proposed framework supports large-scale IoT devices access, and mitigates inter-beam interference introduced by CBH. Within this framework, we introduce a metric—the ratio of offered capacity to traffic demand (ROCD)—to quantify how well the required traffic sum rate aligns with the achievable sum rate for each beam. We then focus on jointly optimizing the precoding vector, common rate allocation, and CBH pattern design to maximize the worst-case ROCD among beams. To solve this problem efficiently, we decompose the original problem into three sub-problems and propose a two-stage algorithm. Numerical results demonstrate that our proposed scheme improves the minimum satisfaction rate by 14.10% and 39.59% compared to the non-orthogonal multiple access and space-division multiple access baselines, achieving effective interference mitigation.

Mobile/wireless virtual reality (VR) services, especially immersive 360° VR videos, have advanced unprecedentedly in recent years. However, the high bandwidth requirement of VR services has compounded the burden on wireless networks. Multicast is a high potential technique for alleviating the bandwidth requirement of 360° VR video streaming, but the multicast capacity is still constrained by the users with poor channel conditions, and it vanishes when the number of users increases while the number of the base station (BS) antennas is fixed. To overcome the drawbacks of multicast, sidelink, which is an adaptation of the core LTE standard that allows the device-to-device (D2D) communications without going through a BS, can be utilized. In this article, two sidelink-aided multicast scenarios (i.e., independent decoding and joint decoding) are studied for multiquality tiled 360° VR video transmission. We propose a utility model for each scenario, and quality level selection, sidelink sender/receiver selection, and transmission resource allocation are optimized to maximize the total utility of all users under the bandwidth constraints as well as the quality smoothness constraints for multiquality tiles. We then develop an iterative two-stage algorithm to obtain suboptimal solutions to the formulated mixed-integer nonlinear programming (MINLP) problems. Simulation results demonstrate the advantage of the proposed solutions over several baseline schemes.

With the development of virtual reality (VR) technology, the future of VR systems is evolving from single-user wired connections to multi-user wireless connections. However, wireless online rendering and transmission incur extra processing and transmission latency, as well as higher bandwidth requirements. To meet the requirements of wireless VR applications and enhance the quality of the VR user experience, this paper designs a view synthesis-based 360° VR caching system over Cloud Radio Access Network (C-RAN), where both mobile edge computing (MEC) and hierarchical caching are supported. In the system, an MEC-Cache Server is deployed in the pooled Base band Units (BBU pool) and used for view synthesis and caching. In addition, the remote radio heads (RRHs) can also cache some video contents. If the requested content of a specific view is cached in the BBU pool or RRHs, or can be synthesized with the aid of the cached adjacent views, it is unnecessary to request the content from the remote VR video source server. Therefore, the transmission latency and backhaul traffic load for VR services can be decreased. We formulate a hierarchical collaborative caching problem aiming to minimize the transmission latency, which is proved NP-hard. To address the impractical expenses of the offline optimal method, an online MaxMinDistance caching algorithm with low complexity is proposed. Numerical simulation results demonstrate that the proposed caching strategy provides significantly improved cache hit rate, backhaul traffic load, transmission latency, and Quality of Experience (QoE) performances relative to conventional caching strategies.

Caching at the wireless edge is a promising way to alleviate the heavy burden of the backhaul links and reduce the latency of transmission and handover. Although some effective caching schemes have been introduced to Cloud based Radio Access Network (C-RAN), most of them were designed without consideration of users' mobility. In this paper, we investigate the mobility property in cache-enabled C-RAN, and propose a mobility aware proactive caching strategy. We aim to design a novel controller, which is able to utilize the computation and storage resources in C-RAN, and responsible for making cache decision for both the baseband unit (BBU) pool and Remote Radio Head (RRH). A transmission delay model is introduced to formulate the cache placement optimization problem. To solve the problem, we propose an algorithm named MAPCaching. Numerical simulation results show that MAPCaching significantly outperforms the Greedy and EPC caching strategies in terms of average content access delay and cache hit rate by 30% and 20%, respectively.