Satellite-integrated Internet can provide multi-type intelligent services for ubiquitous user equipments (UEs) in the next-generation networks. Considering that most existing multicast systems in satellite-integrated Internet cannot accommodate the diverse requirements of heterogeneous services with limited resources, we propose a utility-optimal multi-type services multicast system based on multiple-input multiple-output rate-splitting multiple access (MIMO-RSMA). Specifically, we consider three types of semantic services classified based on their timeliness, reliability, and semantic characteristics. To support these heterogeneous services coexistences under constrained resources, we design three tiered priority scheduling (TPS) policies with progressively increasing inter-service resource coupling, and demonstrate their advantages under different operating conditions. Considering diverse demands of semantic services, we propose the utility loss of information (UoI) to capture the requirements of each service, and formulate a multi-constrained UoI-minimization problem within each transmission stage of the TPS policies, and transform it via Lyapunov framework with the proposed exponentially-weighted virtual queue (EWVQ). Further, we design a soft actor-critic (SAC)-based power allocation and rate control (PARC) scheme, and propose an adaptive weighted priority scheduling (AWPS) function to solve the non-convex UoI-minimization problem under differentiated reliability requirements. Simulation results validate the effectiveness of the proposed TPS policies and demonstrate that our SAC-PARC scheme outperforms state-of-the-art schemes in minimizing UoI.

The pull-based transmission initiates the generation and updating of status to the destination as needed, potentially reducing unnecessary energy costs and maintaining data freshness for satellite-integrated Internet with limited resources. In this paper, we introduce a semantic-empowered metric called utility loss of information (UoI) for a multi-state Markov source to assess the freshness and value of information, and the synchronization of transceivers, which can simultaneously quantify the age of information (AoI), value of diversity states, and the mismatch of transceivers. Then, we propose a utility-critical prompt (UP) transmission scheme for terrestrial Internet of Things (IoT) sensors with multi-state Markov source to transmit status update to the satellite efficiently, and derive the average UoI (AUoI) in both periodic and stochastic queries. Simulation results demonstrate that the UP scheme can achieve an optimal tradeoff between freshness, value, and synchronization of transceivers in both periodic and stochastic queries, and outperforms than state-of-the-art schemes.

Abstract Driven by the vision of ubiquitous connectivity and wireless intelligence, the evolution of ultra-dense constellation-based satellite-integrated Internet is underway, now taking preliminary shape. Nevertheless, the entrenched institutional silos and limited, nonrenewable heterogeneous network resources leave current satellite systems struggling to accommodate the escalating demands of next-generation intelligent applications. In this context, the distributed satellite information networks (DSIN), exemplified by the cohesive clustered satellites (CCS) system, have emerged as an innovative architecture, bridging information gaps across diverse satellite systems, such as communication, navigation, and remote sensing, and establishing a unified, open information network paradigm to support resilient space information services. This survey first provides a profound discussion about innovative network architectures of DSIN, encompassing distributed regenerative satellite network architecture, distributed satellite computing network architecture, and reconfigurable satellite formation flying, to enable flexible and scalable communication, computing and control, fundamentally enhancing network resilience. The DSIN faces challenges from network heterogeneity, unpredictable channel dynamics, sparse resources, and decentralized collaboration frameworks. To address these issues, a series of enabling technologies is identified, including channel modeling and estimation, cloud-native distributed MIMO cooperation, new waveform design, grant-free massive access, nonorthogonal multicast, distributed phased array antennas, high-speed inter-satellite communication, network routing, and the proper combination of all these diversity techniques. Furthermore, to heighten the overall resource efficiency, the cross-layer optimization techniques are further developed to meet upper-layer deterministic, adaptive and secure information services requirements. In addition, emerging research directions and new opportunities are highlighted on the way to achieving the DSIN vision.

The existing task-agnostic and resource-constrained satellite communication fails to meet diverse task demands in the upcoming sixth-generation (6G) network. In this paper, to enable the ubiquitous intelligent services with massive traffic for global users through satellite-Integrated Internet, we first propose a novel semantic metric named utility loss of information (UoI), which can capture the task-oriented aspects by quantifying both value loss of semantic mismatch, and energy loss of unnecessary transmissions. Then, we design a UoI minimization data generation and transmission (UMGT) scheme for task-adaptive communications in satellite-Integrated Internet with energy constraint and reliability requirement. For the time-varying satellite-terrestrial link with high bit error rate (BER) and delayed feedback, we derive the closed-form expressions of BER, and apply the long erasure coding (LEC) to combat the deep fading. Subsequently, we transform the optimization problem to minimize the upper bound of an unconstrained Lyapunov drift-plus-penalty (DPP). Further, we propose two deep reinforcement learning (DRL) algorithms to intelligently choose when to generate data, how to adjust the number of LEC packets and whether to retransmit, thereby minimizing the average UoI. Simulation results validate that our UMGT scheme can achieve the lowest UoI than several state-of-the-art schemes, and demonstrate its adaptability to various task demands.

In response to the requirements of precise information conveying and goal-oriented transmitting with minimal cost for the upcoming satellite-integrated Internet, we focus on a semantic communication metric named utility loss of information (UoI), which is generalized to capture the tradeoff of the value and energy loss of information. The former is quantified by the duration and severity of mismatch transceivers, and the latter is evaluated by unnecessary data generation and transmissions. To achieve the optimal tradeoff between value and energy loss of information for status update, we formulate a joint optimization problem to design a UoI-optimal policy to generate and transmit data for a multi-state Markov source. By regarding the limited energy, we transform the above problem to a constrained Markov decision process (CMDP), and rigorously prove the UoI-optimal policy has a dual-threshold structure. Then, we derive the closed-form expressions for average UoI and generation and transmission ratio. Moreover, we propose a simplified relative value iteration (SRVI) algorithm based on the theoretical derivations, combined with the bisection search to find two optimal thresholds for the UoI-optimal policy. Simulation results verify that our UoI-optimal policy achieves the optimal tradeoff among timeliness, reliability, and energy efficiency, and outperforms several state-of-the-art semantic-aware policies.

Satellite-integrated Internet can provide pervasive intelligent services for ubiquitous terrestrial equipments (TEs) in the forthcoming sixth generation network. Consider that the most of existing multicast systems in satellite-integrated Internet are content independent, which may result redundant data transmission in satellites with limited resources, we propose a semantic empowered rate splitting multiple access (RSMA) downlink system. First, we propose a semantic empowered metric, named Utility Loss of Information (UoI), which can simultaneously capture freshness, mismatch of transceivers, and environment ingredient for the RSMA downlink system. Then, we design a joint content- and environment-aware sampling policy for discrete multistate Markov sources to achieve minimum UoI, and provide rigorous proof to show the policy has a threshold structure and derive the closed-form transmission ratio. Further, we formulate a joint optimization of power allocation and rate control for the RSMA downlink system to minimize long-term average UoI with limited onboard resources, and utilize the Lyapunov optimization framework to transform the above problem to minimize the upper bound of corresponding drift-plus-penalty expression, and solve via a deep reinforcement learning-based algorithm. Simulation results validate that our scheme achieves the minimum long-term average UoI, under optimal tradeoff among timeliness, reliability, and environment-aware importance, and outperforms the state-of-the-art schemes.

The upcoming space-air-ground integrated network (SAGIN) can provide status updates relaying for ground user equipment (UEs). However, the SAGIN cannot utilize traditional hybrid automatic retransmission request (HARQ) for reliable transmission due to the high bit error rate (BER) and long propagation latency. In this paper, we propose the age-critical long erasure code-CCSDS file delivery protocol (LEC-CFDP) schemes with the metric of age of information (AoI) to realize timely status updates in dual-hop SAGIN. We first propose the uniform LEC-CFDP (U-LEC-CFDP), where the UE and satellite can uniformly insert one LEC packet in every$(L-1)$information packets, and the receiver can utilize the LEC packet to recover the lost packets and avoid retransmission. Moreover, the satellite can immediately forward the successively recovered information packets to the destination, named U-LEC-i CFDP, and a close-form expression of peak AoI (PAoI) for the U-LEC-i CFDP is derived. To further improve PAoI, we model a partially observable Markov decision process (POMDP) problem to analyse optimal$L$for our dynamic LEC-i CFDP (D-LEC-i CFDP), and design an effective Point-based Informed Bound (PIB) algorithm to update optimal$L$. Simulation results show that the D-LEC-i CFDP scheme can lower the expected end-to-end delay and PAoI in comparison with U-LEC-CFDP schemes.

The upcoming satellite Internet of Things (S-IoT) can provide status updates relaying for ground user equipment (UE). However, the S-IoT cannot utilize conventional hybrid automatic retransmission request (HARQ) for reliable transmission due to the high bit error rate (BER) and long propagation latency. The consultative committee for space data systems (CCSDS) has proposed the CCSDS file delivery protocol (CFDP) to relieve the long propagation latency, and the CFDP utilizes retransmission to guarantee the reliability. In this paper, we propose two age-critical long erasure coding-CFDP (LEC-CFDP) schemes to realize dual-hop timely status updates in S-IoT via a relay satellite over shadowed Rician (SR) fading channel, where the satellite and destination can select the deferred or asynchronous mode to adjust the number of inserted LEC packets, called D-LEC CFDP and A-LEC CFDP, respectively. Further, the satellite can select half-duplex or full-duplex relay mode, i.e., LEC-h CFDP or LEC-f CFDP to forward packets to the destination. We derive a close-form expression for the peak age of information (PAoI) and an approximation expression for the expected end-to-end delay for the D-LEC-f CFDP scheme. Moreover, we propose an A-LEC-f CFDP scheme to further improve the PAoI, and model it as a partially observable Markov decision process (POMDP) problem, which can be solved by a low complexity Point-based Informed Bound (PIB) algorithm. Simulation results verify the accuracy of the theoretical derivations, and illustrate that the A-LEC-f CFDP scheme can achieve lower end-to-end delay and PAoI in comparison with the existing schemes.

Satellite-based Internet of Things (S-IoT) is viewed as an efficient solution to provide timely status updates to the terrestrial user equipment (UE), due to its ubiquitous coverage and broadband access capability inherited from high throughput satellite (HTS). However, the conventional hybrid automatic repeat request (HARQ) cannot guarantee the freshness of status update transmission, because the reliable transmission needs the retransmission of the lost packets, which deteriorates the freshness due to the nontrivial propagation delay and high bit error rate (BER) of the satellite–territory link (STL). In this article, we propose an age-optimal network coding HARQ (NC HARQ) scheme with the metric of information timeliness, i.e., Age of Information (AoI) to realize timely status updates in S-IoT. First, we model the STL as a shadowed Rician (SR) fading channel and derive the closed-form expressions of BER. Then, we propose a fixed interval NC inserted HARQ (f-NC HARQ) scheme, where the NC packets are inserted in the information packets with fixed interval to accelerate the recovery of lost information packets and derive the expressions of Peak AoI (PAoI) and average end-to-end delay. Furthermore, we propose an adaptive NC inserted HARQ (A-NC HARQ) scheme for the drastic variations in the SR fading channel, where the transmission of the status update is modeled as a partially observable Markov decision process (POMDP) problem and solved by a low complexity improved fast informed bound (iFIB) algorithm. Simulation results validate the accuracy of our theoretical derivations and show that the A-NC HARQ scheme can achieve the lowest PAoI and average end-to-end delay.