International Journal of Satellite Communications and Networking最新文献

Connectivity in satellite networks is governed by the spacecraft nodes' orbital dynamics together with the planet's continuous rotation where ground nodes are located. The resulting time-dynamic but predictable topology demands the design of specific distributed routing schemes. However, terrestrial Internet routing schemes' maturity, proven scalability, and efficiency shall be leveraged whenever possible to facilitate space-terrestrial integration while reducing risk and costs. In line with this reflection, we introduce SATNET-OSPF: a backward-compatible satellite extension for the widely used Open Shortest Path First routing protocol. The key features of SATNET-OSPF are (a) accurate routing interface mapping to inter-satellite links and ground-to-satellite links, (b) accelerated link-up/link-down event detection adapted to space-specific wireless technologies, (c) proactive routing and forwarding mechanism to take advantage of predicted link-down events, and (d) low memory footprint topology model to efficiently propagate the forthcoming space connectivity events via constrained telecommand links. Leveraging existing IPv6 and OSPFv3 open-source stacks, we implemented SATNET-OSPF in an actual space router comprising a space-grade SPARC V8 CPU and a radiation-hardened FPGA. Furthermore, we present the details of an emulation test bench supporting various configurations with COTS terrestrial OSPF routers that enabled a realistic performance evaluation of the SATNET-OSPF. Results show that SATNET-OSPF reduced OSPFv3 routing protocol overhead by up to 31%; shortened the link event detection delay by four orders of magnitude; decreased the routing outage by a factor of 22; and ensured flooding control message generation and forwarding times, as well as routing computing time, satisfy the original requirements (192, 37, and 17 ms, respectively).

With the development of the massive satellite constellation and the on-orbit laser-based communication equipment, wavelength routing optical satellite networks (WROSN) becomes a potential solution for on-orbit, high-capacity, and high-speed communication. Since the inter-satellite links (ISLs) are time-varying, one of the fundamental considerations in the construction of the WROSN is assigning limited laser communication terminals for each satellite to establish ISLs with the visible satellites. Therefore, we propose a links assignment scheme (LAS) based on the potential edges importance matrix (PEIM) algorithm to construct a temporarily stable topology for a dual-layer WROSN (DWROSN). The simulation results showed that the LAS based on the PEIM algorithm diminishes the long-hops route path, reduces the average node-to-node distance, and saves the wavelength demand of the DWROSN. The node pair connectivity and wavelength demand in the DWROSN is a trade-off problem. The research in this paper also brings a novel method for optimizing the route paths and reducing the wavelength demand of wavelength routing optical satellite networks, that is through designing the topology with a links assignment algorithm.

The tasks of a space-based information network are complex and diverse, but the resources of a space-based environment are minimal. The existing methods are challenging to match task demand to resource supply accurately. Aiming at the problem of accurate prediction from task to resource, we propose a resource prediction adjustment strategy. First, we propose a multidimensional resource prediction algorithm based on improved particle swarm optimization and back propagation (IPSO-BP) neural network. The improved PSO is used to optimize the weight and threshold of BP neural network to make up for the defects that BP neural network is easy to fall into local minimum and the predicted output value is not unique. Second, to meet the quality of service (QoS) of tasks, we propose a density-based performance evaluation algorithm (DPEA) to adjust resources. This method uses the idea of local sensitive hash to select the evaluation subset for the configuration task, then dynamically selects the $�k$ nearest neighbors of the configuration task, and uses the idea of weighted average to evaluate the QoS performance index of the configuration task. Simulation results show that the proposed resource prediction and adjustment strategy effectively reduces the scheduling time overhead and improves resource utilization.

We define a novel core network router scheduling architecture called priority switching scheduler (PSS), to carry and isolate time constrained and elastic traffic flows from best-effort traffic. To date, one possible solution has been to implement a core DiffServ network with standard fair queuing and scheduling mechanisms as proposed in the well-known “A Differentiated Services Code Point (DSCP) for Capacity-Admitted Traffic” from RFC5865. This architecture is one of the most selected solutions by internet service provider for access networks (e.g., customer-premises equipment) and deployed within several performance-enhancing proxies (PEPs) over satellite communications (SATCOM) architectures. In this study, we argue that the proposed standard implementation does not allow to efficiently quantify the reserved capacity for the AF class. By using a novel credit-based shaper mechanism called burst limiting shaper (BLS) to manage the AF class, we show that PSS can provide the same isolation for the time constrained EF class while better quantifying the part allocated to the AF class. PSS operates both when the output link capacity is fixed (e.g., wire links and terrestrial networks) or might vary due to system impairments or weather condition (e.g., wireless or satellite links). We demonstrate the capability of PSS through an emulated SATCOM scenario with variable capacity and show the AF output rate is less dependent on the EF traffic, which improves the quantification of the reserved capacity of AF, without impacting EF traffic.

Conventional solid-state power amplifier (SSPA) design approach isolates radio frequency (RF) design from communication theory. In this paper, a unified SSPA design approach is proposed, which optimizes SSPA parameters (bias voltage and input RF signal power) to minimize total DC power consumption while satisfying received SNR constraint specified by the link budget. The effect of SSPA nonlinearity is quantified by the error vector magnitude measured at its output and the corresponding received SNR degradation is analyzed. Using the quantitative metrics for received SNR, it is possible to evaluate highly nonlinear SSPA classes such as Class-B or deep-Class AB, which are normally not considered in conventional SSPA design approach to be used in satellite communication applications.

The recent wave of creating an interconnected world through satellites has renewed interest in satellite communications. Private and government-funded space agencies are making advancements in the creation of satellite constellations, and the introduction of 5G has brought a new focus to a fully connected world. Satellites are the proposed solutions for establishing high throughput and low latency links to remote, hard-to-reach areas. This has caused the injection of many satellites in Earth's orbit, which has caused many discrepancies. There is a need to establish highly adaptive and flexible satellite systems to overcome this. Machine Learning (ML) and Deep Learning (DL) have gained much popularity when it comes to communication systems. This review extensively provides insight into ML and DL's utilization in satellite communications. This review covers how satellite communication subsystems and other satellite system applications can be implemented through Artificial Intelligence (AI) and the ongoing open challenges and future directions.