Jiaxin Zhang

The ongoing evolution toward sixth-generation (6G) communications necessitates the deep integration of terrestrial and non-terrestrial infrastructures into the seamless Space–Air–Ground–Sea Integrated Network

With the rapid growth of global traffic and the construction of large-scale low-orbit satellites, the hybrid network of multi-tier LEO satellite has become the future trend, which also brings challenges to satellite routing. In this paper, we propose a flexible satellite cross-tier routing method under the control of gateway, considering on-board processing ability and satellite congestion to realize low lantency routing. Firstly, we model the multi-tier satellite constellations as Marked Poission Point Process (MPPP), in which each tier follows Poission Point Process (PPP) distribution with marked different satellite queueing length. Then, the analytical expressions of routing outage probability, end-to-end delay are derived, considering search radius, packet arrival rate, routing distance and inter-tier distance. Finally, the search range expansion approach is proposed to solve the problem of traffic congestion, and the trade-off between routing success probability and search range deflection angle is obtained. Numerical results show that the cross-tier routing mechanism can significantly reduce the routing outage probability under high load and reduce the end-to-end delay under medium load respectively. In addition, the search range expansion approach can significantly reduce the routing outage probability without influencing the sum delay significantly. This work is expected to be instructive to the future sixth generation (6G) network.

With the rapid development of satellite on-board processing, caching capability, and the inter-satellites link (ISL) transmission capacity, the 6th generation mobile networks (6G) has been expected to provide global coverage for the consumer electronics. In this paper, for the purpose of content caching and delivery to the consumer user equipment (UE), an end-to-end satellite-terrestrial integrated network with the multi-edge access and cache strategy is proposed, under the split of the control-plane (C-plane) and the user-plane (U-plane) with the software-defined features. Assuming the popularity of the contents follow the typical Zipf distribution, with three main cases are categorized and compared. In addition, the analytical expressions of service coverage probability and network service throughput are derived and analyzed, as the functions of key parameters, including the next Generation Node B (gNB) density, cache ability, access radius and Quality-of-Service (QoS) threshold. Numerical results show that the collaboration between the distributed unit (DU) and centralized unit (CU) with the joint access and caching strategy in the proposed system can significantly improve the service coverage probability and overall throughput of the network. Trade-offs between both the gNB density and the access radius with the key network performances are illustrated.

Self-organizing networks of small satellites have gradually gained attention in recent years. However, self-organizing networks of small satellites have high topological change frequency, large transmission delay, and complex communication environments, which require appropriate networking and routing methods. Therefore, this paper, considering the characteristics of satellite networks, proposes the shortest queue length-cluster-based routing protocol (SQL-CBRP) and has built a satellite self-organizing network simulation platform based on OMNeT++. In this platform, functions such as the initial establishment of satellite self-organizing networks and cluster maintenance have been implemented. The platform was used to verify the latency and packet loss rate of SQL-CBRP and to compare it with Dijkstra and Greedy Perimeter Stateless Routing (GPSR). The results show that under high load conditions, the delay of SQL-CBRP is reduced by up to 4.1%, and the packet loss rate is reduced by up to 7.1% compared to GPSR. When the communication load is imbalanced among clusters, the delay of SQL-CBRP is reduced by up to 12.7%, and the packet loss rate is reduced by up to 16.7% compared to GPSR. Therefore, SQL-CBRP performs better in networks with high loads and imbalance loads.

The network densification of small cells (SCs) is a promising way to cope with the explosive growth of future traffic demands in 5G networks. However, the overall power consumption and the backhaul limitation of the network have become the key factors affecting the network performance and users' quality-of-experience, which have great importance in 5G wireless networks. Due to the complexity of 5G networks and the variety of user behaviors, the combination of software-defined networks and content delivery strategy could be a more efficient way to manage such networks. In this paper, a cache-enabled wireless heterogeneous network with the control-plane (C-plane) and user-plane (U-plane) split is proposed, where the macro cell and SCs with different cache abilities are overlaid and cooperated together in the backhaul scenario. Using an evaluation tool composed of stochastic processes and classical power consumption model, key performance indicators, e.g., the coverage probability, throughput, and energy efficiency (EE), are derived as closed-form expressions or the functions of the signal-to-interference-plus-noise ratio threshold, path loss exponent, transmission power and density of macro and SCs, cache ability, file popularity, and backhaul capacity. Fundamental trade-offs are illustrated between EE and transmission power, EE and SC density, as well as the throughput and density of SCs. Numerical results show that the proposed cache-enabled software-defined networks have much higher throughput and improved EE than current LTE networks, which shows a promising solution for future cellular networks.