With the increasing global communication demands and the development of Internet of Things (IoT), extending the connectivity to rural and remote areas has become imperative for future networks. The sixth-generation (6G) network is expected to provide heterogeneous services and seamless network coverage for everyone and everything. Combining the advantages of both satellite and terrestrial networks, the integrated satellite-terrestrial network architecture is promising to provide global broadband access for all types of users, which has drawn much attention from both the academia and industry. In this article, we present a comprehensive survey of the state-of-the-art of integrated satellite-terrestrial networks toward 6G. First, an executive classification and summary of the integration architecture is presented from network design to performance optimization. Then, typical applications of the integrated satellite-terrestrial network are discussed based on the architecture. By considering the unique characteristics of the two networks, main challenges are pointed out when performing integration, such as the long propagation delay, complex link conditions, and high dynamics of the network topology. Finally, some promising future techniques are explored from the perspective of the integrated architecture. A detailed survey of the potential integration architectures is of great importance to enable more flexible network design and construction in future 6G networks. This article will provide a valuable guideline on future research and development of integrated satellite-terrestrial networks.

Unmanned aerial vehicles (UAVs) have been widely used in both military and civilian applications. However, the cooperation of small and mini drones in a network is capable of further improving the performance and the coverage area of UAVs. There are numerous new challenges to be solved before the widespread introduction of multi-UAV-based heterogeneous flying ad hoc networks (FANET), including the formulation of a stable network structure. Meanwhile, an efficient gateway-selection algorithm and management mechanism is required. However, the stability control of the hierarchical UAV network guarantees the efficient collaboration of the drones. In this article, we begin by surveying the FANET structure and its protocol architecture. Then, a variety of distributed gateway-selection algorithms and cloud-based stability-control mechanisms are addressed, complemented by a range of open challenges.

Unmanned aerial vehicles (UAVs) have been widely used to provide enhanced information coverage as well as relay services for ground Internet of Things (IoT) networks. Considering the substantially limited processing capability, IoT devices may not be able to tackle with heavy computing tasks. In this paper, a multi-UAV aided mobile edge computing (MEC) system is constructed, where multiple UAVs act as MEC nodes in order to provide computing offloading services for ground IoT nodes which have limited local computing capabilities. For the sake of balancing the load for UAVs, the differential evolution (DE) based multi-UAV deployment mechanism is proposed, where we model the access problem as a generalized assignment problem (GAP), which is then solved by a near-optimal solution algorithm. Based on this, we are capable of achieving the load balance of these drones while guaranteeing the coverage constraint and satisfying quality of service (QoS) of IoT nodes. Furthermore, a deep reinforcement learning (DRL) algorithm is conceived for the task scheduling in a certain UAV, which improves the efficiency for the task execution in each UAV. Finally, sufficient simulation results show the feasibility and superiority of our proposed load-balance oriented UAV deployment scheme as well as the task scheduling algorithm.

Unmanned aerial vehicles (UAVs) have been widely used in both military and civilian applications. Equipped with diverse communication payloads, UAVs cooperating with satellites and base stations (BSs) constitute a space-air-ground three-tier heterogeneous network, which are beneficial in terms of both providing the seamless coverage as well as of improving the capacity for increasingly prosperous Internet of Things (IoT) networks. However, cross-tier interference may be inevitable among these tightly embraced heterogeneous networks when sharing the same spectrum. The power association problem in satellite, UAV and macrocell three-tier networks becomes a critical issue. In our paper, we propose a two-stage joint hovering altitude and power control solution for the resource allocation problem in UAV networks considering the inevitable cross-tier interference from space-air-ground heterogeneous networks. Furthermore, Lagrange dual decomposition and concave-convex procedure (CCP) method are used to solve this problem, followed by a low-complexity greedy search algorithm. Finally, simulation results show the effectiveness of our proposed two-stage joint optimization algorithm in terms of UAV network’s total throughput.