Maritime Coverage Enhancement Using UAVs Coordinated With Hybrid Satellite-Terrestrial Networks

Abstract

Due to its agile maneuverability, unmanned aerial vehicles (UAVs) have shown great promise for ondemand communications. In practice, UAV-aided aerial base stations are not separate. Instead, they rely on existing satellites/terrestrial systems for spectrum sharing and efficient backhaul. In this case, how to coordinate satellites, UAVs and terrestrial systems is still an open issue. In this paper, we deploy UAVs for coverage enhancement of a hybrid satellite-terrestrial maritime communication network. Under the typical composite channel model including both large-scale and small-scale fading, the UAV trajectory and in-flight transmit power are jointly optimized, subject to constraints on UAV kinematics, tolerable interference, backhaul, and the total energy of UAV for communications. Different from existing studies, only the location-dependent large-scale channel state information (CSI) is assumed available, because it is difficult to obtain the small-scale CSI before takeoff in practice, and the ship positions can be obtained via the dedicated maritime Automatic Identification System. The optimization problem is non-convex. We solve it by problem decomposition, successive convex optimization and bisection searching tools. Simulation results demonstrate that the UAV fits well with existing satellite and terrestrial systems, using the proposed optimization framework. Index TermsHybrid satellite-terrestrial network, maritime communications, power allocation, trajectory, unmanned aerial vehicle (UAV). X. Li, W. Feng (corresponding author), and N. Ge are with the Beijing the UAV's maximum velocity and/or maximum acceleration, the trajectory of UAV was optimized for maximum throughput or minimum UAV periodic flight duration, or optimal energy efficiency [18]-[23]. These works [11]-[23] mainly considered static users. For mobile users, the ergodic achievable rate was maximized by dynamically adjusting the UAV heading [24]-[26]. Intuitively in the maritime scenario, the UAV's trajectory should adaptively cater to the mobility of ships, providing an accompanying broadband coverage, which however remains elusive. 2) Coexistence of UAVs and TBSs: In addition to UAV-only models, the coexistence of UAVs and TBSs was investigated in [27]-[31]. For rotary-wing UAVs, the TBS can be used as a hub to connect UAVs to the network [27]. In this case, the access link and backhaul link should be jointly optimized to maximize the sum rate. In [28], the UAV-based multi-hop backhaul network was formulated to adapt to the dynamics of the network. Outage probability is also an important issue for the coexistence of UAVs and TBSs [29]-[31]. In [30], the outage probability was minimized. In [31], the throughput was maximized subject to the maximum outage probability constraint. For the maritime scenario, the TBS is the primary choice for UAV backhaul, due to their high-speed transmission rate. 3) Coexistence of UAVs and Satellites: More recently, the integration of UAVs and satellites has been investigated in [32]-[37]. Particularly, the aut...

Enabling 5G on the Ocean: A Hybrid Satellite-UAV-Terrestrial Network Solution

“…We assume that only the large-scale CSI is available for the UAV predeployment. The trajectory and the transmit power of the UAV are jointly optimized to maximize the minimum ergodic achievable rate during the period that the UAV serves the vessel, under various practical constraints including the maximum transmit power P max , the residual energy E, the limited backhaul capacity, and the interference temperature limitation I [14]. The goal of maximizing the minimum achievable rate is to improve the coverage performance, i.e., to promote the worst-case user's performance.…”

“…For comparison, the performances of two UAV scheduling algorithms are demonstrated in Fig. 4, including 1) the algorithm in [15], which was designed for the terrestrial scenario and has shown significant gains in improving the performance of cellular networks, and 2) the algorithm proposed in [14], which utilizes only the large-scale CSI, and additionally considered constraints on the interference and maximum transmit power. When I = −40 dBm, the constraint on the interference is looser compared with others, and hence it can be ignored.…”

Environment-Aware Coverage Optimization for Space-Ground Integrated Maritime Communications

“…Particularly, assuming the antennas of a ST are always pointing to the satellite, the antenna directivity θ (j,i) n can be estimated from the satellite's position (as depicted in Fig. 1), and L (j,i) can be calculated according to (6). In addition, the AoD of each scattering path from the n-th CAA of the i-th BS to the j-th ST ϕ (j,i) n,l can be obtained from the locations of scatterers, and T (j,i) can be estimated accordingly.…”

“…The ergodic sum capacity is often restricted by the blind zones and the coverage areas with severe interference, posing great challenges to the design of practical MCNs. Therefore, it is critically important to reconsider the coverage optimization issue for space-ground integrated MCNs [6].…”

Height Optimization in Aerial Networks for Enhanced Broadband Communications at Sea

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