English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Non-terrestrial networks (NTNs), which integrate space and aerial networkswith terrestrial systems, are a key area in the emerging sixth-generation (6G)wireless networks. As part of 6G, NTNs must provide pervasive connectivity to awide range of devices, including smartphones, vehicles, sensors, robots, andmaritime users. However, due to the high mobility and deployment of NTNs,managing the space-air-sea (SAS) NTN resources, i.e., energy, power, andchannel allocation, is a major challenge. The design of a SAS-NTN forenergy-efficient resource allocation is investigated in this study. The goal isto maximize system energy efficiency (EE) by collaboratively optimizing userequipment (UE) association, power control, and unmanned aerial vehicle (UAV)deployment. Given the limited payloads of UAVs, this work focuses on minimizingthe total energy cost of UAVs (trajectory and transmission) while meeting EErequirements. A mixed-integer nonlinear programming problem is proposed,followed by the development of an algorithm to decompose, and solve eachproblem distributedly. The binary (UE association) and continuous (power,deployment) variables are separated using the Bender decomposition (BD), andthen the Dinkelbach algorithm (DA) is used to convert fractional programminginto an equivalent solvable form in the subproblem. A standard optimizationsolver is utilized to deal with the complexity of the master problem for binaryvariables. The alternating direction method of multipliers (ADMM) algorithm isused to solve the subproblem for the continuous variables. Our proposedalgorithm provides a suboptimal solution, and simulation results demonstratethat the proposed algorithm achieves better EE than baselines.

Seamless and Energy Efficient Maritime Coverage in Coordinated 6G Space-Air-Sea Non-Terrestrial Networks