Hierarchical Cognitive Spectrum Sharing in Space-Air-Ground Integrated Networks

• Published in: IEEE International Conference on Communications (2003) pp. 385 - 390
• Main Authors: Zhou, Zizhen, Zhang, Qianqian, Ge, Jungang, Liang, Ying-Chang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 09.06.2024
• Subjects: Array signal processing; Base stations; Interference; Quality of service; Satellites; Simulation; Space-air-ground integrated networks
• ISSN: 1938-1883
• DOI: 10.1109/ICC51166.2024.10622415

Cognitive spectrum sharing has been regarded as a promising solution to improve spectrum utilization efficiency for space-air-ground integrated networks (SAGINs). However, in SAGIN, different networks may have different quality of service (QoS) requirements, which pose challenges to the traditional cognitive spectrum sharing architecture. For example, the aerial network typically has high QoS requirements, which may not be met when it acts as a secondary network. To address this issue, we propose a hierarchical cognitive spectrum sharing architecture (HCSSA) for SAGIN, where the secondary networks are divided into a preferential one and an ordinary one. Specifically, in SAGIN, an aerial network and a terrestrial network share the spectrum of a satellite network. HCSSA gives higher priority to the aerial network by a QoS constraint, while the terrestrial network is the ordinary secondary network without protection. Besides, the satellite terminal requires the received interference to be below a threshold. Subject to these two constraints and the maximum transmit power constraints, we aim to maximize the sum rate of the terrestrial network by optimizing the transmit beamforming vectors of the aerial base station (BS) and the terrestrial BSs. To solve this non-convex problem, we propose an iterative beamforming scheme by exploiting the penalty method and the successive convex approximation scheme. Simulation results show the performance of the proposed beamforming scheme and illustrate the advantages of HCSSA compared with the traditional cognitive spectrum sharing architecture.