TY - JOUR
T1 - Resource Allocation and Management in Multisatellite Collaborative Networks
T2 - Frameworks, Key Techniques, and Challenges
AU - Zhang, Jie
AU - Yang, Liang
AU - Wu, Qingqing
AU - Pan, Gaofeng
AU - Xu, Lexi
AU - Niyato, Dusit
AU - Alouini, Mohamed Slim
N1 - Publisher Copyright:
© 1986-2012 IEEE.
PY - 2026/8/1
Y1 - 2026/8/1
N2 - With the rapid deployment of hybrid mega-constellations, efficient resource allocation (RA) in multisatellite collaborative (MSC) networks has become critical to support diverse, delay-sensitive, and computation-intensive services. This article presents a structured three-tier collaboration framework, intraorbit, interorbit, and heterogeneous satellite collaboration to transform static RA into adaptive, multitimescale optimization. We analyze three fundamental challenges that distinguish MSC networks from terrestrial systems: highly dynamic topology, multidimensional onboard resource coupling (power, spectrum, computation, and caching), and complex 3D interference. For each challenge, we survey optimization techniques (convex programming, game theory, and deep reinforcement learning) and key enabling mechanisms, including dynamic spectrum management, joint power/beamforming control, routing and handover, computing resource scheduling, reconfigurable intelligent surface-assisted beamforming, and advanced multiple access. Furthermore, a case study of RA under the proposed MSC framework is presented and realistic constraints are discussed. Finally, we highlight open problems, collaboration formation, green communications, security/privacy, and outline directions for future research.
AB - With the rapid deployment of hybrid mega-constellations, efficient resource allocation (RA) in multisatellite collaborative (MSC) networks has become critical to support diverse, delay-sensitive, and computation-intensive services. This article presents a structured three-tier collaboration framework, intraorbit, interorbit, and heterogeneous satellite collaboration to transform static RA into adaptive, multitimescale optimization. We analyze three fundamental challenges that distinguish MSC networks from terrestrial systems: highly dynamic topology, multidimensional onboard resource coupling (power, spectrum, computation, and caching), and complex 3D interference. For each challenge, we survey optimization techniques (convex programming, game theory, and deep reinforcement learning) and key enabling mechanisms, including dynamic spectrum management, joint power/beamforming control, routing and handover, computing resource scheduling, reconfigurable intelligent surface-assisted beamforming, and advanced multiple access. Furthermore, a case study of RA under the proposed MSC framework is presented and realistic constraints are discussed. Finally, we highlight open problems, collaboration formation, green communications, security/privacy, and outline directions for future research.
KW - Multi-satellite collaborative (MSC) networks
KW - optimization techniques
KW - resource allocation (RA)
UR - https://www.scopus.com/pages/publications/105039242249
U2 - 10.1109/MAES.2026.3691337
DO - 10.1109/MAES.2026.3691337
M3 - Article
AN - SCOPUS:105039242249
SN - 0885-8985
VL - 41
SP - 46
EP - 58
JO - IEEE Aerospace and Electronic Systems Magazine
JF - IEEE Aerospace and Electronic Systems Magazine
IS - 8
ER -