基于多目标优化的星空融合网络波束成形算法

Multi-objective Beamforming Algorithm for Integrated Satellite and Aerial Networks

将卫星通信网和无人机通信网有机结合构成的星空融合网络,具有覆盖范围广、通信容量大、组网方便快捷等众多优势,在未来第六代移动通信领域显示了广阔的应用前景。与此同时,采用太赫兹频段进行无线传输,被认为是解决当前无线通信领域频谱效率偏低、系统容量受限等问题的有效手段。针对工作在太赫兹频段的星空融合网络,在卫星网络和无人机网络分别采用多播技术和层分复用技术,且它们共享频谱资源的条件下,提出了一种基于多目标优化的波束成形方案,以满足用户的差异化服务需求。首先,建立卫星和无人机发射功率受限,且各类用户的服务质量得到保证为约束条件,系统的和速率最大化与总发射功率最小化为目标函数的多目标优化问题。其次,通过加权切比雪夫法,将数学上非常复杂的多目标问题转换为单目标问题,并进一步提出基于凹凸过程的迭代算法处理非凸约束,得到帕累托最优解。最后,计算机仿真验证了所提算法采用层分复用技术能够有效提高系统的频谱效率,从而证实了所提算法的优越性。

Combining the satellite and aerial networks,the integrated satellite and aerial network with the advantages of wide coverage,large communication capacity,convenient and fast networking has shown a broad application prospect in the field of sixth generation mobile communication.At the same time,using terahertz frequency band for wireless transmis⁃sion is considered to be an effective means to solve the problems of low spectrum efficiency and limited system capacity in the current wireless communication field.In this paper,a multi-objective beamforming scheme is proposed to support het⁃erogeneous service in Terahertz integrated satellite and aerial networks.Specifically,the satellite network shares the spec⁃trum resources with the aerial network and adopts multicast technique to serve satellite users,while the aerial network offers services to multiple aerial users through layer division multiplexing.Under this setup,we first formulate a multiobjective optimization problem(MOOP)to achieve a good trade-off between sum rate maximization and total transmit power minimization under the constraints of the users’quality of service,satellite and UAV transmit power budgets.Then,we exploit the weighted Tchebycheff approach to transform the complicated MOOP into a single-objective problem.Furthermore,an iterative algorithm based on concave-convex process is proposed to deal with non-convex constraints,and the Pareto optimal solution is obtained.Finally,computer simulation verifies that the proposed algorithm can effectively improve the spectrum efficiency of the system by using layer division multiplexing technology,thus proving the superiority of the proposed algorithm.