4.7 Article

Dynamic Transmission and Computation Resource Optimization for Dense LEO Satellite Assisted Mobile-Edge Computing

期刊

IEEE TRANSACTIONS ON COMMUNICATIONS
卷 71, 期 5, 页码 3087-3102

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2023.3253721

关键词

Energy consumption; Satellites; Costs; Simulation; Precoding; Transforms; Resource management; Lyapunov optimization; mobile edge computing; MIMO; resource allocation; dense satellite

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In order to meet the computing demands for next generation networks, a dense satellite-terrestrial integrated mobile-edge computing network (SATIMECN) architecture is developed. The optimization problem is transformed into a deterministic one using Lyapunov optimization theory. The problem is decomposed into four subproblems and each one is solved iteratively.
A dense satellite-terrestrial integrated mobile-edge computing network (SATIMECN) architecture is developed to meet the computing demands for next generation networks. We formulate an average weighted sum energy consumption minimization problem by jointly considering task ratio allocation of computing or offloading at local and the gateway (GW), ground user terminal (GUT)-satellite association relation, GUT multiple-input and multiple-output (MIMO) precoding, and computation resource allocation at local and the GW. Due to the stochastic property of the optimization problem, we adopt Lyapunov optimization theory to transform it into a deterministic one. Then, we decompose the optimization problem into four subproblems and solve each one iteratively. Specifically, task ratio allocation of computing or offloading at local and the GW is obtained in a closed-form expression using the delay constraint. Then, the binary GUT-satellite association subproblem is solved by the weighted minimum mean-squared error and quadratic transform based fractional programming (QTFP) methods. Moreover, the MIMO precoding subproblem is solved by QTFP and interior point methods. Finally, the computation resource allocation subproblem for local and edge computing is derived in closed-form expressions. Simulation results demonstrate that the tradeoff between the average weighted sum energy consumption and the average queue length can be realized by adjusting the Lyapunov control parameter. Moreover, the proposed MIMO communication and frequency reuse schemes for dense satellite network can realize efficient computation offloading with relative low cost.

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