Cooperative energy recycling (CER) offers a new way to boost energy utilization in wireless-powered multi-access edge computing (MEC) networks, yet its integration with computation-communication co-design remains underexplored. This paper proposes a CER-enabled MEC framework that maximizes the minimum computable data among users under energy causality, latency, and power constraints. The intractable problem is reformulated into a convex form through relaxation, maximum ratio combining, and variable substitution, and closed-form solutions are derived via Lagrangian duality and alternating optimization, offering analytical insights. Simulation results verify that the proposed CER mechanism markedly increases total computable data while maintaining equitable performance across heterogeneous users.
翻译：协作式能量回收（CER）为提升无线供能多接入边缘计算（MEC）网络的能量利用率提供了新途径，但其与计算-通信协同设计的结合仍待深入探索。本文提出一种支持CER的MEC框架，在能量因果性、时延和功率约束下最大化用户间最小可计算数据量。通过松弛处理、最大比合并及变量代换，将原难解问题重构为凸优化形式，并利用拉格朗日对偶性与交替优化推导出闭式解，从而提供解析性洞见。仿真结果表明，所提出的CER机制在保证异构用户间公平性能的同时，显著提升了总可计算数据量。
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