Mobile-edge computing (MEC) and wireless power transfer (WPT) have beenrecognized as promising techniques in the Internet of Things (IoT) era toprovide massive low-power wireless devices with enhanced computation capabilityand sustainable energy supply. In this paper, we propose a unified MEC-WPTdesign by considering a wireless powered multiuser MEC system, where amulti-antenna access point (AP) (integrated with an MEC server) broadcastswireless power to charge multiple users and each user node relies on theharvested energy to execute computation tasks. With MEC, these users canexecute their respective tasks locally by themselves or offload all or part ofthem to the AP based on a time division multiple access (TDMA) protocol.Building on the proposed model, we develop an innovative framework to improvethe MEC performance, by jointly optimizing the energy transmit beamformer atthe AP, the central processing unit (CPU) frequencies and the numbers ofoffloaded bits at the users, as well as the time allocation among users. Underthis framework, we address a practical scenario where latency-limitedcomputation is required. In this case, we develop an optimal resourceallocation scheme that minimizes the AP's total energy consumption subject tothe users' individual computation latency constraints. Leveraging thestate-of-the-art optimization techniques, we derive the optimal solution in asemi-closed form. Numerical results demonstrate the merits of the proposeddesign over alternative benchmark schemes.
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