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That alleviating the heavy computing task, improving spectral efficiency and prolonging battery lifetime have been the key design challenges in Internet of Things (IoT) and intelligent connected vehicles (ICV). This paper studies the optimization of communication, computation and energy resource to minimize the energy consumption in the mobile terminal, where some superior technologies are included, such as Full-Duplex (FD), Simultaneous Wireless Information and Power Transfer (SWIPT), Mobile-Edge Computing (MEC) and Multi-input Multi-output (MIMO). In this model, the MEC-assisted Base station (BS) works in FD mode, then it can transmit and receive signals in the same frequency and time. Moreover, the mobile devices offload some computation tasks to the BS and complete local computations at the same time. Besides, the mobile device harvests the energy from the BS to support its energy consumption. And, our target is to minimize the energy consumption of mobile devices. Since the problem is non-convex, we propose an iterative solving algorithm including a multi-step optimization. First, we obtain the closed-form solution of the CPU frequency. And then, we transform the remain problem into a convex one to solve it by the interior point algorithm. Finally, we obtain the approximate solution by multiple iterations. Simulation results show that the proposed algorithm is superior to the compared schemes. INDEX TERMS Mobile-edge computing, simultaneous wireless information and power transfer, multi-input multi-output, full-duplex, multi-step iteration, vehicular communications.

Summary In order to achieve flexible configuration and asynchronous transmission of different subbands (SBs), SB filters are utilized in filtered orthogonal frequency division multiplexing (f‐OFDM) systems to isolate different SBs efficiently. Nevertheless, the price is the insertion of some intrinsic interference.Therefore, the suppression of the out‐of‐band emission (OOBE) between SBs is essential for the system performance improvement of f‐OFDM. According to the system structure of f‐OFDM, an optimization design model based on active interference cancelation (AIC) is proposed in this study, and the optimization design model is solved through second order cone programming. Furthermore, the effectiveness of the proposed AIC algorithm in OOBE suppression is verified by computer simulations. To the whole system, the OOBE suppression also means the decrease of inter‐SB interference (ITBI). In addition, the influences of main parameters, such as the number of the cancelation carriers (CCs), on the OOBE suppression performance of the proposed AIC algorithm, are simulated and analyzed. Moreover, some intrinsic characteristics of the proposed algorithm in parameter configuration are revealed in terms of power spectral density (PSD) and bit error ratio (BER).