Mobile edge computing (MEC) is envisioned as a promising technology for enhancing the computation capacities and prolonging the lifespan of mobile devices, by enabling mobile devices to offload computation-intensive tasks to servers in close proximity. For wireless communication, MEC introduces a new scenario, where computations are performed directly at the receiving side of the wireless links. Our objective is therefore to evaluate the importance of joint radio-and-computational resource allocation and spectral efficiency enhancing techniques in this new scenario. We formulate the resource allocation problem to minimize the energy consumption of computation offloading of delay sensitive tasks and propose near-optimal solutions for both orthogonal and non-orthogonal multiple access schemes, with the optimal joint allocation of computing resources and transmission power. Our numerical results demonstrate the superiority of non-orthogonal multiple access over its orthogonal counterpart and the importance of joint resource allocation, especially in scenarios with strict delay limits, where both the transmission and the computational resources are scarce.

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Industrial automation has been recently challenged by new initiatives such as Industry 4.0, which promises higher connectivity between the devices in an industrial plant. The goal of this work is to discuss how electric drives, widely employed in industry, could benefit from this increased connectivity. Specific applications, such as condition monitoring and multidrive systems, are considered to show the advantages of the industrial network presence, combined with the introduction of new data driven methods. Moreover, the status of industrial communication technologies is depicted, and their suitability for condition monitoring and multi-drive systems applications is described.

Abstract-In hierarchical cognitive radio networks, unlicensed secondary users can increase their achievable rates by assisting licensed primary user transmissions via cooperation. In this paper, a novel approach to maximize the transmission rates in the secondary network by optimizing the relay selection, the secondary transmit powers, and the cooperative relaying power splitting parameters is proposed. The resulting optimization problem is mixed integer and non-convex, which makes it NP hard to find the optimal solutions. Therefore, centralized and distributed solution methods to find near-to-optimal solutions of this challenging problem are proposed. The methods are based on iteratively solving the secondary relay selection by a greedy approach, and the optimal power allocation problem by a fixedpoint approach together with alternating direction method of multipliers. It is established that both centralized and distributed solution methods always converge. The numerical results illustrate the performance of the proposed solution methods, and show that they give a near-to-optimal solution. Moreover, the performance margins of the primary transmitters that permit the accommodation of relaying secondary users, still having high achievable transmit rates, are characterized.

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