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As an emerging network architecture and technology, mobile edge computing (MEC) can alleviate the tension between the computation-intensive applications and the resource-constrained mobile devices. However, most available studies on computation offloading in MEC assume that the edge severs host various applications and can cope with all kinds of computation tasks, ignoring limited computing resources and storage capacities of the MEC architecture. To make full use of the available resources deployed on the edge servers, in this paper, we study the cross-server computation offloading problem to realize the collaboration among multiple edge servers for multi-task mobile edge computing, and propose a greedy approximation algorithm as our solution to minimize the overall consumed energy. Numerical results validate that our proposed method can not only give near-optimal solutions with much higher computational efficiency, but also scale well with the growing number of mobile devices and tasks. [ABSTRACT FROM AUTHOR]

Orthogonal frequency-division multiplexing (OFDM) is an attractive multicarrier technique for the simplicity of equalization and high data throughput. However, the transmitted OFDM signal has a very high peak-to-average power ratio (PAPR), which severely degrades the performance of practical OFDM systems and reduces the efficiency of high-power amplifiers (HPA). The selected mapping (SLM) scheme is an effective PAPR reduction method of OFDM signals. However, this approach usually requires side information (SI) transmission, which increases the difficulty of the hardware implementation with high complexity and reduces the data transmission rate. In this paper, based on designing phase rotation vectors in the time domain, a novel blind SLM method with low complexity is proposed to reduce the PAPR of OFDM signals. At the transmitter, the proposed method properly designs the phase rotation vectors in the time domain, which can be considered as an equivalent wireless channel without SI transmission. At the receiver, the effect of phase rotation vectors can be removed by the conventional channel estimation method, and the data demodulation processing can be easily performed by the frequency domain equalization. Simulation results show that the proposed scheme can achieve low complexity in PAPR reduction and has great robustness in bit error rate (BER) performance compared to the other low-complexity SLM PAPR schemes. [ABSTRACT FROM AUTHOR]