Computation Rate Maximization in Wireless Powered MEC with Spread Spectrum Multiple Access
| Autor: | Hui Wang, Yuegui Chen, Xiaohui Lin, Suzhi Bi, Xian Li |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Networking and Internet Architecture (cs.NI)
Signal Processing (eess.SP) FOS: Computer and information sciences Optimization problem Mobile edge computing Computer science Code division multiple access business.industry Distributed computing ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS Spread spectrum Computer Science - Networking and Internet Architecture Benchmark (computing) Computer Science::Networking and Internet Architecture FOS: Electrical engineering electronic engineering information engineering Resource allocation Wireless Wireless power transfer Electrical Engineering and Systems Science - Signal Processing business |
| DOI: | 10.48550/arxiv.2002.10258 |
| Popis: | The integration of mobile edge computing (MEC) and wireless power transfer (WPT) technologies has recently emerged as an effective solution for extending battery life and increasing the computing power of wireless devices. In this paper, we study the resource allocation problem of a multi-user wireless powered MEC system, where the users share the wireless channel via direct sequence code division multiple access (DS-CDMA). In particular, we are interested in jointly optimizing the task offloading decisions and resource allocation, to maximize the weighted sum computation rate of all the users in the network. The optimization problem is formulated as a mixed integer non-linear programming (MINLP). For a given offloading user set, we implement an efficient Fractional Programming (FP) approach to mitigate the multi-user interference in the uplink task offloading. On top of that, we then propose a Stochastic Local Search algorithm to optimize the offloading decisions. Simulation results show that the proposed method can effectively enhance the computing performance of a wireless powered MEC with spread spectrum multiple access compared to other representative benchmark methods. Comment: The paper has been accepted for publication by Proc. IEEE ITOEC 2020 |
| Databáze: | OpenAIRE |
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