OFDM Multiple Antennas Cognitive Radio Relay CDMA Synchronization Channel Estimation Spectrum Sharing Interference Cancellation Resource Allocation Spectrum Sensing Neural Networks Full duplex Stochastic Geometry Equalizer Bi-Directional Feedback Energy Harvesting Heterogeneous Networks Femtocell Device-to-Device (D2D) Idle cells Cross-link interference FBMC Spectral efficiency Cell Search SINR mismatch problem NOMA Ultra-dense small cell networks HetNet interference management Dynamic TDD outage probability selection diversity achievable sum rate bursty traffic model Cognitive relay networks mode selection multi-spectral 5G Complexity Singular Vale Decomposition OQAM tabu-search Filtered OFDM TDD configuration flexible duplex Handoff GFDM Heterogeneous channel estimation capability self-interference cancellation in-band full-duplex system Channel estimation error coexistence CP-OFDM MU-MIMO automatic repeat request (ARQ) Two-way communications UWB full-duplex relay full-duplex cellular Simultaneous Sensing and Transmission Correlated MIMO transmission capacity (TC) sensing duration Bi-directional full-duplex Vehicle-to-Vehicle prototype filter pilot signal Coexistence scenarios resource size control Vehicle-to-vehicle communication link reliability interference to noise ratio eigen decomposition TS-W-OFDM Resource management Cooperative systems LTE-based V2V Aggregate interference time-frequency efficiency mixed numerology Windowing Reliability C-V2V Asynchronous Transmission Full-duplex Computation offloading Grant-free Transmission Preamble full-spreading NOMA massive connectivity Edge computing Multiple access MLP Deep learning Railway Mobility interference mitigation HST non-orthogonal multiple access
Status : Accepted 
Date : 2021-09 
Title : Resource Configuration for Full-duplex-aided Multiple-Access Edge Computation Offloading 
Authors : Hakkeon Lee, Jaeyoung Choi, and Daesik Hong 
Journal : IEEE Transactions on Wireless Communications 
Abstract : Multiple-access edge computation offloading (MECO) systems have been highlighted as a solution for extending the battery life and computation capability of mobile devices. However, in scenarios where information data and computation offloading (CO) data coexist, CO users and information users affect each other. It means that the communication resources for information data transmission are inevitably reduced by the communication resources allocated for CO in the conventional half-duplex (HD) based systems. Hence, improving the spectral efficiency of MECO systems in coexistence scenarios is essential, and we investigate a full-duplex (FD)-aided MECO (FD-MECO) system. A step-wise resource configuration is proposed to improve the performance of computation offloading under the information data rate constraint. The main idea is to improve spectral efficiency by maximizing the opportunity of operating in FD mode. By comparing all the communication phases in FD-MECO systems, the proposed resource configuration maximizes the amount of delivered CO data while guaranteeing the required information data rate. The simulation results show that FD-MECO systems with the proposed resource configuration always outperform HD-MECO systems. 

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» [IEEE Trans. Wireless Commun.] Hakkeon Lee, Jaeyoung Choi, and Daesik Hong, "Resource Configuration for Full-duplex-aided Multiple-Access Edge Computation Offloading" in IEEE Transactions on Wireless Communications, September 2021 Accepted  2021-09