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 : Published 
Date : 2019-10 
Title : An Enhanced Tabu Search based Receiver for Full-spreading NOMA Systems 
Authors : Insik Jung, Hyunsoo Kim, Jinkyo Jung, Sooyong Choi, and Daesik Hong 
Journal : IEEE Access 
Abstract : Full-spreading non-orthogonal multiple access (FS-NOMA) is one category of the candidate technologies designed to support massive connectivity in wireless communication systems. Before it can handle the massive volume of user connections, it is important for the FS-NOMA to develop a receiver that successfully decodes target data from non-orthogonally overlapped receiving signals. However, the decoding performance of conventional interference-cancellation (IC)-based receivers is far from optimal because of error-propagation problems. To improve the decoding performance, we propose a novel FSNOMA receiver based on the tabu-search (TS) algorithm which is a sort of machine-learning algorithm. Specifically, a novel TS mechanism and a diversification scheme are proposed to overcome the inherent adverse conditions of FS-NOMA systems which lead the TS algorithm to local optima. Simulation results demonstrate that the proposed TS-based receiver has decoding performance that is superior to that of the conventional IC-based receiver. The results also show that the proposed receiver accommodates a higher number of user connections with a given packet drop rate threshold. 
URL : https://ieeexplore.ieee.org/document/889...uthoralert 

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» [IEEE Access] Insik Jung, Hyunsoo Kim, Jinkyo Jung, Sooyong Choi, and Daesik Hong, "An Enhanced Tabu Search based Receiver for Full-spreading NOMA Systems", IEEE Access, Oct. 2019 Published  2019-10