OFDM Multiple Antennas Cognitive Radio Relay CDMA Synchronization Channel Estimation Spectrum Sharing Interference Cancellation Neural Networks Spectrum Sensing Full duplex Resource Allocation Stochastic Geometry Equalizer Feedback Bi-Directional Energy Harvesting Femtocell Heterogeneous Networks Device-to-Device (D2D) Cell Search FBMC HetNet Idle cells Ultra-dense small cell networks Spectral efficiency SINR mismatch problem automatic repeat request (ARQ) in-band full-duplex system Two-way communications transmission capacity (TC) Correlated MIMO sensing duration self-interference cancellation Simultaneous Sensing and Transmission full-duplex cellular multi-spectral beamforming UWB achievable sum rate outage probability Cognitive relay networks selection diversity full-duplex relay Latency Vehicular and wireless technologies Asynchronized system Cross-link interference Cellular networks coexistence Channel estimation error Ultra-dense small cell Shortened TTI UL grant free NOMA mode selection Bi-directional full-duplex OQAM Link adaptation Iterative decoder LTE-TDD Dynamic TDD bursty traffic model Filtered OFDM MIMO singular value decomposition Time spreading K-S statistics interference coordination Vehicle-to-vehicle communication eigen decomposition 5G networks GFDM MU-MIMO TS-W-OFDM prototype filter pilot signal Windowing time-frequency efficiency Long Term Evolution-Advanced Aggregate interference LTE-based V2V Resource management Coexistence scenarios resource size control interference to noise ratio interference management mixed numerology Reliability Cooperative systems link reliability C-V2V non-orthogonal multiple access full-spreading NOMA massive connectivity Complexity CP-OFDM Vehicle-to-Vehicle Singular Vale Decomposition tabu-search
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