OFDM Multiple Antennas Cognitive Radio Relay CDMA Synchronization Channel Estimation Spectrum Sharing Interference Cancellation Full duplex Spectrum Sensing Resource Allocation Neural Networks Stochastic Geometry Equalizer Bi-Directional Feedback Femtocell Energy Harvesting Heterogeneous Networks Device-to-Device (D2D) Cross-link interference Cell Search SINR mismatch problem Ultra-dense small cell networks HetNet Idle cells Spectral efficiency Dynamic TDD interference management NOMA FBMC selection diversity Handoff outage probability mode selection B5G multi-spectral achievable sum rate Grant-free Transmission Filtered OFDM tabu-search bursty traffic model flexible duplex 5G Asynchronous Transmission Preamble Deep learning Shortened TTI automatic repeat request (ARQ) Two-way communications transmission capacity (TC) in-band full-duplex system self-interference cancellation Complexity Ultra-dense small cell sensing duration Correlated MIMO Cognitive relay networks Heterogeneous channel estimation capability Bi-directional full-duplex full-duplex cellular full-duplex relay Simultaneous Sensing and Transmission UWB OQAM Windowing Vehicle-to-vehicle communication prototype filter pilot signal LTE-based V2V link reliability resource size control interference to noise ratio eigen decomposition TS-W-OFDM C-V2V massive connectivity Reliability Vehicle-to-Vehicle full-spreading NOMA Resource management Cooperative systems Coexistence scenarios mixed numerology 6G Cell-free Coexisting network Multiple access Railway CP-OFDM MLP Edge computing Full-duplex Mobility non-orthogonal multiple access HST interference mitigation Computation offloading TDD configuration Singular Vale Decomposition
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