OFDM Relay Cognitive Radio Multiple Antennas Resource Allocation Full Duplex Spectrum Sensing Synchronization Spectrum Sharing Interference Cancellation Channel Estimation Feedback Heterogeneous Networks Bi-directional Energy Harvesting Stochastic Geometry HetNet relay networks FBMC Equalization channel capacity TVWS CDMA interference in-band full-duplex system Duplex MIMO Ultra Low Power C-V2V 5G Reliability SC-FDMA interference suppression D-TDD CLI indoor positioning reinforcement learning RSRP weighting - Computation offloading smart factory Cell-free multi-access edge computing estimated position overlapping —Device-to-device (D2D) estimated position updating mMIMO control overhead hybrid NR positioning Femtocell Rat-dependent positioning frame structure Zigbee body area networks channel estimation error Handoff CoMP User grouping power uncertainty ultra-dense small cell network mode selection antenna arrays 5G mobile communication UFMC resource block management inter user interference WVAN health care partial overlap GFDM Dynamic TDD Multi-user Receiver Number of training blocks Uplink SCMA system V2X Vehicular communication cross-link interference LTE-TDD FS-NOMA Location-based user fairness Mode 3 QR Factorization Metaheuristics P-NOMA non-orthogonal multiple access dynamic HetNet spectrum partitioning and 5G networks. massive connectivity non-orthogonal multiple access (NOMA) overloading DQN OTDOA distributed mode Communication range resource selection maximum likelihood method Resource sharing Power allocation packet delay
Status : Presented 
Date : 2010-05 
Title : A New Grouping-ML Detector with Low Complexity for SC-FDMA Systems 
Authors : Sungmook Lim, Taehoon Kwon, Jemin Lee and Daesik Hong 
Conference : IEEE ICC 2010 
Abstract : In this paper, we propose a new grouping-maximum likelihood detector (GMLD) for single carrier-frequency division multiple access (SC-FDMA) systems. The proposed detector performs local maximum likelihood (ML) detection by grouping the received symbol block based on orthogonal projection to reduce the complexity of ML detector. As a result, the proposed detector offers lower complexity than the ML detector, while its performance approaches that of the ML detector. In addition, the efficient group size to guarantee the lowest complexity and the BER performance close to the ML is also presented. 
URL : http://ieeexplore.ieee.org/xpl/articleDe...MA+Systems 
Download : http://mirinae.yonsei.ac.kr/?module=file...323925ff4a 

Sungmook Lim; Taehoon Kwon; Jemin Lee; Daesik Hong; , "A New Grouping-ML Detector with Low Complexity for SC-FDMA Systems,"Communications (ICC), 2010 IEEE International Conference on , vol., no., pp.1-5, 23-27 May 2010
doi: 10.1109/ICC.2010.5502813
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5502813&isnumber=5501741

List of Articles
No.
Status Datesort
2 [IEEE VTC] Sungmook Lim, Jemin Lee, Taehoon Kwon, Woohyun Seo and Daesik Hong, "A ML-based Detector considering Transmit Power Allocation for SC-FDMA Systems", VTC 2011, May 2011 file Presented  2011-05 
» [IEEE ICC] Sungmook Lim, Taehoon Kwon, Jemin Lee and Daesik Hong, "A New Grouping-ML Detector with Low Complexity for SC-FDMA Systems", IEEE ICC 2010, Dec. 2009 file Presented  2010-05