OFDM Relay Cognitive Radio Multiple Antennas Resource Allocation Full Duplex Spectrum Sensing Synchronization Spectrum Sharing Channel Estimation Interference Cancellation Stochastic Geometry Energy Harvesting Feedback Bi-directional Heterogeneous Networks Equalization HetNet relay networks FBMC Ultra Low Power SC-FDMA TVWS Duplex Reliability CDMA MIMO interference channel capacity in-band full-duplex system interference suppression 5G C-V2V reinforcement learning RSRP weighting non-orthogonal multiple access (NOMA) health care 5G mobile communication indoor positioning Vehicle-to-vehicle communication estimated position overlapping Resource sharing Power allocation multi-access edge computing control overhead hybrid Rat-dependent positioning NR positioning smart factory UFMC Handoff Femtocell QAM CoMP power uncertainty - Computation offloading amplify and forward communication Zigbee body area networks resource block management frame structure WVAN inter user interference GFDM mode selection antenna arrays partial overlap LTE-based V2V resource selection maximum likelihood method Communication range Number of training blocks Vehicular communication Uplink SCMA system Dynamic TDD QR Factorization Metaheuristics FS-NOMA cross-link interference user fairness Multi-user Receiver Mode 3 V2X P-NOMA dynamic HetNet spectrum partitioning DQN D-TDD CLI massive connectivity and 5G networks. OTDOA estimated position updating distributed mode non-orthogonal multiple access Spatial capacity LTE-TDD —Device-to-device (D2D) Location-based overloading
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.
Statussort Date
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