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