Title   name
2007년 KSIAM 봄 학술대회
  Speaker   Park, Soonchul  
  Date 2007-05-25
  Place KAIST
  File  의 1 번째 Real Media 동영상입니다. 의 1 번째 강연자료입니다.
Abstract : We develop a computationally efficient approximation of the maximum likelihood (ML) detectorfor 16 quadrature amplitude modulation (16-QAM) in multiple-input multiple-output(MIMO) systems. The detector is based on solving a convex relaxation of the ML problemby a box constrained optimization scheme. Simulation results in a random MIMO system showthat this proposed approach outperforms the conventional decorrelator detector and is similarto the semidefinite relaxation (SDR) detector. However, we should note that the complexity ofthe proposed approach is less than that of those detectors. In the case of 8 antennas and 4 users,about 99% fewer computations are required when compared to the SDR and ML detectors.