TY - GEN
T1 - Nonlinear programming based detectors for multiuser systems
AU - Yener, A.
N1 - Publisher Copyright:
© 2001 IEEE.
PY - 2001
Y1 - 2001
N2 - Maximum likelihood (ML) detection problems for several multiuser systems result in nonlinear optimization problems with unacceptably high complexity. One way of achieving near-optimum performance without the complexity associated with the ML detector is using nonlinear programming relaxations to approximate the solution of the ML detection problem at hand. Using this approach, new detectors are formulated and it is observed that some popular suboptimum receivers correspond to relaxations of the ML detectors. We concentrate on two types of systems to demonstrate this concept and evaluate the performance of the resulting detectors.
AB - Maximum likelihood (ML) detection problems for several multiuser systems result in nonlinear optimization problems with unacceptably high complexity. One way of achieving near-optimum performance without the complexity associated with the ML detector is using nonlinear programming relaxations to approximate the solution of the ML detection problem at hand. Using this approach, new detectors are formulated and it is observed that some popular suboptimum receivers correspond to relaxations of the ML detectors. We concentrate on two types of systems to demonstrate this concept and evaluate the performance of the resulting detectors.
UR - http://www.scopus.com/inward/record.url?scp=84961784563&partnerID=8YFLogxK
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U2 - 10.1109/ITCC.2001.918815
DO - 10.1109/ITCC.2001.918815
M3 - Conference contribution
AN - SCOPUS:84961784563
T3 - Proceedings - International Conference on Information Technology: Coding and Computing, ITCC 2001
SP - 327
EP - 331
BT - Proceedings - International Conference on Information Technology
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - International Conference on Information Technology: Coding and Computing, ITCC 2001
Y2 - 2 April 2001 through 4 April 2001
ER -