TY - GEN
T1 - Complexity reduced SBI estimation in iterative MIMO systems
AU - Ahmed, Saleem
AU - Zhang, Meixiang
AU - Waheed Umrani, Abdul
AU - Kim, Sooyoung
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016
Y1 - 2016
N2 - In this paper, we demonstrate the performance of low complexity soft interference cancellation minimum mean-squared error (SIC-MMSE) detection method for a turbo coded multiple-input multiple-output (MIMO) system with joint iterative detection and decoding (JIDD) principle. The main computational burden of SIC-MMSE detector lies in the multiple inverse operation of the filtering process and maximum a posteriori (MAP) based soft bit information (SBI) estimation. In order to reduce the complexity we apply hybrid approach for SBI estimation. Based on the reliability of soft information provided by channel decoder, the SBI estimation process is switched between the hard decision threshold based (HDT) method with a single distance calculation and a MAP based estimation. Furthermore, we employ a scaling method for the HDT method which can reduce the over estimated SBI values, resulting in performance improvement. Simulation results show that the hybrid approach for SIC-MMSE method highly reduces computational complexity, without appreciable bit error rate performance degradation.
AB - In this paper, we demonstrate the performance of low complexity soft interference cancellation minimum mean-squared error (SIC-MMSE) detection method for a turbo coded multiple-input multiple-output (MIMO) system with joint iterative detection and decoding (JIDD) principle. The main computational burden of SIC-MMSE detector lies in the multiple inverse operation of the filtering process and maximum a posteriori (MAP) based soft bit information (SBI) estimation. In order to reduce the complexity we apply hybrid approach for SBI estimation. Based on the reliability of soft information provided by channel decoder, the SBI estimation process is switched between the hard decision threshold based (HDT) method with a single distance calculation and a MAP based estimation. Furthermore, we employ a scaling method for the HDT method which can reduce the over estimated SBI values, resulting in performance improvement. Simulation results show that the hybrid approach for SIC-MMSE method highly reduces computational complexity, without appreciable bit error rate performance degradation.
UR - https://www.scopus.com/pages/publications/85018179028
U2 - 10.1109/ICAEES.2016.7888116
DO - 10.1109/ICAEES.2016.7888116
M3 - Conference paper
AN - SCOPUS:85018179028
T3 - 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016
SP - 597
EP - 600
BT - 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016
A2 - Nordin, Rosdiadee
A2 - Mansor, Mohd Fais
A2 - Ismail, Mahamod
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016
Y2 - 14 November 2016 through 16 November 2016
ER -