A novel low-complexity iterative receiver for multiuser space frequency block coding (SFBC) system was proposed in this paper. Unlike the conventional linear minimum mean square error (MMSE) detector, which requires m...A novel low-complexity iterative receiver for multiuser space frequency block coding (SFBC) system was proposed in this paper. Unlike the conventional linear minimum mean square error (MMSE) detector, which requires matrix inversion at each iteration, the soft-in soft-out (SISO) detector is simply a parallel interference cancellation (PIC)-matched filter (MF) operation. The probability density function (PDF) of PIC-MF detector output is approximated as Gaussian, whose variance is calculated with a priori information fed back from the channel decoder. With this approximation, the log likelihood ratios (LLRs) of transmitted bits are under-estimated. Then the LLRs are multiplied by a constant factor to achieve a performance gain. The constant factor is optimized according to extrinsic information transfer (EXIT) chart of the SISO detector. Simulation results show that the proposed iterative receiver can significantly improve the system performance and converge to the matched filter bound (MFB) with low computational complexity at high signal-to-noise ratios (SNRs).展开更多
基金The Science and Technology Committee of Shanghai Municipality ( No 06DZ15013,No03DZ15010)
文摘A novel low-complexity iterative receiver for multiuser space frequency block coding (SFBC) system was proposed in this paper. Unlike the conventional linear minimum mean square error (MMSE) detector, which requires matrix inversion at each iteration, the soft-in soft-out (SISO) detector is simply a parallel interference cancellation (PIC)-matched filter (MF) operation. The probability density function (PDF) of PIC-MF detector output is approximated as Gaussian, whose variance is calculated with a priori information fed back from the channel decoder. With this approximation, the log likelihood ratios (LLRs) of transmitted bits are under-estimated. Then the LLRs are multiplied by a constant factor to achieve a performance gain. The constant factor is optimized according to extrinsic information transfer (EXIT) chart of the SISO detector. Simulation results show that the proposed iterative receiver can significantly improve the system performance and converge to the matched filter bound (MFB) with low computational complexity at high signal-to-noise ratios (SNRs).
