This paper derives a low-complexity turbo equalization algorithm for turbo coded multiple input multiple output/ orthogonal frequency division multiplexing systems. This algorithm consists of soft-output decision-feed...This paper derives a low-complexity turbo equalization algorithm for turbo coded multiple input multiple output/ orthogonal frequency division multiplexing systems. This algorithm consists of soft-output decision-feedback equalization with a probabilistic data association algorithm and a soft-input soft-output turbo channel decoder using iterative operations. In each iteration, extrinsic information extracted from the probabilistic data association algorithm detector and from the channel decoder is used as the prior information for the next iteration to realize iterative channel equalization and channel decoding, Our simulation results show that the algorithm improves the signal noise ratio around 1 dB with bit error rate reaching 10 -6 when the Eb/ N0 - 4 dB compared to minimum mean square error and match filter, and can greatly reduce the intersymbol interference at a low overall complexity of O（ N^3） after 2 iterations.展开更多
To restrain the interference of co-channel users using space-time block coding （STBC）, the proposed Gaussian-forcing soft decision multi-user detection （GFSDMUD） algorithm is applied in fiat-fading channels by usi...To restrain the interference of co-channel users using space-time block coding （STBC）, the proposed Gaussian-forcing soft decision multi-user detection （GFSDMUD） algorithm is applied in fiat-fading channels by using the relation among the users＇ signals, which can enhance the capacity by introducing co-channel users. During iterations, extrinsic information is calculated and exchanged between a soft multi-user detector and a bank of turbo decoders to achieve refined estimates of the users＇ signals. The simulations show that the proposed iterative receiver techniques provide significant performance improvement around 2 dB over conventional noniterative methods. Furthermore, iterative multi-user space-time processing techniques offer substantial performance gains around 8 dB by adding the number of receiver antennas from 4 to 6, and the system performance can be enhanced by using this strategy in multi-user STBC systems, which is very important for enlarging the system capacity.展开更多
文摘This paper derives a low-complexity turbo equalization algorithm for turbo coded multiple input multiple output/ orthogonal frequency division multiplexing systems. This algorithm consists of soft-output decision-feedback equalization with a probabilistic data association algorithm and a soft-input soft-output turbo channel decoder using iterative operations. In each iteration, extrinsic information extracted from the probabilistic data association algorithm detector and from the channel decoder is used as the prior information for the next iteration to realize iterative channel equalization and channel decoding, Our simulation results show that the algorithm improves the signal noise ratio around 1 dB with bit error rate reaching 10 -6 when the Eb/ N0 - 4 dB compared to minimum mean square error and match filter, and can greatly reduce the intersymbol interference at a low overall complexity of O（ N^3） after 2 iterations.
文摘To restrain the interference of co-channel users using space-time block coding （STBC）, the proposed Gaussian-forcing soft decision multi-user detection （GFSDMUD） algorithm is applied in fiat-fading channels by using the relation among the users＇ signals, which can enhance the capacity by introducing co-channel users. During iterations, extrinsic information is calculated and exchanged between a soft multi-user detector and a bank of turbo decoders to achieve refined estimates of the users＇ signals. The simulations show that the proposed iterative receiver techniques provide significant performance improvement around 2 dB over conventional noniterative methods. Furthermore, iterative multi-user space-time processing techniques offer substantial performance gains around 8 dB by adding the number of receiver antennas from 4 to 6, and the system performance can be enhanced by using this strategy in multi-user STBC systems, which is very important for enlarging the system capacity.
