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
The amplitude of frequency spectrum can he integrated with prohabilisfic data association （PDA） to distinguish the target with clutter echoes, especially in low SNR underwater environment. A new target-tracking algo...The amplitude of frequency spectrum can he integrated with prohabilisfic data association （PDA） to distinguish the target with clutter echoes, especially in low SNR underwater environment. A new target-tracking algorithm is presented which adopts the amplitude of frequency spectrum to improve target tracking in clutter. The prohabilisfic density distribution of frequency spectrum amplitude is analyzed. By simulation, the results show that the algorithm is superior to PDA. This approach enhances stability for the association probability and increases the performance of target tracking.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.
基金This project was supported by the Defense Pre-Research Project of the‘Tenth Five-Year-Plan’of China (40105010101)
文摘The amplitude of frequency spectrum can he integrated with prohabilisfic data association （PDA） to distinguish the target with clutter echoes, especially in low SNR underwater environment. A new target-tracking algorithm is presented which adopts the amplitude of frequency spectrum to improve target tracking in clutter. The prohabilisfic density distribution of frequency spectrum amplitude is analyzed. By simulation, the results show that the algorithm is superior to PDA. This approach enhances stability for the association probability and increases the performance of target tracking.
