This paper investigates joint design and optimization of both low density parity check （LDPC） codes and M-algorithm based detectors including iterative tree search （ITS） and soft-output M-algorithm （SOMA） in mul...This paper investigates joint design and optimization of both low density parity check （LDPC） codes and M-algorithm based detectors including iterative tree search （ITS） and soft-output M-algorithm （SOMA） in multiple-input multiple-output （MIMO） systems via the tool of extrinsic information transfer （EXIT） charts. First, we present EXIT analysis for ITS and SOMA. We indicate that the extrinsic information transfer curves of ITS obtained by Monte Carlo simulations based on output log-likelihood rations are not true EXIT curves, and the explanation for such a phenomenon is given, while for SOMA, the true EXIT curves can be computed, enabling the code design. Then, we propose a new design rule and method for LDPC code degree profile optimization in MIMO systems. The algorithm can make the EXIT curves of the inner decoder and outer decoder match each other properly, and can easily attain the desired code with the target rate. Also, it can transform the optimization problem into a linear one, which is computationally simple. The significance of the proposed optimization approach is validated by the simulation results that the optimized codes perform much better than standard non-optimized ones when used together with SOMA detector.展开更多
轨道交通LTE-M(Long Term Evolution-Metro,基于轨道交通的长期演进)同频干扰检测关乎列控信号传输的可靠性,提出一种基于INFO(weIghted meaNoFvectOrs,基于向量加权平均)算法的盲源分离方法,即INFO-BSS。该方法以混合信号的最大化负熵...轨道交通LTE-M(Long Term Evolution-Metro,基于轨道交通的长期演进)同频干扰检测关乎列控信号传输的可靠性,提出一种基于INFO(weIghted meaNoFvectOrs,基于向量加权平均)算法的盲源分离方法,即INFO-BSS。该方法以混合信号的最大化负熵为目标函数,用INFO优化算法替代牛顿迭代法,解决了牛顿迭代法初始参数易设置不当以及容易陷入局部最优的问题。仿真结果对比表明,在不同分辨率带宽、不同信干比等条件下,INFO-BSS的检测性能都要优于常规算法。展开更多
基金Supported by the National Basic Research Program of China (Grant No. 2009CB320406)the National Natural Science Foundation of China(Grant No. 60872048)Specialized Major Science and Technology Project of China (Grant Nos. 2008ZX03003-004, 2009ZX03003-009)
文摘This paper investigates joint design and optimization of both low density parity check （LDPC） codes and M-algorithm based detectors including iterative tree search （ITS） and soft-output M-algorithm （SOMA） in multiple-input multiple-output （MIMO） systems via the tool of extrinsic information transfer （EXIT） charts. First, we present EXIT analysis for ITS and SOMA. We indicate that the extrinsic information transfer curves of ITS obtained by Monte Carlo simulations based on output log-likelihood rations are not true EXIT curves, and the explanation for such a phenomenon is given, while for SOMA, the true EXIT curves can be computed, enabling the code design. Then, we propose a new design rule and method for LDPC code degree profile optimization in MIMO systems. The algorithm can make the EXIT curves of the inner decoder and outer decoder match each other properly, and can easily attain the desired code with the target rate. Also, it can transform the optimization problem into a linear one, which is computationally simple. The significance of the proposed optimization approach is validated by the simulation results that the optimized codes perform much better than standard non-optimized ones when used together with SOMA detector.
文摘轨道交通LTE-M(Long Term Evolution-Metro,基于轨道交通的长期演进)同频干扰检测关乎列控信号传输的可靠性,提出一种基于INFO(weIghted meaNoFvectOrs,基于向量加权平均)算法的盲源分离方法,即INFO-BSS。该方法以混合信号的最大化负熵为目标函数,用INFO优化算法替代牛顿迭代法,解决了牛顿迭代法初始参数易设置不当以及容易陷入局部最优的问题。仿真结果对比表明,在不同分辨率带宽、不同信干比等条件下,INFO-BSS的检测性能都要优于常规算法。
