Coordinated cancellation and correction of non-stationary noise in OFDM

我们报告了第二项目阶段的结果，涉及申请中曾经设想的所有四个工作包。从脉冲噪声中LDPC码的处理和脉冲噪声记忆的马尔可夫模型出发，提出了一个悬而未决的问题，即如何通过联合处理LDPC译码和马尔可夫状态估计来改善噪声状态估计。到目前为止，脉冲状态是由一个简单但优化的阈值决定决定的，它已经提供了接近最佳的性能。甚至可以通过链接状态估计和迭代译码来弥合到最佳性能的微小剩余差距。我们还报告了格空时码的使用，其中我们保留了一维空间用于脉冲噪声检测，并推导了检测阈值和成对错误概率。此外，还研究了一种简单的基于重复的放大转发中继情况，并推导了最优合并器。此外，我们对基于脉冲噪声测量的参数估计进行了专业化，表明了Middleton的A类模型的良好拟合。在项目的第一阶段，我们已经开始了将我们的脉冲噪声处理应用于航空测距设备的脉冲的研究。现在，我们设法确定了获得接近无干扰情况的性能的最佳接收器。

We report about the results of the second project phase addressing all the four work packages that were once envisaged in the application. From the treatment of LDPC codes in impulse noise and a Markov modeling of the impulse noise memory, an open question evolved, namely how the noise state estimation can be improved by a joint treatment of LDPC decoding and Markov state estimation. So far, impulsive states are determined by a simple, yet optimized threshold decision, which already offers a close to optimum performance. The small leftover gap to optimum performance may even be closed by interlinking state estimation and iterative decoding. We also report about the use of lattice space-time codes, where we leave one spatial dimension for impulse-noise detection and derive the detection threshold and the pairwise error probability. Furthermore, a simple repetition-based amplify-and-forward relaying situation is studied and the optimum combiner is derived. Additionally, we professionalized the parameter estimation based on impulse-noise measurements showing the nice fit of Middleton’s Class A model. In the first project phase, we already started some studies applying our impulse-noise treatment to impulses of aeronautical distance measurement equipment. Now, we managed to determine an optimum receiver which obtains a performance close to the disturbance-free case.