Coordinated cancellation and correction of non-stationary noise in OFDM

我们报告的第二个项目阶段的结果，解决所有四个工作包，曾经设想的应用程序。从脉冲噪声中LDPC码的处理和脉冲噪声记忆的马尔可夫建模，一个开放的问题，即如何通过LDPC解码和马尔可夫状态估计的联合处理来改善噪声状态估计。到目前为止，脉冲状态是由一个简单的，但优化的阈值决定，它已经提供了一个接近最佳的性能。最佳性能的小剩余间隙甚至可以通过互连状态估计和迭代解码来闭合。我们还报告使用格型空时码，在那里我们离开一个空间维度的脉冲噪声检测，并推导出检测阈值和成对的错误概率。此外，一个简单的重复为基础的放大和转发中继的情况进行了研究，并推导出最佳的组合器。此外，我们专业化的脉冲噪声测量的基础上的参数估计显示米德尔顿的A类模型很好的配合。在第一个项目阶段，我们已经开始了一些研究，将我们的脉冲噪声处理应用于航空测距设备的脉冲。现在，我们设法确定了一个最佳的接收器，获得接近无干扰的情况下的性能。

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.