MIMO和ISI信道中迭代接收机的信道缩短解调器设计
On the Design of Channel Shortening Demodulators for Iterative Receivers in MIMO and ISI Channels
摘要：
我们考虑的问题，设计解调器的线性矢量信道的存储器，使用减少尺寸的网格描述的接收信号。我们假设一个整体迭代接收机，并且对于网格描述未覆盖的信号部分，我们使用基于外部解码器提供的软信息的干扰消除。为了达到一个网格描述，线性滤波器被应用作为前端压缩成一个小的网格的信号结构。该过程需要设计三个参数：（i）前端滤波器，（ii）通过其进行干扰消除的反馈滤波器，以及（iii）指定网格的目标响应。这种形式的解调器之前已经在当时的名称信道缩短（CS）下进行了研究，但是CS和干扰消除之间的相互作用在文献中没有得到充分的解决。在本文中，我们分析了两种类型的CS解调器，分别基于Forney和Ungerboeck检测模型。基于广义互信息（GMI）函数对参数进行联合优化。我们还介绍了第三种类型的CS解调器，一般是次优的，但所有参数的封闭形式的解决方案。此外，信号噪声比（SNR）的渐近性质进行了分析，我们表明，第三CS解调器渐近收敛到最佳CS解调器的意义上最大化的GMI。
英文摘要：
We consider the problem of designing demodulators for linear vector channels with memory that use reduced-size trellis descriptions for the received signal. We assume an overall iterative receiver, and for the parts of the signal not covered by the trellis description, we use interference cancelation based on the soft information provided by the outer decoder. In order to reach a trellis description, a linear filter is applied as front-end to compress the signal structure into a small trellis. This process requires three parameters to be designed: (i) the front-end filter, (ii) the feedback filter through which the interference cancelation is done, and (iii) a target response which specifies the trellis. Demodulators of this form have been studied before under then name channel shortening (CS), but the interplay between CS and interference cancelation has not been adequately addressed in the literature. In this paper, we analyze two types of CS demodulators that are based on the Forney and Ungerboeck detection models, respectively. The parameters are jointly optimized based on a generalized mutual information (GMI) function. We also introduce a third type of CS demodulator that is in general suboptimal but has closed form solutions for all parameters. Moreover, signal to noise ratio (SNR) asymptotic properties are analyzed and we show that the third CS demodulator asymptotically converges to the optimal CS demodulator in the sense of maximizing the GMI.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
