Signal recognition has recently emerged as a key ingredient for cognitive radios with defense and industrial uses. This letter area encompasses the recognition of a broad range of transmission aspects such as modulation format, space-time mapping, channel coding form, central frequency, and data rate. Each of these aspects has been extensively researched in the literature. Only a few works addressed co-recognition. To the best of the authors’ knowledge, there is a single study that is dedicated to the recognition of combined modulation and space-time block coding (STBC), with the constraints of having more receive antennas than transmit antennas and operating over frequency-flat channels. In this letter, we propose a novel algorithm that recognizes modulation and STBC simultaneously over unknown frequency-selective channels while relaxing the requirement of having more antennas at the receiver than at the transmitter. The mathematical treatments demonstrate how an iterative expectation-maximization strategy is simply used to create a maximum-likelihood solution for this problem. Additionally, we make use of soft information coupled with channel decoders to enhance the proposed algorithm’s recognition performance. The proposed design also incorporates the supplementary task of channel estimation as a part of its overall structure. According to the findings of the computational complexity analysis and simulation results, the proposed algorithm easily defeats the one documented in the literature.

中文翻译：

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配备编码传输调制和 STBC 识别的认知无线电


信号识别最近已成为国防和工业用途认知无线电的关键要素。该字母区域涵盖了广泛的传输方面的识别，例如调制格式、空时映射、信道编码形式、中心频率和数据速率。这些方面中的每一个都在文献中得到了广泛的研究。只有少数作品涉及共同认可。据作者所知，有一项研究致力于识别组合调制和空时块编码（STBC），其限制是接收天线多于发射天线，并且在频率平坦的情况下运行渠道。在这封信中，我们提出了一种新颖的算法，可以在未知的频率选择信道上同时识别调制和 STBC，同时放宽接收器处比发射器处拥有更多天线的要求。数学处理演示了如何简单地使用迭代期望最大化策略来创建该问题的最大似然解。此外，我们利用软信息与通道解码器相结合来增强所提出算法的识别性能。所提出的设计还将信道估计的补充任务纳入其整体结构的一部分。根据计算复杂度分析和仿真结果的结果，所提出的算法很容易击败文献中记录的算法。