Modulation recognition plays a critical role in the development of reconfigurable radios which intelligently interact with their environments to maximize resources utilization. This research topic has been intensively investigated in the literature for different communication systems during the last decades. However, to the best of the authors’ knowledge, no work has been reported to take advantage of channel decoders, which are typically implemented in most practical systems, in designing modulation recognition algorithms. In this contribution, for the first time in the literature, we show how the output of a channel decoder can be exploited to iteratively estimate the maximum-likelihood value of the transmit modulation format. The proposed algorithm is implemented via an expectation-maximization procedure. The proposed algorithm operates with any channel code as long as its decoder can provide the a posteriori probabilities of the transmitted bits. Monte Carlo simulations indicate that the proposed algorithm achieves a high recognition performance over a wide range of signal-to-noise ratios compared to the traditional ones.

中文翻译：

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可重构无线电的软信息辅助调制识别

调制识别在可重配置无线电的开发中起着至关重要的作用，可重配置无线电与环境进行智能交互以最大程度地利用资源。在过去的几十年中，该研究主题已在文献中针对不同的通信系统进行了深入研究。但是，据作者所知，尚无任何工作可利用信道解码器来进行设计，该信道解码器通常在大多数实际系统中实现，用于设计调制识别算法。在此贡献中，我们首次展示了如何利用信道解码器的输出来迭代地估算发射调制格式的最大似然值。所提出的算法是通过期望最大化过程实现的。只要其解码器可以提供所传输比特的后验概率，则所提出的算法可以在任何信道码下运行。蒙特卡洛仿真表明，与传统算法相比，该算法在宽范围的信噪比下均具有较高的识别性能。