AI 中文总结
研究大规模MIMO系统检测问题，提出基于方向统计和置信传播、利用冯·米塞斯参数表示的低复杂度检测方法，适用于PSK调制，不依赖调制阶数，还给出信道扩展，量化性能并与高斯近似算法比较。
AI 中文摘要
在大规模多输入多输出（mMIMO）系统中，使用最大后验概率（MAP）等最优解码器时，检测存在指数级复杂度。我们提出一种基于方向统计的基于置信传播的检测器，适用于依赖相移键控（PSK）调制的mMIMO系统。通过将PSK调制连续松弛到单位圆，并利用消息的冯·米塞斯参数表示来获得（通常是无限维）消息的稀疏表示，该方法允许以低复杂度进行近似检测，且不依赖于PSK调制阶数。还给出了算法对不完美信道实现的扩展。我们量化了所提方法的性能和复杂度，并与基于高斯近似的检测算法进行比较。
英文摘要
Detection in massive multiple input multiple output (mMIMO) systems suffers from exponential complexity while using optimal decoders like maximum a posteriori (MAP). We propose a belief propagation-based detector based on directional statistics, applicable to mMIMO systems relying on PSK modulations. Thanks to a continuous relaxation of the PSK modulation to the unit circle, and to the use of von Mises parametric representations of the messages to obtain sparse representations of the (generally infinite dimensional) messages, the proposed method allows for approximate detection with a low complexity which does not depend on the PSK modulation order. Extensions of the algorithm to imperfect channel realizations are also present. We quantify the performance and complexity of the proposed approach and compare it with detection algorithms based on Gaussian approximation.
