In wireless networks, frequent reference signal transmission for accurate channel reconstruction may reduce spectral efficiency. To address this issue, we consider to use a data-carrying reference signal (DC-RS) that can simultaneously estimate channel coefficients and transmit data symbols. Here, symbols on the Grassmann manifold are exploited to carry additional data and to assist in channel estimation. Unlike conventional studies, we analyze the channel estimation errors induced by DC-RS and propose an optimization method that improves the channel estimation accuracy without performance penalty. Then, we derive the achievable rate of noncoherent Grassmann constellation assuming discrete inputs in multi-antenna scenarios, as well as that of coherent signaling assuming channel estimation errors modeled by the Gauss-Markov uncertainty. These derivations enable performance evaluation when introducing DC-RS, and suggest excellent potential for boosting spectral efficiency, where interesting crossings with the non-data carrying RS occurred at intermediate signal-to-noise ratios.

翻译：在无线网络中，频繁发送参考信号以实现精确的信道重建可能会降低频谱效率。为解决该问题，本文考虑使用一种可同时进行信道系数估计与数据符号传输的携带数据的参考信号（DC-RS）。在此框架下，利用格拉斯曼流形上的符号既承载额外数据又辅助信道估计。不同于传统研究，我们分析了DC-RS引发的信道估计误差，并提出一种在不牺牲性能的前提下提升信道估计精度的优化方法。随后，推导了多天线场景中采用离散输入时非相干格拉斯曼星座的可达速率，以及基于高斯-马尔可夫不确定性建模信道估计误差下的相干信令可达速率。这些推导为引入DC-RS的性能评估提供了依据，并表明其具有显著提升频谱效率的潜力，尤其在中信噪比区域，观察到与无数据携带参考信号出现有趣交叉的现象。