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，频繁传输用于精确信道重构的参考信号可能会降低频谱效率。为解决这一问题，我们考虑使用一种可同时估计信道系数并传输数据符号的数据承载参考信号（DC-RS）。本文利用格拉斯曼流形上的符号来承载额外数据并辅助信道估计。不同于传统研究，我们分析了DC-RS引起的信道估计误差，并提出了一种在不产生性能损失的前提下提升信道估计精度的优化方法。随后，我们推导了多天线场景下假设离散输入时非相干格拉斯曼星座的可达速率，以及假设由高斯-马尔可夫不确定性建模的信道估计误差时相干信令的可达速率。这些推导使得引入DC-RS时的性能评估成为可能，并揭示了其在提升频谱效率方面的巨大潜力，其中在中等信噪比区域出现了与非数据承载参考信号的有趣交叉现象。