The content delves into the concept of DC-RS for boosting spectral efficiency in wireless networks. It analyzes channel estimation errors induced by DC-RS, proposes optimization methods, and derives achievable rates for noncoherent Grassmann constellations. The study highlights the potential of DC-RS in improving spectral efficiency.
In wireless networks, reference signals play a crucial role in estimating channel state information between transmitters and receivers. Different types of reference signals are defined for various channel estimation purposes in 5G NR.
Training methods using pilot symbols have low computational complexity but can lead to high overhead in scenarios with frequent CSI updates.
Various approaches exist to reduce channel estimation overhead, such as differential coding, superimposed pilot methods, and blind methods that eliminate the need for preambles.
Using Grassmann constellations as reference signals enables noncoherent detection and stable performance even in high-mobility scenarios.
The construction methods for Grassmann constellations involve mapping classic symbols, algebraic constructions, and numerical optimizations.
DC-RS on the Grassmann manifold allows for simultaneous data and channel estimation without suffering from phase uncertainties.
An optimization method is proposed to improve channel estimation accuracy while maintaining the same minimum chordal distance between codewords.
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by Naoki Endo,H... um arxiv.org 03-05-2024
https://arxiv.org/pdf/2401.02597.pdfTiefere Fragen