Joint Spatio-Temporal Precoding for Practical Non-Stationary Wireless Channels
Joint Spatio-Temporal Precoding for Practical Non-Stationary Wireless Channels
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DOI：
10.1109/tcomm.2023.3241326
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发表时间：
2022-11
影响因子：
8.3
通讯作者：
Zhibin Zou;M. Careem;Aveek Dutta;Ngwe Thawdar
中科院分区：
文献类型：
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作者：
Zhibin Zou;M. Careem;Aveek Dutta;Ngwe Thawdar
现代无线系统中的高移动性、密度和多径性使得信道具有高度的非平稳性。这导致信道分布的时间变化，这导致跨多个自由度（DoF，例如，用户、天线、频率和符号），这使得传统的预编码在实践中是次优的。在这项工作中，我们推导出一个高阶广义的美世定理（HOGMT），它分解成两个（双）集的联合正交子信道（本征函数）的多用户非平稳信道，这导致在另一组时，一组通过信道传输。本征函数的这种对偶性和联合正交性确保了在独立平坦衰落子信道上的传输。因此，传输这些具有最佳导出系数的本征函数最终减轻了其自由度上的任何干扰，并形成了所提出的联合时空预编码的基础。所传送的对偶本征函数和系数在解调时直接在接收器处重构数据符号，从而通过减轻对任何互补后编码的需要而显著地减少其计算负担。此外，从时间-频率延迟-多普勒信道内核分解的本征函数对于提取二阶信道统计是至关重要的，因此完全表征了底层信道。我们评估这一点，使用一个现实的非平稳信道的框架建立在Matlab中，并表明我们的预编码实现了${\geqslant }4$订单的BER降低SNR ${\geqslant }15$ dB的OFDM系统中的高阶调制和更低的复杂性相比，国家的最先进的预编码。
The high mobility, density and multi-path evident in modern wireless systems makes the channel highly non-stationary. This causes temporal variation in the channel distribution that leads to the existence of time-varying joint interference across multiple degrees of freedom (DoF, e.g., users, antennas, frequency and symbols), which renders conventional precoding sub-optimal in practice. In this work, we derive a High-Order Generalization of Mercer’s Theorem (HOGMT), which decomposes the multi-user non-stationary channel into two (dual) sets of jointly orthogonal subchannels (eigenfunctions), that result in the other set when one set is transmitted through the channel. This duality and joint orthogonality of eigenfuntions ensure transmission over independently flat-fading subchannels. Consequently, transmitting these eigenfunctions with optimally derived coefficients eventually mitigates any interference across its degrees of freedoms and forms the foundation of the proposed joint spatio-temporal precoding. The transferred dual eigenfuntions and coefficients directly reconstruct the data symbols at the receiver upon demodulation, thereby significantly reducing its computational burden, by alleviating the need for any complementary post-coding. Additionally, the eigenfunctions decomposed from the time-frequency delay-Doppler channel kernel are paramount to extracting the second-order channel statistics, and therefore completely characterize the underlying channel. We evaluate this using a realistic non-stationary channel framework built in Matlab and show that our precoding achieves ${\geqslant }4$ orders of reduction in BER at SNR ${\geqslant }15$ dB in OFDM systems for higher-order modulations and less complexity compared to the state-of-the-art precoding.