Millimeter wave (mmWave) full-duplex (FD) is a promising technique for improving capacity by maximizing the utilization of both time and the rich mmWave frequency resources. Still, it has restrictions due to FD self-interference (SI) and mmWave's limited coverage. Therefore, this study dives into FD mmWave MIMO with the assistance of reconfigurable intelligent surfaces (RIS) for capacity improvement. First, we demonstrate the angular-domain reciprocity of FD antenna arrays under the far-field planar wavefront assumption. Accordingly, a strategy for joint downlink-uplink (DL-UL) channel estimation is presented. For estimating the SI channel, the direct channel, and the cascaded channel, the Khatri-Rao product-based compressive sensing (KR-CS), distributed CS (D-CS), and two-stage multiple measurement vector-based D-CS (M-D-CS) frameworks are proposed, respectively. Additionally, we propose a passive beamforming optimization solution based on the angular-domain cascaded channel. With hybrid beamforming architectures, a novel hybrid weighted minimum mean squared error method for SI cancellation (H-WMMSE-SIC) is proposed. Simulations have revealed that joint DL-UL processing significantly improves estimation performance in comparison to separate DL/UL channel estimation. Particularly, when the interference-to-noise ratio is less than 35 dB, our proposed H-WMMSE-SIC offers spectral efficiency performance comparable to fully-digital WMMSE-SIC. Finally, the computational complexity is analyzed for our proposed methods.

翻译：毫米波（mmWave）全双工（FD）是一种有前景的技术，通过最大化时间及丰富的毫米波频率资源的利用来提高容量。然而，由于FD自干扰（SI）和毫米波覆盖范围受限等问题，该技术仍存在限制。因此，本研究深入探讨了在可重构智能表面（RIS）辅助下的FD毫米波MIMO技术以提升容量。首先，我们展示了远场平面波假设下FD天线阵列的角域互易性。据此，提出了一种联合下行-上行（DL-UL）信道估计策略。针对自干扰信道、直射信道及级联信道的估计，分别提出了基于Khatri-Rao积的压缩感知（KR-CS）、分布式压缩感知（D-CS）以及两阶段多测量矢量D-CS（M-D-CS）框架。此外，我们还提出了一种基于角域级联信道的无源波束赋形优化方案。在混合波束赋形架构下，提出了一种用于自干扰消除的新型混合加权最小均方误差方法（H-WMMSE-SIC）。仿真结果表明，与单独的下行/上行信道估计相比，联合DL-UL处理显著提升了估计性能。特别地，当干扰噪声比低于35 dB时，我们提出的H-WMMSE-SIC可提供与全数字WMMSE-SIC相当的频谱效率性能。最后，对所提方法的计算复杂度进行了分析。