Title: On the Capacity of Communication Channels with Memory and Sampled Additive Cyclostationary Gaussian Noise: Full Version with Detailed Proofs Show Chinese title

Title: 具有记忆的通信信道与采样加性循环平稳高斯噪声的容量：带有详细证明的完整版本

Abstract: In this work we study the capacity of interference-limited channels with memory. These channels model non-orthogonal communications scenarios, such as the non-orthogonal multiple access (NOMA) scenario and underlay cognitive communications, in which the interference from other communications signals is much stronger than the thermal noise. Interference-limited communications is expected to become a very common scenario in future wireless communications systems, such as 5G, WiFi6, and beyond. As communications signals are inherently cyclostationary in continuous time (CT), then after sampling at the receiver, the discrete-time (DT) received signal model contains the sampled desired information signal with additive sampled CT cyclostationary noise. The sampled noise can be modeled as either a DT cyclostationary process or a DT almost-cyclostationary process, where in the latter case the resulting channel is not information-stable. In a previous work we characterized the capacity of this model for the case in which the DT noise is memoryless. In the current work we come closer to practical scenarios by modelling the resulting DT noise as a finite-memory random process. The presence of memory requires the development of a new set of tools for analyzing the capacity of channels with additive non-stationary noise which has memory. Our results show, for the first time, the relationship between memory, sampling frequency synchronization and capacity, for interference-limited communications. The insights from our work provide a link between the analog and the digital time domains, which has been missing in most previous works on capacity analysis. Thus, our results can help improving spectral efficiency and suggest optimal transceiver designs for future communications paradigms. Show Chinese abstract

Abstract: 在本工作中，我们研究具有记忆的干扰受限信道的容量。这些信道模拟非正交通信场景，例如非正交多址接入（NOMA）场景和叠加认知通信，在这些场景中，来自其他通信信号的干扰远强于热噪声。预计干扰受限通信将在未来的无线通信系统中变得非常普遍，例如5G、WiFi6以及更高级别。由于通信信号在连续时间（CT）中本质上是循环平稳的，因此在接收端采样后，离散时间（DT）接收信号模型包含带有采样CT循环平稳噪声的采样期望信息信号。采样噪声可以建模为DT循环平稳过程或DT几乎循环平稳过程，在后一种情况下，得到的信道不是信息稳定的。在之前的工作中，我们表征了DT噪声无记忆情况下的该模型容量。在当前工作中，我们通过将产生的DT噪声建模为有限记忆随机过程，更接近实际场景。记忆的存在需要开发一套新的工具来分析具有记忆的加性非平稳噪声信道的容量。我们的结果首次展示了干扰受限通信中记忆、采样频率同步和容量之间的关系。我们工作的见解建立了模拟和数字时间域之间的联系，这在大多数先前关于容量分析的工作中是缺失的。因此，我们的结果有助于提高频谱效率，并为未来通信范式提供最优的收发器设计。