With the continually increasing demand for higher data rate and link density as well as better network coverage, wireless networks, including 5G-enabled vehicular communication network (VCN), will be designed/deployed to cover more overlapping areas, experiencing more severe interferences. As a result, interference becomes a key impediment to the improvement of network performance, thus requiring a thorough investigation. There have been numerous interference management (IM) methods, of which interference alignment (IA) has been receiving significant attention in recent years. IA compresses the dimension of interference subspace by confining multiple interfering signals into a finite subspace, so that the desired signal subspace may be maximized. However, when IA is applied to the situation where multiple interferences are from the same source, the interference subspace cannot be compressed due to the fact that if these interfering components are aligned in the same direction at their unintended receiver (Rx), they will become indistinguishable at their desired Rx. To solve this problem, we propose Inside-Out Precoding (IOP). With IOP, multiple data streams that may cause interference to the other Rx are at first pre-processed at the interfering transmitter (Tx), by employing an inner-precoder which makes the streams spatially separable, and then, by exploiting interactions among wireless signals, multiple interfering components are treated as an effective interference to which an outer-precoder is applied, so that multiple interferences can be compressed into one dimension at the interfered Rx while making them distinguishable at their desired Rx. We present two IOP realizations — forward IOP (F-IOP) and backward IOP (B-IOP) — and propose a protocol to realize the synchronization of processing parameters at the interfering Tx and its intended Rx so that the Rx can adapt itself to the precoding strategy employed at the Tx side. Our in-depth analysis and simulation results have shown that the proposed IOP can effectively manage multiple interferences from the same source while guaranteeing the performance of transmission from the interfering Tx to its intended Rx.

中文翻译：

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由内而外的预编码以管理来自同一来源的多个干扰

随着对更高数据速率和链路密度以及更好网络覆盖的需求不断增加，包括支持 5G 的车载通信网络 (VCN) 在内的无线网络将被设计/部署以覆盖更多重叠区域，从而遭受更严重的干扰。因此，干扰成为提高网络性能的主要障碍，因此需要彻底调查。已经有许多干扰管理（IM）方法，其中干扰对齐（IA）近年来受到了极大的关注。IA通过将多个干扰信号限制在一个有限的子空间中来压缩干扰子空间的维数，使得期望的信号子空间可以最大化。但是，当 IA 应用于多个干扰来自同一个源的情况时，干扰子空间无法压缩，因为如果这些干扰分量在其非预期接收器 (Rx) 处以相同方向对齐，则它们在所需的 Rx 处将变得无法区分。为了解决这个问题，我们提出了内向外预编码（IOP）。使用 IOP，可能会对其他 Rx 造成干扰的多个数据流首先在干扰发射机 (Tx) 进行预处理，通过使用使流在空间上可分离的内部预编码器，然后利用无线信号之间的相互作用，多个干扰分量被视为有效干扰，应用了外部预编码器，从而可以将多个干扰在受干扰的 Rx 处压缩为一维，同时使它们在所需的 Rx 处可区分。我们提出了两种 IOP 实现——前向 IOP (F-IOP) 和后向 IOP (B-IOP)——并提出了一种协议来实现干扰 Tx 及其预期 Rx 处的处理参数同步，以便 Rx 能够适应Tx 端采用的预编码策略。我们的深入分析和仿真结果表明，所提出的 IOP 可以有效管理来自同一源的多个干扰，同时保证从干扰 Tx 到其预期 Rx 的传输性能。