results: simulation结果表明，使用提议的BeamSync方法可以提高性能，当AP中天线数量 Doubles 时，性能提高3dB。此外，这种方法也与传统的束 formaiting技术相比较好。Abstract
In distributed massive multiple-input multiple-output (MIMO) systems, multiple geographically separated access points (APs) communicate simultaneously with a user, leveraging the benefits of multi-antenna coherent MIMO processing and macro-diversity gains from the distributed setups. However, time and frequency synchronization of the multiple APs is crucial to achieve good performance and enable joint precoding. In this paper, we analyze the synchronization requirement among multiple APs from a reciprocity perspective, taking into account the multiplicative impairments caused by mismatches in radio frequency (RF) hardware. We demonstrate that a phase calibration of reciprocity-calibrated APs is sufficient for the joint coherent transmission of data to the user. To achieve synchronization, we propose a novel over-the-air synchronization protocol, named BeamSync, to calibrate the geographically separated APs without sending any measurements to the central processing unit (CPU) through fronthaul. We show that sending the synchronization signal in the dominant direction of the channel between APs is optimal. Additionally, we derive the optimal phase and frequency offset estimators. Simulation results indicate that the proposed BeamSync method enhances performance by 3 dB when the number of antennas at the APs is doubled. Moreover, the method performs well compared to traditional beamforming techniques.
摘要
在分布式巨大多输入多输出（MIMO）系统中，多个地理上分开的访问点（AP）同时与用户通信，利用多antenna干扰MIMO处理和macro-多样性收益。然而，多个AP的时间和频率同步是需要达到良好性能和启用联合预编码的关键。在这篇论文中，我们从reciprocity角度分析了多个AP之间的同步需求，考虑了 radio频率硬件匹配不准的乘数性质。我们示出，只需要在reciprocity-calibrated APs中进行相位准化，即可实现联合整合数据传输到用户。为实现同步，我们提出了一种新的无需中央处理单元（CPU）通过前段传输的空中同步协议，名为BeamSync。我们发现，在AP之间通信道的主导方向上发送同步信号是优化的。此外，我们 derive了最佳相位和频率偏移估计器。实验结果表明，我们提出的BeamSync方法可以在APantenna数量两倍时提高性能，并且与传统的扫描方法相比，其性能较好。
Channel Estimation for FAS-assisted Multiuser mmWave Systems
results: simulations results show that the proposed method can obtain precise CSI with minimal hardware switching and pilot overhead, leading to a system sum-rate that approaches the upper bound achievable with perfect CSI.Abstract
This letter investigates the challenge of channel estimation in a multiuser millimeter-wave (mmWave) time-division duplexing (TDD) system. In this system, the base station (BS) employs a multi-antenna uniform linear array (ULA), while each mobile user is equipped with a fluid antenna system (FAS). Accurate channel state information (CSI) plays a crucial role in the precise placement of antennas in FAS. Traditional channel estimation methods designed for fixed-antenna systems are inadequate due to the high dimensionality of FAS. To address this issue, we propose a low-sample-size sparse channel reconstruction (L3SCR) method, capitalizing on the sparse propagation paths characteristic of mmWave channels. In this approach, each fluid antenna only needs to switch and measure the channel at a few specific locations. By observing this reduced-dimensional data, we can effectively extract angular and gain information related to the sparse channel, enabling us to reconstruct the full CSI. Simulation results demonstrate that our proposed method allows us to obtain precise CSI with minimal hardware switching and pilot overhead. As a result, the system sum-rate approaches the upper bound achievable with perfect CSI.
摘要