论文标题
皮肤莫莫：基于振动的MIMO通信人类皮肤
Skin-MIMO: Vibration-based MIMO Communication over Human Skin
论文作者
论文摘要
我们通过人类皮肤上的振动来探讨多输入 - 型号输出（MIMO）通信的可行性。分别使用现成的电动机和压电传感器作为振动发射器和接收器，我们构建了一个2x2 MIMO测试床，以收集和分析来自真实受试者的振动信号。我们的分析表明，一对发射器和接收器之间存在多个独立的振动通道，从而确认了MIMO的可行性。不幸的是，机械电动机和快速变化的皮肤通道的慢速渐变使得基于传统通道的基于通道的通道状态信息（CSI）的采集是不切实际的，这对于实现MIMO容量增长至关重要。为了解决这个问题，我们提出了一种基于深度学习的CSI采集技术的Skin-Mimo，以完全基于惯性传感器（加速度计和陀螺仪）测量在发射机上准确预测CSI，从而避免了通道发声的需求。基于实验振动数据，我们表明，与单输入单输出输出（SISO）或开环MIMO相比，皮肤模拟物可以提高MIMO容量为2.3倍，而无需访问CSI。一个令人惊讶的发现是，测量角速度的陀螺仪在预测皮肤振动方面比加速度计优于测量线性加速度，并在先前的研究中广泛用于固体对象的振动通信。
We explore the feasibility of Multiple-Input-Multiple-Output (MIMO) communication through vibrations over human skin. Using off-the-shelf motors and piezo transducers as vibration transmitters and receivers, respectively, we build a 2x2 MIMO testbed to collect and analyze vibration signals from real subjects. Our analysis reveals that there exist multiple independent vibration channels between a pair of transmitter and receiver, confirming the feasibility of MIMO. Unfortunately, the slow ramping of mechanical motors and rapidly changing skin channels make it impractical for conventional channel sounding based channel state information (CSI) acquisition, which is critical for achieving MIMO capacity gains. To solve this problem, we propose Skin-MIMO, a deep learning based CSI acquisition technique to accurately predict CSI entirely based on inertial sensor (accelerometer and gyroscope) measurements at the transmitter, thus obviating the need for channel sounding. Based on experimental vibration data, we show that Skin-MIMO can improve MIMO capacity by a factor of 2.3 compared to Single-Input-Single-Output (SISO) or open-loop MIMO, which do not have access to CSI. A surprising finding is that gyroscope, which measures the angular velocity, is found to be superior in predicting skin vibrations than accelerometer, which measures linear acceleration and used widely in previous research for vibration communications over solid objects.
