6/2/2023 0 Comments Rssi values wifi![]() Conceptually, the channel response is the response to RSSI, just like the response of the rainbow to the solar beam, the components of different wavelengths are separated, and OFDM is the medium that refracts RSSI into CSI. Different from RSSI, because the superposition of the multipath signal exchange layer has the characteristics of rapid change, the power characteristics and channel response of the physical layer CSI can distinguish the multipath characteristics. RSSI, as the superposition of channel strength, cannot clearly reflect the channel changes, which greatly reduces the detection rate. Human behavior will inevitably cause major changes in signal propagation channels by changing multipath. In an indoor environment, the signal sent by the transmitter passes through multiple propagation paths and undergoes reflection and scattering before reaching the receiver. CSI uses a more fine-grained wireless channel measurement than RSSI, so CSI has some inherent advantages in terms of information. RSSI is the energy characteristic of the Media Access Control (MAC) layer. 1.2 The relationship between CSI and RSSI In addition to perceiving environmental changes caused by large movements such as walking and running of people or animals, it can also capture subtle movements caused by small movements such as breathing and chewing of people or animals in a static environment. CSI is extremely sensitive to environmental changes. By analyzing and studying the changes in CSI, we can conversely speculate on the changes in the physical environment that cause the changes in the channel state, that is, to achieve non-contact intelligent sensing. It can be used to measure the channel status of the wireless network in Wi-Fi communication. These indicators reveal the signal scattering, reflection, and power attenuation phenomena that occur with the carrier as the transmission distance changes. Supported versions and chips ESP-CSIĬhannel state information (CSI) includes specific indicators such as carrier signal strength, amplitude, phase, and signal delay. You can get more accurate results through machine learning, neural network and other algorithms based on the original CSI data. The human body detection algorithm is still being optimized. The main purpose of this project is to show the use of ESP-WIFI-CSI.
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