FarSense——2019UbiCom论文阅读笔记_farsense: pushing the range limit of wifi-based…

FarSense:Pushing the Range Limit of WiFi-based Respiration Sensing with CSI Ratio of Two Antennas

YOUWEI ZENG,PekingUniversity,China
DAN WU,PekingUniversity,China
JIE XIONG,University of Massachusetts,USA
ENZE YI,PekingUniversity,China
RUIYANG GAO,PekingUniversity,China
DAQING ZHANG∗,Peking University,Chinaa nd Telecom SudParis,France

Key words

1. FarSense–the first real-time system that can reliably monitor human respiration when the target is faraway from the WiFi transceiver pair. 第一个可以实时远距离检测呼吸的系统
2. two novel schemes：(1)Instead of applying the raw CSI readings of individual antenna for sensing, we employ the ratio of CSI readings from two antennas, whose noise is mostly canceled out by the division operation to significantly increase the sensing range;(2)The division operation further enables us to utilize the phase information which is not usable with one single antenna for sensing.Theorthogonal amplitude and phase are elaborately combined to address the ”blind spots” issue and further increase the sensing range. 解决了两大问题：使用天线相除去除噪声提取信息；解决了盲区问题（参考菲涅尔区边界和内部相位的不同变化）
3. the target is 8 meters away from the transceiver pair，through-wall respiration sensing.感知距离达到8米，可以穿墙。
4. 同时使用振幅和相位信息

Note that a complex number can be represented in the form of a + bi as well as Aeiθ where a,b are the real part (I) and imaginary part (Q), and A,θ are the amplitude and phase, respectively. The orthogonal I and Q components of CSI ratio keep perfect complementarity for respiration sensing which means at a location I component is bad for sensing, Q component is good and vice versa.

Contribution

The main contributions of the work can be summarized as follows:
(1) We propose to employ CSI ratio rather than raw CSI for sensing. We develop the CSI-ratio model that establishes the relationship between human’s movement and CSI ratio changes which lays the foundation to guide fine-grained sensing. We believe the general CSI-ratio model will benefit not just respiration sensing but also to further sensing applications.
(2) We apply the CSI-ratio model for respiration sensing and elaborately combine the amplitude and phase of CSI ratio to address the ”blind spots” issue and further increase the sensing range.
(3) We design and implement FarSense on commodity WiFi devices.The sensing range is increased from the current state-of-the-art 2-4 meters to 8-9 meters. For the first time, FarSense is able to enable through-wall respiration sensing with commodity WiFi hardware,moving one step further towards real-life deployment.

RELATED WORK

Radar-based respiration sensing. These approaches can be mainly divided into three categories according to the technologies they are using. (1) Continuous-wave (CW) Doppler radar.(2) Ultra-wideband (UWB) pulse radar.
WiFi-based respiration sensing
(1) Respiration sensing with amplitude information.(2) Respiration sensing with phase information.

THE CSI-RATIO MODEL

1. 理想状态下，静态成分由LoS和其他静态物体反射路径组成；动态成分由人体运动反射组成；
   
   
   d(t)运动一个波长相位变化一周2π

2. 实际上，存在相位漂移

3. CSI RATIO
   基于不同天线使用相同网卡拥有相同的RF振荡器获得了相同相位漂移和d2(t)−d1(t) =∆d的假设
   
   天线1除以天线2，因为相位漂移相同，所以统一的相位漂移（随时间变化）被去掉了，使用A,B,C,D代替后
   
   之后化简
   
   根据莫比乌斯变化，缩放和平移不会改变旋转方向，只有反演——z->1/z会引入反向；
   当原点(0,0)在z包含的圆内，则1/z会反向旋转；如果不包含，则保持原来的方向；因为一般情况下，静态组分的能量大于动态成分，所以|D/C|的模长大于1，平移后不包含原点，所以保持原来的方向。

EXTRACTING RESPIRATION PATTERN FROM CSI RATIO

1. 将复平面的信号以一定的步长投影在不同角度的向量上，将投影后的不同参数组合作为candidates
2. 使用breathing-to-noise ratio(BNR)，根据呼吸能量和总能量的比值确定最佳的candidate
3. First, for each sub-carrier, we calculate the autocorrelation of its respiration pattern.The autocorrelation function describes the similarity of a signal to a shifted version of itself.通过自相关函数确定相似度最终确定每一个呼吸片段