PHY & Radio RSSI

RSSI

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Received Signal Strength Indicator -- a measurement of radio signal power at the receiver, commonly used for proximity estimation.

    


    
    
    

      Also known as:
      
      Received Signal Strength Indicator
      
    

    
  


  




  
  

    
RSSI


RSSI (Received Signal Strength Indicator) is a measurement of the power level of a received BLE radio signal, expressed in dBm. It is the most widely used metric for proximity estimation, indoor positioning, and connection quality monitoring in BLE applications.


How RSSI Is Measured


Every BLE packet received by a device includes metadata from the radio hardware, one component of which is the RSSI value. This value represents the total power measured at the receiver antenna during packet reception. Typical BLE RSSI values range from about -30 dBm (very close, strong signal) to -100 dBm (far away or obstructed, near the RX sensitivity limit).


RSSI is available both during advertising (scanning mode) and during an active connection. In scanning mode, the central can read the RSSI of each advertising packet to estimate how far away a peripheral is before deciding to connect. During a connection, RSSI can be polled via HCI commands to monitor link quality.


RSSI and Distance Estimation


The relationship between RSSI and distance follows the log-distance path loss model. In free space, signal strength decreases by approximately 6 dB for every doubling of distance. If a device reports -40 dBm at 1 meter, you would expect roughly -46 dBm at 2 meters and -52 dBm at 4 meters.


In practice, RSSI-based distance estimation is notoriously imprecise due to multipath reflections, body absorption, antenna orientation, and environmental clutter. Accuracy of +/-2 meters at 5-meter range is typical. For applications requiring higher precision, Direction Finding (BLE 5.1) or Channel Sounding (Bluetooth 6.0) provide centimeter-level accuracy.


Improving RSSI Accuracy


Averaging RSSI over multiple samples (10--50 readings) reduces noise. Kalman filters or exponential moving averages are commonly applied to smooth out short-term fluctuations. Combining RSSI with TX power data from advertising packets allows path loss calculation, which is more meaningful than raw RSSI for distance estimation. Despite these techniques, RSSI remains best suited for coarse proximity zones (near, mid, far) rather than precise distance measurement.

  

  

  
  
  




  
  
Related Terms

  

  

    
    TX Power
    
    RX Sensitivity
    
    Channel Sounding
    
    Direction Finding
    
    Indoor Positioning System
    
  





  

  
  

  
  

  
  
  

    
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Frequently Asked Questions


  

    
    

      
      

        
Our glossary covers 90+ BLE technical terms organized by category. Each term includes a definition, related terms, and links to relevant chips and guides.