RSSI Modification for Device Noise in Wi-Fi
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Solution Overview
Problem
Wi-Fi performance is affected by device noise, leading to reduced signal-to-noise ratio (SNR) values, as existing wireless networks do not effectively adjust transmit power in response to increased noise, resulting in suboptimal communication for devices connected to access points using IEEE 802.11 standards.
Innovation Solution
A wireless client device modifies its feedback received signal strength indicator (RSSI) value based on device noise, determined using a modulation coding scheme (MCS) index, to maintain an SNR threshold by transmitting a reduced RSSI value to the access point, which then enhances transmit power, thereby optimizing Wi-Fi performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If transmit power is increased to compensate for device noise, then signal-to-noise ratio is improved, but energy consumption increases
Solution Approach 1:
The system implements feedback by monitoring MCS index changes that indicate device noise conditions, then adjusting RSSI values accordingly. This closed-loop approach allows the access point to dynamically adapt transmit power only when noise conditions change, rather than continuously increasing power, thus maintaining SNR while minimizing unnecessary energy consumption.
Solution Approach 2:
The invention changes the RSSI parameter based on detected noise conditions (through MCS index monitoring). By modifying the RSSI value to reflect actual channel conditions including device noise, the system enables more accurate transmit power adjustment that maintains communication reliability without excessive energy usage.
2Reliability
If transmit power is increased to maintain SNR threshold, then communication reliability is improved, but device complexity increases due to noise monitoring and RSSI adjustment mechanisms
Solution Approach 1:
The MCS index serves as an intermediary that indirectly indicates device noise conditions without requiring direct noise measurement. By monitoring changes in the MCS index (which the access point already tracks for throughput optimization), the system can infer noise conditions and adjust RSSI accordingly, avoiding the need for complex direct noise monitoring hardware or algorithms.
3Reliability
If RSSI value is reduced to account for device noise, then signal-to-noise ratio is maintained, but measurement precision of actual signal strength is compromised
Solution Approach 1:
The RSSI value is made dynamic rather than static. The system adjusts the RSSI value in real-time based on changing noise conditions detected through MCS index monitoring. This dynamic adjustment allows the RSSI to accurately represent effective signal strength under varying noise conditions, maintaining measurement precision for communication purposes while accounting for device noise impact on SNR.
Data Source
AI summary
In one example, a device may include a transceiver to receive a signal at a first transmit power from an access point via a wireless network connection. The first transmit power may be based on a feedback received signal strength indicator (RSSI) value. Further, the device may include a noise detection unit to determine device noise generated in the device and a signal-to-noise ratio (SNR) monitoring unit to determine that an SNR value associated with the wireless network connection falls below a threshold due to the device noise. Furthermore, the device may include a control unit to modify the feedback RSSI value upon determining that the SNR value falls below the threshold and transmit the modified feedback RSSI value to the access point via the transceiver.