Why non line of sight conditions doesn't effect estimation error?

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Ilgaz Onur Tas 2022-3-23

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https://ww2.mathworks.cn/matlabcentral/answers/1679034-why-non-line-of-sight-conditions-doesn-t-effect-estimation-error

回答： Riya 2024-1-16

Hello,

I am trying to calculate estimated position of the UE based on the code here. In the code it asks me to define los conditions as a logical array of 0 and 1's for the number of base stations. (0=nlos, 1=los) and calculates the path loss for multiple base stations and UE's. When I write los conditions as following for 5 base stations, UE Position Estimation Error doesn't change. I was expecting to have a more error in the full nlos condition. But it doesn't change for this two conditions. Anyone can explain the reason for that? I am attaching the result of different los condition array and results as an image.

los = [1 1 1 1 1]; %FULL LOS

los = [0 0 0 0 0]; %FULL NON-LOS

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Answer 1

Riya 2024-1-16

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https://ww2.mathworks.cn/matlabcentral/answers/1679034-why-non-line-of-sight-conditions-doesn-t-effect-estimation-error#answer_1390411

Hello Ilgaz,

Please note that in typical wireless communication systems, “Line-Of-Sight” (LOS) conditions often result in better signal propagation characteristics compared to “Non-Line-Of-Sight” (NLOS) conditions. NLOS conditions can lead to higher path loss, multipath fading, and increased likelihood of obstructions, which can degrade signal quality and increase estimation errors for tasks such as “User Equipment” (UE) position estimation.

To troubleshoot this issue, you can refer following steps:

Review the path loss model and ensure it differentiates between LOS and NLOS conditions.
Verify that the LOS array is correctly used in the path loss calculations.
Examine the position estimation algorithm to see if it accounts for propagation conditions.
Check for any compensating mechanisms or error sources that could be overshadowing the LOS/NLOS effects.
Run separate, controlled simulations or consult the documentation for the model to understand how LOS/NLOS conditions are expected to impact the results.