However, if you are new to this area the interpretation of the plots may not seem to be clear.įollowing constellation is based on LTE physical layer specification. If you had chance with articles or papers /thesis about communication technology (especially with anything related to transmitter, reciever technology), you would have seen the plots as shown at the bottom right. Now let's describe on the relationship between SNR and Bit Error Rate in more quantitative way. If you are not familiar with this kind of concept, please give some more time until you understand the concept. as SNR goes lower, the probablity of error goes higher. You would notice that as SNR goes lower the range of constellation spread goes wider.
In this example, you see three cases of QAM constellation and each case is exposed to error with different SNR. You can say, the farther a black dot is from the red dots, the higher probable errors (Bit Error) occur. In the following plots, the red dots indicate the ideal constellation with almost no error and the black dots represents the statistical location of each data points with noises. See AWGN page for the details of the relationship between SNR and AWGN) (Note : Noise added to this example is AWGN. As a result, Bit Error Rate (BER) will increase and Sensitity will decrease. As you see, as SNR decreases the quality of the signal gets poorer (higher noise level). How does SNR impact the performance of a system (especially on the reciever of a transmission system) ? I think following plots would give you an intuitive understanding of this. In that case, the device use very complicated signal processing algorithm to estimate SNR and the method itself tend to be different depending on communication technology. However, if you have to measure SNR in a communication device (not in test equipment), you cannot use the same method as spectrum analyzer. You can get the rough estimate of SNR for a certain signal using a spectrum analyzer, but it may not be as easy as it sound to measure the accurate SNR since ideally this measurement should be done at RBW of 1 Hz. This is why in most communication text book or in most of measurement process, SNR rather than the absolute signal power is used as evaluation/test criteria. On the contrary, even if the signal power is very low, you would get good communication result if the noise power is much lower than the signal power. You would not get good communication result (low error or no error) if the noise power is high as well. Even if your signal power is very strong, You may think Signal Power is the most important factors for signal quality, but in theory Signal power alone does not mean anything in terms of representing signal quality which help you predict how much error will happen for your communication system. It is because SNR is one of the most important indicator to represent signal quality. You may think communication would be impossible in the negative SNR condition, but in reality there is communication system (technology) which is designed to work mostly in such a condition (e.g, CDMA, WCDMA). Negative SNR means that Signal power is lower than the noise power. SNR can be either positive and negative value if you represent it in dB scale. SNR can be represented in a graphical form as shown below. It is just the ratio of Signal Power and Noise Power as described below in mathematical form. It is pretty much self-explanatory and it would not need much explanation. In many case, it would be much easier to understand if you understand on what purpose (in what context) these are used. I will try to explain the concept of these terms as much as practical sense (hopefully). These terms are confusing almost everybody. There are several similar but a little bit different terminology that indicates the ratio between the wanted signal and the unwanted noise.
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