BIT RESOLUTION CALCULATOR UPDATE

Substituting these values give the following results. P F = 0, DAC full-scale output power (P F) (Eq. The parameters then for the three equations needed to compute NSD Q14 (Equations 2, 3, and 4) are as follows:

BIT RESOLUTION CALCULATOR UPDATE

The full-scale output power specification of the MAX5868 is 0dBm when generating a 100MHz sinewave using a 4.96Gsps update rate. Then, we will examine the input interface and see how the resolution and sample rate affect performance. First, we will look at the core 14-bit DAC independent of the input interface. Now, let us apply the above theory using the MAX5868 specifications.

We will assume that the noise is evenly distributed across the Nyquist zone of the converter and use it in the following equation:

The next step is the conversion of the noise power to a power spectral density value. P F = the output power specification of the DAC, in dBm and based on a full-scale sinewave. We will call this term P Q and compute it as follows: The first step in the conversion to NSD is to calculate the total noise power due to quantization within the Nyquist BW. Since this is an absolute power, we will use the full-scale output power specification of the DAC as our reference point, allowing the conversion of SNR Q to noise density due to quantization. Noise spectral density is a measure of the noise power, typically expressed in dBm or dBmV, within a specified bandwidth and usually normalized to 1Hz. Calculating Noise Spectral Density Due to Quantization The results will show that the NSD Q level at each stage of the MAX5868 ensures that the thermal noise is dominant and that further increases to the core DAC resolution are unwarranted. We will also estimate the level for the SNR THERM (NSD T) term against which the quantization noise will be compared. In order to facilitate this analysis, we will convert the calculated SNR Q to an ideal noise spectral density (NSD Q) due to quantization. We also need to consider the update rates at the various stages to make the comparison meaningful. The SNR due to quantization is useful information, but we need to compare this against the other terms in Equation 1 to determine the impact of the resolution of the DAC and input interface. The result of the calculation applied to DACs is the aggregate noise within the entire Nyquist bandwidth due to quantization. While Equation 2 is most often mentioned in reference to analog-to-digital converters (ADCs), it is equally useful in determining the impact of quantization noise in DAC applications. These sources combine to determine the total SNR as shown in the following calculation:Īnother common theorem in data conversion is the calculation of ideal SNR as a function of device resolution assuming no thermal or jitter contributions in other words, the SNR due to only quantization (SNR Q) as follows: In the case of a DAC, there are three primary sources of output noise: thermal noise, jitter noise, and quantization noise. The resolution of a data converter has a direct impact on the SNR performance of the device. If the input interface were only 14 bits, the quantization noise would dominate the thermal noise. One aspect of the design has resulted in an oft-repeated question: Why is the interface 16 bits yet the DAC is shown as 14 bits in the MAX5868? A short and sweet explanation is that the noise floor is determined by quantization noise, thermal noise, and jitter noise (clock noise).

Figure 1 shows the simplified block diagram from the MAX5868 datasheet.įigure 1. The first device in this family was the MAX5868, which was introduced in 2012, employs a parallel 16-bit double-data rate (DDR) low-voltage differential signal (LVDS) interface bus. Maxim Integrated manufactures a family of 16-bit radio frequency digital-to-analog converters (RF DACs) designed to provide high performance, wide-band signal generation.

Bit resolution calculator