SFDR is frequently written in the units of dBHz^(2/3), particularly for fiber optic links. Fiber optic links can often have such high bandwidth, that assuming a bandwidth in SFDR is unhelpful or misleading. Normalizing to 1Hz therefore became a standard practice. The units of SFDR for a real system with a bandwidth are dB.
Now consider that the real system has a specific bandwidth. The real SFDR can be calculated using the following formulas: SFDR_real = SFDR_1Hz – (2/3)*10*log10(BW)
The standard definition for noise figure (NF) is the degradation of signal to noise ratio (SNR). That is, if the output noise power of the system is increased more than the output signal power, then this implies a significant noise figure and a degredation of SNR.
For an RF photonic link, there are a couple assumptions that result in a slightly altered definition and calculation for noise figure. One assumption is that the input noise is the thermal noise (kT), such as would be detected from an antenna receiver. It is also the case that RF photonic links may be employed in a case where the input signal power level is not defined. In simple telecommunications aplications, it is standard to expect a certain input power level, but as a communications system at a radar front end for instance, the input signal is not known. We can use the gain of the link as a relationship between output signal and input signal instead of a known input and output signal power.
It is a goal of the link designer in those cases to ensure that all true signals can be distinguished from noise. For these reasons, we may also think of noise figure in the following definition:
Noise figure (NF) is the difference between the total equivalent input noise and thermal background noise.
The equivalent input noise is the output noise without considering the gain of the link.
For the noise figure calculation, we have then:
NF = 10*log_10( EIN / GkT ),
where EIN is the equivalent input noise, G is the link gain, k is Boltzmann’s constant, and T is the temperature in Kelvin.
RF Photonic links (also called Microwave Photonic Links) are systems that transport radiofrequency signals over optical fiber. The essential components of an RF photonic link are the laser as a continuous-wave (CW) carrier, a modulator as a transmitter and the photodetector as a receiver. A low-noise amplifier is often used before the modulator.
Optical fiber boasts much lower loss over longer distances compared to coaxial cable, and this flexibility of optical fiber is one advantage over conventional microwave links. Another advantage of RF photonic links are their immunity to electromagnetic interference, which plays a more significant role in electronic warfare (EW) applications. RF Photonic links are employed in telecommunications, electronic warfare, and quantum information processing applications, although the performance requirement in each of these situations vary. In telecommunications, a high bandwidth is required, while in EW applications having high spurious-free dynamic range (SFDR) and a low noise figure (NF) is critical. In quantum information processing applications, a low insertion loss is critical.
In EW scenarios, unlike in telecommunications, the expected signal frequency and signal power is unknown. This is because typically, an RF photonic link is found as a radar receiver. In a system with high SFDR and low NF, distortion is minimized, the radar has stronger reliability and range, and smaller signals can be registered. Here is a demonstration of two scenarios with different SFDR and NF:
Any object with a temperature above absolute zero (Kelvin) radiates electromagnetic energy, or thermal noise. Noise is generated by the earth and cosmos, and this is background thermal noise, which is received by an antenna.
Thermal background noise is the starting point for system performance. A signal of strength below the thermal background noise will be indistinguishable from noise.
The thermal background noise power is proportional to the temperature (P = kTB, k being Boltzmann’s constant, T the temperature in Kelvin, and B the bandwidth in hertz). The thermal background noise power spectral density is the fundamental noise minimum at -174 dBm/Hz at 300K.
The gain of the device or system further amplifies the thermal background noise. RF Photonic links most often use a low noise amplifier (LNA) directly before the modulator, amplifying the thermal background noise.
The definition of thermal noise applied to electronics is the movement of charge carriers caused by temperature in a conductor.
In general, the third order distortion tones are understood to exist as in-band distortion at frequencies 2ω2-ω1 and 2ω1-ω2 in a two tone intermodulation test. Third order distortion also exists at frequencies ω1 and ω2. Second order distortion tones are found outside of a narrowband system at 2ω2, 2ω1, and ω1+ω2.
Consider the two-tone input of a non-linear system with frequencies ω1 and ω2:
Vin = A[cos(ω1t)+cos(ω2t)]
The second order and third order distortion tones are calculated on the following page. In summary, the tones are shown in the table below. This shows that third order distortion tones are found not only in the positions mentioned above, but also contribute to the fundamental tone frequencies. In a spurious-free system, all third order tones will be below the noise floor. This is verified in MATLAB with ω1, ω2 at 500kHz, 501kHz.
In the term spurious-free dynamic range (SFDR), spurious-free means that non-linear distortion is below the noise floor for given input levels. The system is spurious when non-linear distortion is present above the noise floor. The system is spurious-free when non-linear distortion is below the noise floor. SFDR therefore is the range of output levels whereby the system is undisturbed by non-linear distortion or spurs.
SFDR contrasts with compression dynamic range (or linear dynamic range (LDR)) which is the range of output levels whereby the fundamental tone is proportional to the input, irrespective of distortion tone levels. The fundamental tone is no longer considered to be linear beyond the 1dB compression point, after which the output fundamental tones do not increase at the same rate as the input fundamental tones.
Spurs are non-linear distortion tones generated by non-linearities of a system. The output of a non-linear system can be modeled as a Fourier series.
The first term a0 is a DC component generated by the non-linear system. The second term a1Vin is the fundamental tone with some level of gain a1. The third term a2Vin2 is a second order non-linear distortion tone. The fourth term a3Vin3 is the third-order non-linear distortion tone. Further expansion of the Fourier series generates more harmonic and distortion tones. Even order harmonic distortion tones are usually outside of the band of interest, unless the system is very wideband. Odd order distortion tones however are found much closer to the fundamental tone in the frequency domain. SFDR is usually taken with respect to the third order intermodulation distortion, however it may also occasionally be taken for the fifth order (or seventh).
The units of spurious-free dynamic range (SFDR) are dB·Hz^(2/3). The units can be a source of confusion. The short answer is that it is a product of ratios between power levels (dBm) and noise power spectral density (dBm/Hz). The units of dBHz^(2/3) are for SFDR normalized to a 1Hz bandwidth. For the real SFDR of a system, the units are in dB.
Now, we need to look at the units of both OIP3 and EIN. The units of OIP3 are dBm and the units of the equivalent input noise (a noise power spectral density) are dBm/Hz.
SFDR = (2/3)*(OIP3 – EIN)
[SFDR] = (2/3) * ( [dBm] – [dBm/Hz] )
Now, remember that in logarithmic operations, division is equal to subtracting the denominator from the numerator. and therefore:
[dBm/Hz] = [dBm] – 10*log_10([Hz])
Note that the [Hz] term is still in logarithmic scale. We can use dBHz to denote the logarithmic scale in Hertz.
[dBm/Hz] = [dBm] – [dBHz]
Substituting this into the SFDR unit calculation:
[SFDR] = (2/3) * ( [dBm] – ( [dBm] – [dBHz] )
This simplifies to:
[SFDR] = (2/3) * ( [dBm] – [dBm] + [dBHz] )
Remember that the difference between two power levels is [dB].
[SFDR] = (2/3) * ( [dB] + [dBHz] )_
The units of [dB] + [dBHz] is [dBHz], as we know from the same logarithmic relation used above for [dBm] and [dB].
[SFDR] = (2/3) * [dBHz]
Now, remember that this is a lkogarithmic operation, and a number multiplying a logarithm can be taken as an exponent in the inside of the logarithm.Therefore, we can express Hz again explicitly in logarithm scale, and move the (2/3) into the logarithm.
We’ll begin a discussion on the topic of analog system quality. How do we measure how well an analog system works? One over-simplistic answer is to say that power gain determines how well a system operates. This is not sufficient. Instead, we must analyze the system to determine how well it works as intended, which may include the gain of the fundamental signal. Whether it is an audio amplifier, acoustic transducers, a wireless communication system or optical link, the desired signal (either transmitted or received) needs to be distinguishable from the system noise. Noise, although situationally problematic can usually be averaged out. The presence of other signals are not however. This begs the question, which other signals could we be speaking of, if there is supposed to be only one signal? The answer is that the fundamental signal also comes with second order, third order, fourth order and higher order distortion harmonic and intermodulation signals, which may not be averaged from noise. Consider the following plot:
We usually talk about Third Order Intermodulation Distortion or IMD3 in such systems primarily. Unlike the second and fourth order, the Third Order Intermodulation products are found in the same spectral region as the first order fundamental signals. Second and fourth order distortion can be filtered out using a bandpass filter for the in-band region. Note that the fifth order intermodulation distortion and seventh order intermodulation distortion can also cause an issue in-band, although these signals are usually much weaker.
Consider the use of a radar system. If a return signal is expected in a certain band, we need to be able to distinguish between the actual return and differentiate this from IMD3, else we may not be able to trust our result. We will discuss next how IMD3 is avoided.
Linearity is the measure of a system’s performance as an output signal being proportional to the input signal level. Not every system can be expected to perform ideally and thus linearly. Devices such as diodes and transistors are examples of non-linear systems.
The intercept point of the third order, IP3 is a measure of the linearity of a system. IP3 is the third order of a Taylor series expansion of the input signal’s presence in the frequency domain. Being third order, this term in a Taylor series expansion is understood as distortion since it is different from the sought output signal. In contrast to the second order harmonics, which fall outside of the frequency band of the first order signal, the third order is found in the same frequency band as the original or first order signal. Similarly, consecutive even orders (4, 6, 8, etc) are found outside of the frequency band of the first order signal. Consecutive odd orders beyond the third order such as IP5 and IP7 also cause distortion but are not of primary focus since the amplitude of these order signals are weaker after consequent exponentiation.
The meaning of an intercept point of an nth order (IPn) on a dBm-dBm axis is the point at which the first-order and nth-order powers would be equal for a given input power. In the case of IP3, this indicates the power level needed for a third-order power to potentially drown out the first-order signal with distortion. The 1 dB compression point defines the range of linear operation for a system.