Residual sideband suppression (RSB) is one of key TX specs. We want to minimize this because this degrades EVM (when LO is centered to CC leading to signal and its image falling on top of each other) or degrades ACLR (when LO is not centered to CC leading to different signal and image locations). Mismatches in amplitude or phase of I and Q channels in IQ TX generate RSB. Therefore, IQ correction is a usual calibration routine that is followed in industry practice where IQ errors are measured and corrected. We discuss below how it is done in context of TX.
Consider an ideal IQ TX. I channel receives a cosine baseband signal from DAC and multiplies it with cosine LO. Q channel receives a sin baseband signal from DAC and multiplies with sin LO. Multiplication generates two sidebands:
Let
We can write output as follows:
where
Let’s take squares of these tones since we are interested in ratios of their powers.
If isLSB = -1, that is when we want to keep
If isLSB = +1, that is when want to keep
That means IRR is same no matter what sideband we transmit which makes sense since IRR should only be dependent upon gain and phase error.
We want to make some measurements to evaulate
Assume
Doing similar manipulations on numerator:
We can finally write IRR equation as follows:
which shows IRR is an equation of circle in plane of
We can figure out
Thus, you can calculate gain and phase errors by making three measurements. Graphically, it is the point where the three circles overlap.
(Tip: . A quick sanity check of phase error sign is to see if the IRR3 was better than IRR2. In that case, phase error that you applied partially cancelled the phase error in the system, therefore we can say the phase error in the system is of opposite polarity than what we applied. If IRR3 is worse than IRR2, then phase error in system has same polarity as of phase error you applied.)
Once you have figured out
Consider Q channel baseband and LO multiplication, we can write it as follows:
that is instead of saying phase error we can say it was a multiplication error as if our Q-channel LO was sin LO multiplied with
so our IQ TX with gain and phase errors is equivalent to figure in bottom left that is we can model gain and phase errors by gain scaling
We can calibrate the errors by doing opposite as shown in image below. This circuitry will be added in digital front end where data of I channel will be scaled by
We built an IQ TX in Cadence using ideal blocks like multipliers, summers and delay elements from ahdlLib library as shown in image below.
We added gain error of 0.075 to I channel BB and phase delay of 1.25 degree to Q channel LO. Our goal is now get these numbers from calibration algorithm presented above. We measure (or simulate in this case) raw IRR1, IRR2 with gain error of 0.01 applied and IRR3 with gain error of 0.01 and phase delay of 1 degree applied. Three measured numbers are shown in image below.
We made an Excel calculator (which is available to download below), plugged these numbers in, and this give us our calculated gain and phase error to be 0.071 and -1.26 degree (means delay). Hmm this is close but does not quite match the actual gain and phase errors in system which were 0.075 and -1.25 degree to be precise.
Let’s see what happens when we compute our
IRR improves from -28dBc to -54dBc after IQ calibration. Good but not perfect. So what is missing? Remember we assumed
Image below plots IRR with circle equation (dotted lines) and actual equation (solid lines). We can already see for gain error of 0.1 or more, the circle equation and actual equation don’t match. However, if gain and phase errors are small (i.e., for intrinsic IRRs better than -30dBc), circle equation is good enough.
[1] Wideband Digital Correction of I and Q Mismatch in Quadrature Radio Receivers (Hardware Friendly Implementation)
https://ieeexplore.ieee.org/document/857556
[2] I/Q Imbalance Calibration in Wideband Direct Conversion Receivers
https://ieeexplore.ieee.org/document/7790607
[3] A Low-Complexity I/Q Imbalance Calibration Method for Quadrature Modulator (Calibration Algorithm)
Summation of two vectors with phase
Assume a vector
RFInsights
Published: 04 June 2023
Last Edit: 04 June 2023