Receiver options—decision feedback equalization (DFE): DFE is a powerful tool for legacy channel management (Fig. 16). DFE can’t improve every possible channel. However, many channels that have insufficient bandwidth and/or reflections, which results in no discernable RX eye opening at the receiver, can be made to operate robustly.
Going back to the earlier pulse response figure ( Fig. 9, again ), a DFE functionally operates on the pulse-response principle: The ideal response entering the receive slicer should have a single, non-zero entry at the main sample point and “zero” entries at subsequent samples around the main value. The circuit consists of a multi-tap finite impulse response filter, whose input and output are looped around the receive data slicer. Circuit algorithms such as LMS are then used to adjust the individual tap weights toward the ideal response discussed above.
While the circuit, by virtue of the feedback from the slicer, does meet the classical DSP definition of IIR (output feeds back into the input), the circuit is often considered as FIR because the span of control for which the DFE can modify the pulse response is limited to the number of taps in the circuit. This is different from the next receiver structure we’ll address, CTLE. However, the advantage of DFE is that within the span of control, the ability to adjust for discontinuities is much more granular and tap-to-tap independent.
Figure 17, a pulse response example of DFE, illustrates DFE principles. The circuit is a three-tap DFE with a presumed bit rate of 8 Gbits/s. The orange arrow represents the pulse response shaping caused by the pre-cursor emphasis of the three-tap transmitter discussed earlier, and not by the receiver. The three green arrows span the range (in time) of discontinuity control that each of the three independent RX taps may possess. Note that the fourth pulse (at t = 0.625 ps) shows no improvement. Because this DFE is only three taps, it’s not possible to deterministically control any discontinuity outside of a 0.375 ps (3UI or three-tap) window from the main pulse.
One other point of note about pulse responses: Intermediary non-zero excursions of the response, which aren’t located on the baud lines, don’t adversely affect the signal quality. With a baud rate equalizer, it’s important to maximize the energy of the main cursor and minimize the energy at the pre- and post-cursors each time a sample is taken.
DFE structures have the following advantages/disadvantages:
- Autonomous adjustment
- Independent control of each tap within the circuit
- No magnification of channel noise
- Burst errors/error propagation (mitigated PCIe replay scheme)
- Finite control range that expands linearly with the number of taps (size/power)
- Adjusts post-cursor response only
- Difficulty converging in the presence of significant data wander
It’s the ability of a properly functioning DFE circuit to autonomously adjust to the characteristics of the channel that makes it very powerful. But just as with any high-end vehicle, performance comes at a cost—power. DFE can add anywhere from 15% to 30% of the overall SERDES power for an optimized PCIe design. While the PCIe Gen 3 specification doesn’t require DFE, it’s probable that many high-performance SERDES will likely employ such a structure. Depending on size and power, there’s a likely potential that the five-tap DFE, common in the OIF community, also will become commonplace in PCIe.
Receiver options—fixed linear equalization: Linear equalization poses an attractive alternative to pure digital forms due to lower power consumption. Because PCIe places such a high importance on low power consumption, linear options have been an attractive alternative in Gen2.
On the other hand, Gen 3 devices that maintain the absolute lowest metric in power and size are likely to opt for linear equalization only. In well-designed new applications, such devices can provide solid performance. The questions will be their applicability to service today’s legacy backplanes, and the tradeoff between channel design and silicon cost. The evolution of linear equalization can be seen with a simple channel-equalization scheme (Fig. 18).
This typical passive-line equalizer operates by reducing the overall signal amplitude. Energy in the high-frequency band passes through the capacitor with minimal loss. Low-frequency components pass through an additional attenuation (R), causing an overall amplitude balance that counterbalances the high-frequency roll-off of typical channels. This conceptually mimics the same functionality as PCIe transmitter de-emphasis (post-cursor) equalization.
To better visualize the single-pole response of such a circuit and how it could modify the signal spectrum, Figure 19 depicts a frequency plot for several potential filter settings for a 5-Gbit/s link. Channel insertion loss is 6 dB. Signal components below 2.5 GHz undergo varying amounts of additional attenuation. Components near 2.5 GHz (5 Gbits/s fundamental) pass through the channel at the base insertion.
Going back to the earlier discussion of the channel and how the higher frequencies are more attenuated—the filter attempts to implement an inverted response so that the net output is flat across frequencies. Typical of many Gen2 PCIe devices, several stages of these filter circuits are manually switched in by the user.
Adjustable linear equalizers: Notice that the transfer function, H(s), for the network is an RC time constant that decays to infinity—it has what’s known as an “infinite impulse response.” Adaptive linear filter options differ by placing the linear element either inside or outside the decision feedback loop. With a continuous time linear equalizer (CTLE), the linear element is placed before the slicer. The receiver structure conceptually employs a similar design to the passive-line equalizer, but will allow a range of impedance and gain control (variable R, for example) so that filter and/or corner frequency can be adjusted automatically and overall amplitude can be adjusted. Proprietary algorithms perform the adjustment in order to observe the data before and after the slicer. A comparison of the filtered response to that of the sliced response can be used to make adjustment.
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