The present disclosure relates to digital communications receivers and, more particularly, to equalizers suitable for use with high-rate signaling, and pulse-amplitude modulated (PAM)/quadrature amplitude modulated (QAM) signal constellations.
Most integrated circuit devices have become so complex that it is impractical for electronic device designers to design them from scratch. Instead, electronic device designers rely on predefined modular units of integrated circuit layout designs, arranging and joining them as needed to implement the various functions of the desired device. Each modular unit has a defined interface and behavior that has been verified by its creator. Though each modular unit may take a lot of time and investment to create, its availability for re-use and further development cuts product cycle times dramatically and enables better products. The predefined units can be organized hierarchically, with a given unit incorporating one or more lower-level units and in turn being incorporated within higher-level units. Many organizations have libraries of such predefined modular units for sale or license, including, e.g., embedded processors, memory, interfaces for different bus standards, power converters, frequency multipliers, sensor transducer interfaces, to name just a few. The predefined modular units are also known as cells, blocks, cores, and macros, terms which have different connotations and variations (“IP core”, “soft macro”) but are frequently employed interchangeably.
The modular units can be expressed in different ways, e.g., in the form of a hardware description language (HDL) file, or as a fully-routed design that could be printed directly to a series of manufacturing process masks. Fully-routed design files are typically process-specific, meaning that additional design effort would usually be needed to migrate the modular unit to a different process or manufacturer. Modular units in HDL form require subsequent synthesis, placement, and routing steps for implementation, but are process-independent, meaning that different manufacturers can apply their preferred automated synthesis, placement, and routing processes to implement the units using a wide range of manufacturing processes. By virtue of their higher-level representation, HDL units may be more amenable to modification and the use of variable design parameters, whereas fully-routed units may offer better predictability in terms of areal requirements, reliability, and performance. While there is no fixed rule, digital module designs are more commonly specified in HDL form, while analog and mixed-signal units are more commonly specified as a lower-level, physical description.
Serializer-deserializer (SerDes) cores are a frequent need for device designs that employ modern data communications standards, which continue to evolve towards higher symbol rates and larger numbers of bits per channel symbol. At higher symbol rates, channel symbols become more attenuated and dispersed as they propagate, causing evermore severe intersymbol interference (ISI) at the receiving end of the channel. When trying to detect the channel symbols, receivers must contend with this ISI in addition to the channel noise that contaminates the receive signal.
Due to their relative low complexities, linear equalizers and decision feedback equalizers (DFE) are typically preferred for facilitating channel symbol detection without undue noise enhancement. Yet as data rates push ever closer to channel capacity, these equalizers may fail to provide sufficiently low error rates. Particularly in high ISI channels, DFEs may suffer from error propagation, causing error bursts that can significantly degrade performance.
Accordingly, there are disclosed herein receivers, methods, and cores that provide decision feedback equalization with efficient burst error correction. An illustrative receiver includes: a decision feedback equalizer that derives symbol decisions from a receive signal; a subtractor that determines an equalization error for each said symbol decision; and a post-processor that operates on the symbol decisions and equalization error to detect and correct symbol decision errors.
One illustrative receiving method includes: using a decision feedback equalizer to derive symbol decisions from a filtered receive signal; determining an equalization error for each said symbol decision; and processing the symbol decisions and equalization error to detect and correct symbol decision errors.
An illustrative semiconductor intellectual property core generates circuitry for implementing a receiving and method as described above.
Each of the foregoing receiver, method, and core implementations may be embodied individually or conjointly and may be combined with any one or more of the following optional features: 1. the post-processor detects error exit symbols by comparing the equalization error's magnitude to a threshold. 2. the decision feedback equalizer includes a forward filter that shapes a channel response to 1+γD. 3. the threshold to detect error exit symbols is programmable. 4. the decision feedback equalizer derives M-ary PAM symbol decisions, M>2, and the error exit symbol is limited to 0 and (M−1). 5. the post-processor includes a metric circuit to determine a likelihood difference for each of multiple different error burst lengths. 6. the post-processor includes a corrector circuit that finds the minimum likelihood difference and when appropriate corrects a corresponding number of decision errors preceding the error exit symbol. 7. the metric circuit and corrector circuit are disabled until an error exit symbol is detected. 8. processing includes finding a minimum likelihood difference for each error exit symbol and if the minimum likelihood difference so indicates, correcting a corresponding number of decision errors preceding that error exit symbol.
While specific embodiments are given in the drawings and the following description, keep in mind that they do not limit the disclosure. On the contrary, they provide the foundation for one of ordinary skill to discern the alternative forms, equivalents, and modifications that are encompassed in the scope of the appended claims.
For context,
The pluggable modules 206 may each include a retimer chip 210 and a microcontroller chip 212 that controls operation of the retimer chip 210 in accordance with firmware and parameters that may be stored in nonvolatile memory 214. The operating mode and parameters of the pluggable retimer modules 206 may be set via a two wire bus such as 12C or MDIO that connects the microcontroller chip 212 to the host device (e.g., switch 112). The microcontroller chip 212 responds to queries and commands received via the two wire bus, and responsively retrieves information from and saves information to control registers 218 of the retimer chip 210.
Retimer chip 210 includes a host-side transceiver 220 coupled to a line-side transceiver 222 by first-in first-out (FIFO) buffers 224. The transceivers may be SerDes cores having decision feedback equalizers (DFEs) for high baud rate reception.
yk=L(dk)+γL(dk−1)+nk, (1)
where dk∈{0, 1, 2, 3} represents the transmitted PAM4 symbols, L(dk) is a fixed mapping of PAM4 symbols to their corresponding signal levels, and nk represents the noise plus some other impairments.
A summer 406 combines the filtered receive signal with a feedback signal fk to produce an equalized signal sk having reduced trailing ISI and thus (in the absence of significant channel noise) having open decision eyes such as those of
A post-processor 420 operates on the symbol decisions and equalization error to detect and correct symbol decision errors. Before discussing implementation details, we provide the following derivation to facilitate understanding.
Without loss of generality, the following discussion assumes the nominal signal range is −3 to +3, such that the signal levels for symbols 0, 1, 2, 3, are −3, −1, +1, and +3, respectively. The equalized signal sk is expressible as:
sk=yk−γ·L({circumflex over (d)}k−1) (2)
or equivalently as:
sk=L(dk)+γ[L(dk−1)−L({circumflex over (d)}k−1)]+nk (3)
When a decision error happens such that dk−1≠{circumflex over (d)}k−1,
|L(dk−1)−L({circumflex over (d)}k−1)|≥2, (4)
which for the contemplated range of signal to noise ratios (SNR) can be assumed to mean
L(dk−1)−L({circumflex over (d)}k−1)=±2 when dk−1≠{circumflex over (d)}k−1). (5)
In the presence of a decision error, the equalized signal is shifted from its desired value by γ[L(dk−1)−L({circumflex over (d)}k−1)]=±2γ. In high baud rate systems, the DFE tap γ is typically greater than or equal to 0.5, and often about 1.0. This shift exceeds the distance between the symbol level and the decision threshold, likely causing the decision error to propagate from one symbol interval to the next, causing an extended error burst until
dk=3 with L(dk−1)−L({circumflex over (d)}k−1)>0, or (6a)
dk=0 with(dk−1)−L({circumflex over (d)}k−1)<0 (6b)
Alternatively, a sufficiently large noise signal nk could theoretically overcome the decision error shift to end the error burst, but in the contemplated SNR range |nk|<1.0 with high probability so we neglect this alternative herein and focus on the conditions given in equations (6a) and (6b).
Equations (6a) and (6b) are defined as the error exit conditions, with the corresponding dk designated herein as the “error exit symbol”. The following discussion shows that the equalization error associated with error exit symbols is conspicuously larger than the expected error level.
We define error sign sek=sgn (L(dk)−L({circumflex over (d)}k)), meaning sek ∈{±1} in the presence of a decision error dk−1≠{circumflex over (d)}k−1,
sk=L(dk)+2γ·sek−1+nk (7)
To simplify this discussion, assume for the moment γ=1. If the error exit conditions (6a), (6b) are not satisfied, we have the following:
L(dk)−L({circumflex over (d)}k)=−1·[L(dk−1)−L({circumflex over (d)}k−1)] (8)
sek=−1·sek−1 (9)
Assume the error exit conditions are not satisfied until dk+Δ, i.e., {circumflex over (d)}k−1, {circumflex over (d)}k . . . , {circumflex over (d)}k+Δ are burst errors. The following equations can be derived for the burst errors:
sek+i=(−1)i·sek,0≤i≤Δ (10)
L(dk+i)−L({circumflex over (d)}k+i)=(−1)i·[L(dk)−L({circumflex over (d)}k)],0≤i≤Δ (11)
Define equalization error ek as
ek=sk−L({circumflex over (d)}k) (12)
Consider the equalization error in three cases: no decision errors, burst errors, and error exit symbols. If there are no decision errors, dk−1={circumflex over (d)}k−1, {circumflex over (d)}k={circumflex over (d)}k The equalization error is
ek=nk (13)
If there are burst errors dk−1≠{circumflex over (d)}k−1, dk≠{circumflex over (d)}k, from (3), (11) and (12), the equalization error is
ek=sk−L({circumflex over (d)}k)=L(dk)−L({circumflex over (d)}k)+L(dk−1)−L({circumflex over (d)}k−1)+nk (14)
ek=nk (15)
Now, if the burst errors exit at dk+Δ, i.e., dk+Δ satisfies the error exit condition (6a) or (6b), dk+Δ={circumflex over (d)}k+Δ, L(dk+Δ)=L({circumflex over (d)}k+Δ). From Equation (3), (5) and (11), the equalization error ek+Δ is given as follows.
ek+Δ=sk+Δ−L({circumflex over (d)}k+Δ)=(−1)Δ·[L(dk−1)−L({circumflex over (d)}k−1)]+nk+Δ (16)
ek+Δ=(±2)+nk+Δ (17)
In the contemplated SNR range |nk|<1.0 with high probability, so that the equalization error in equation (17) is conspicuously different from the equalization error of equations (13) and (15). As γ falls below 1, the equalization error of equation (15) grows as the error of equation (17) falls, but depending on SNR they may remain distinguishable until γ approaches 0.5, and in any case they should be readily distinguishable from the equalization error when no decision errors are present.
Summarizing the equalization errors computed in (13), (15) and (17), we have the following:
For a programmable error threshold Te, if |ek|>Te and symbol decision {circumflex over (d)}k ∈{0,3}, then {circumflex over (d)}k is declared as the error exit symbol and dk−1 is likely a single error or the end of an error burst. (The feedback tap coefficient γ is a good choice for the value of threshold Te.) Once the possible errors are detected, an efficient maximum likelihood (ML) search may be performed to verify whether the possible errors are indeed errors and, if so, to correct them.
To illustrate the ML search method, assume {circumflex over (d)}k is declared as the error exit symbol, and let M be the maximum length of the trace back from {circumflex over (d)}k, i.e., the ML search is performed within the window from {circumflex over (d)}k to {circumflex over (d)}k−M. Define the initial (varying-length) decision sequences as:
{circumflex over (d)}i=[L({circumflex over (d)}k−1),L({circumflex over (d)}k−2), . . . ,L({circumflex over (d)}k−i)],1≤i≤M (18)
with competing decision sequences:
{circumflex over (d)}′i={circumflex over (d)}i+2sek·[(−1)0,(−1)1, . . . ,(−1)i−1],1≤i≤M (19)
In (19), sek is redefined as sek=sgn(ek), and this definition is used for sek in the remaining part of this description. For the sequence of filtered receive signals Y={yk−1, yk−1, . . . , yk−i}, the likelihood of {circumflex over (d)}i is computed as:
Pr{Y|{circumflex over (d)}i}∝Pi=−Σj=0i(yk−j=ŷk−j)2, (20)
where
ŷk−j=L({circumflex over (d)}k−j))+γ·L({circumflex over (d)}k−j−1) (21)
It can be shown from the combination of (2), (12), and (21), that
ek−j=yk−j−ŷk−j (22)
The likelihood of {circumflex over (d)}′i is computed as:
Pr{Y|{circumflex over (d)}′i}∝P′i=−ΣΣj=0i(yk−j−ŷ′k−j)2, (23)
where
ŷ′k−j=L({circumflex over (d)}′k−j)+γ·L({circumflex over (d)}′k−j−1). (24)
In (24), {circumflex over (d)}′k−j and L({circumflex over (d)}′k−j) are given by
{circumflex over (d)}′k−j={circumflex over (d)}k−j+sek·(−1)j−1,1≤j≤i, (25)
L({circumflex over (d)}′k−j)=L({circumflex over (d)}k−j)+2·sek·(−1)j−1,1≤j≤i (26)
We note that L({circumflex over (d)}′k)=L({circumflex over (d)}k) and {circumflex over (d)}′k={circumflex over (d)}′k since {circumflex over (d)}k is assumed to be the error exit symbol.
Let the competing error e′k−j be defined by
e′k−j=yk−j−ŷ′k−j (27)
It can be shown that
ê′k−j=ek−j−Δek−j (28)
Δek−j=L({circumflex over (d)}′k−j)−L({circumflex over (d)}k−j)+γ·(L({circumflex over (d)}k−j−1)−L({circumflex over (d)}k−j−1) (29)
In (29) L({circumflex over (d)}′k−j)=L({circumflex over (d)}k−j), when j=0 and j=(i+1).
Define ΔPi=Pi−P′i. After some mathematical operations, it can be shown that ΔPi is given by
ΔPi=Σj=0i[(Δek−j)2−2·Δek−j·ek−j] (30)
If i=1,
ΔPi=4γ2−4·γ·sek·ek+4−4·sek·ek−1 (31)
If i>1,
Δek−j=2sek·(−1)j−1·(1−γ),1≤j≤i, (32)
ΔPi=4(γ2−γ·sek·ek+1−sek·(−1)i−1·ek−i−Σj=1i−1cek−j) (33)
where cek−j is given by
cek−j=(1−γ)2−sek·(1−γ)·(−1)j−1·ek−j (34)
When the DFE tap γ=1,
cek−j=0,1≤j≤i, (35)
Omitting the common factor 4, from (33), the ΔPi computation is further simplified to:
ΔPi=γ2−γ·sek·ek+1−sek·(−1)i−1·ek−i (36)
Now let
If ΔPi_min<0, the previous i_min decisions {circumflex over (d)}k−j, 1≤j≤i_min are errors that should be corrected, replacing {circumflex over (d)}k−j with
d′k−j={circumflex over (d)}k−j+sek·(−1)j−1,1≤j≤i_min (38)
Conversely, if ΔPi_min≥0, the decisions {circumflex over (d)}k−j, 1≤j≤M, do not need to be changed.
If there exists j, 1≤j≤M, such that the competing symbol decision is invalid, i.e., {circumflex over (d)}′k−j ∉{0, 1, 2, 3}, then let J be the minimum of such values, such that J−1 is the number of potential error burst lengths. The ΔPi only needs to be computed for 1≤i≤J instead of 1≤i≤M, and the rest of the process remains unchanged.
Now, we summarize the proposed DFE postprocessing method as follows: (A) Monitor symbol decisions for an error exit symbol (a symbol {circumflex over (d)}k∈{0,3} with |ek|>Te). (B) when an error exit symbol is detected, compute the likelihood differences ΔPi for different burst lengths 1≤i≤min{M,J}. (C) Find the minimum likelihood difference and corresponding index i_min,
(D) If ΔPi_min<0, then replace decisions {circumflex over (d)}k−j, 1≤j≤i_min, with competing symbol decisions {circumflex over (d)}′k−1. If ΔPi_min≥0, no correction is needed.
The limit on trace back length M can be set to, e.g., 32, without adding undue complexity. Other limits can also be evaluated empirically for suitability. The main computation load of the proposed algorithm is the sequence metric ΔPi computation in (33) and (34). Note that the γ2, (1−γ)2 and (1−γ) only need to be computed once for large chunk of data; and sek ∈{±1}. The overall computation complexity of the algorithm is substantially lower than that for maximum likelihood sequence detectors (MLSD) or even than for the reduced complexity 2-state MLSD described in co-pending application Ser. No. 17/656,751.
A control circuit 506 evaluates the sequence of symbol decisions and equalization errors from the decision feedback equalizer to detect potential error exit symbols, enabling metric circuit 502 and corrector circuit 504 to operate only when such symbols are detected. Note that circuits 502, 504 have shift registers that continue to operate when these circuits are “disabled”. It is these shift registers that enable the post-processing operation of the corresponding circuits.
On the left side of
When the DFE tap γ=1, the post-processor can be simplified.
With reference to equation 36, we observe that the minimum likelihood difference will be determined by the maximum of the sign-changed errors for the valid competing symbol decisions. The validity signals vk−i are determined as in
A set of multiplexers 820 pass the sign-changed errors for the valid competing symbol decisions. A chain of compare-and-select (CAS) units 821 each pass the larger of their inputs, thereby determining emax, the maximum of the sign-changed errors. The comparator outputs of the CAS units are combined by a chain of logical OR gates to derive the replacement control signals rk−j for the multiplexers of the shift register 702. Note, however, a set of AND gates 822 blocks the replacement control signals unless equation (36) using emax produces a negative value, in which case it is desired to replace the original symbol decisions with their competing symbol decisions.
Numerous alternative forms, equivalents, and modifications will become apparent to those skilled in the art once the above disclosure is fully appreciated. Though PAM4 was used for the foregoing discussions, the disclosed principles are applicable to larger PAM constellations and to QAM signaling. Though a positive feedback coefficient value was presumed, the disclosed principles are similarly applicable with negative feedback coefficient values. Moreover, the disclosed analysis is readily extendible to multiple feedback taps for DFEs with suitable coefficient values. It is intended that the claims be interpreted to embrace all such alternative forms, equivalents, and modifications that are encompassed in the scope of the appended claims.
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Entry |
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U.S. Appl. No. 17/656,751 as filed in U.S. Patent and Trademark Office, filed Mar. 28, 2022 by inventors Yu Liao and Junqing Sun, titled: “Reduced-Complexity Maximum Likelihood Sequence Detector Suitable for M-ary Signaling”. |
Number | Date | Country | |
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20230318883 A1 | Oct 2023 | US |