The present invention relates to communications in general and in particular to the transmission of signals capable of conveying information and detection of those signals in wired communication.
In communication systems, a goal is to transport information from one physical location to another. It is typically desirable that the transport of this information is reliable, is fast and consumes a minimal amount of resources. Methods of information transport are broadly categorized into “baseband” methods that dedicate use of the physical communications channel to one transport method, and “broadband” methods that partition the physical communications channel in the frequency domain, creating two or more independent frequency channels upon which a transport method may be applied.
Baseband methods may be further categorized by physical medium. One common information transfer medium is the serial communications link, which may be based on a single wire circuit relative to ground or other common reference, multiple such circuits relative to ground or other common reference, or multiple such circuits used in relation to each other. A common example of the latter uses differential signaling (“DS”). Differential signaling operates by sending a signal on one wire and the opposite of that signal on a matching wire. The signal information is represented by the difference between the wires, rather than their absolute values relative to ground or other fixed reference.
Parallel data transfer is also commonly used to provide increased interconnection bandwidth, with busses growing from 16 or fewer wires, to 32, 64, and more. As crosstalk and noise induced on the parallel signal lines can produce receive errors, parity was added to improve error detection, and signal anomalies were addressed through active bus termination methods. However, these wide data transfer widths inevitably resulted in data skew, which became the limiting factor in increased bus data transfer throughput. Alternative approaches were developed utilizing narrower bus widths operating at much higher clock speeds, with significant effort placed on optimizing the transmission line characteristics of the interconnection medium, including use of impedance-controlled connectors and micro stripline wiring. Even so, the inevitable path imperfections required use of active equalization and inter-symbol interference (ISI) elimination techniques, including active pre-emphasis compensation for transmitters and Continuous Time Linear Equalization (CTLE) and Decision Feedback Equalization (DFE) for receivers, all of which increased the complexity and power consumption of the communications interface.
A number of signaling methods are known that maintain the desirable properties of DS, while increasing pin efficiency over DS. One such method is Vector signaling. With vector signaling, a plurality of signals on a plurality of wires is considered collectively although each of the plurality of signals might be independent. Thus, vector signaling codes can combine the robustness of single circuit DS and the high wire count data transfer throughput of parallel data transfer. Each of the collective signals in the transport medium carrying a vector signaling codeword is referred to as a component, and the number of plurality of wires is referred to as the “dimension” of the codeword (sometimes also called a “vector”). With binary vector signaling, each component or “symbol” of the vector takes on one of two possible values. With non-binary vector signaling, each symbol has a value that is a selection from a set of more than two possible values. The set of values that a symbol of the vector may take on is called the “alphabet” of the vector signaling code. A vector signaling code, as described herein, is a collection C of vectors of the same length N, called codewords. Any suitable subset of a vector signaling code denotes a “subcode” of that code. Such a subcode may itself be a vector signaling code. In operation, the coordinates of the codewords are bounded, and we choose to represent them by real numbers between −1 and 1. The ratio between the binary logarithm of the size of C and the length N is called the pin-efficiency of the vector signaling code. A vector signaling code is called “balanced” if for all its codewords the sum of the coordinates is always zero. Additional examples of vector signaling methods are described in Cronie I, Cronie II, Cronie III, Cronie IV, Fox I, Fox II, Fox III, Holden I, Shokrollahi I, Shokrollahi II, and Hormati I.
As previously described, broadband signaling methods partition the available information transfer medium in the frequency domain, creating two or more frequency-domain “channels” which may then may transport information in a comparable manner to baseband circuits, using known methods of carrier modulation to convert the baseband information into a frequency-domain channel signal. As each such channel can be independently controlled as to amplitude, modulation, and information encoding, it is possible to adapt the collection of channels to widely varying information transfer medium characteristics, including variations in signal loss, distortion, and noise over time and frequency.
Asymmetric Digital Subscriber Line or ADSL is one widely deployed broadband signaling method used to transport digital data over legacy copper telephony circuits. In ADSL, each of potentially several hundred frequency-domain channels is independently configured for amplitude, modulation method, and digital carrying capacity, based on the particular noise and loss characteristics of the copper circuit being used for transport.
Methods and systems are described for obtaining a set of carrier-modulated symbols of a carrier-modulated codeword, each carrier-modulated symbol received via a respective wire of a plurality of wires of a multi-wire bus, applying each carrier-modulated symbol of the set of carrier-modulated symbols to a corresponding transistor of a set of transistors, each transistor of the set of transistors connected to a respective output node of a pair of output nodes according to elements of a sub-channel vector, and controlling conductivity of the set of transistors according to a demodulation signal operating at a frequency recovered from the carrier-modulated symbols to responsively generate a demodulated sub-channel data output as a linear combination of the set of carrier-modulated symbols forming a differential voltage on the pair of output nodes.
Communication of digital information using a combination of baseband and broadband techniques over multiple wires is described. A four wire communications channel having 35 dB of attenuation at 37.5 GHz is used in provided examples as a typical transport medium for use with the systems and methods described herein. One embodiment creates two frequency-based channels over the transport medium, with each channel using a combination of a vector signaling code and duobinary encoding to transport sets of three data bits over four wires at an effective rate of 56 Gigabits per second per wire.
Interconnection has long been a limiting factor in the design of large digital systems. Whether at the level of modules interconnected by a backplane, or of functional subsystems interconnected within a large printed circuit board, the need for reliable, error free, high-speed digital interconnection has constantly pushed the limits of available technology to its limits.
The systems and methods described herein provide robust, reliable transfer of data between at least one transmitting device and at least one receiving device, at data rates of at least 50 Gigabits per second per interconnection wire. An example channel model having the frequency- and time-domain characteristics illustrated in
This proposed data rate also strains integrated circuit data processing capabilities within the attached transmitting and receiving devices. It is therefore presumed that high-speed data handling in these devices will be distributed across multiple parallel processing “phases”. As one example, rather than a single data path handling data at 100 Gigabits per second (i.e. with merely 10 picosecond between bits), the same data stream may be distributed across sixteen processing phases, each one thus having a more reasonable 160 picoseconds of processing time per bit. However, this added processing time comes at the cost of significantly increased complexity from the additional processing elements. This distribution of processing also can lead to increased latency before a given digital bit result becomes available, limiting the ability to utilize that result in predicting a subsequent bit result, which is the basis of the Decision Feedback Equalization or DFE method.
The increasing data transfer rates also lead to physical issues as the wavelength of the propagating signals on the interconnection shrinks. As one example, the propagating signal wavelength at 56 Gigahertz on a printed circuit micro stripline is approximately 4 millimeters, thus periodic anomalies with merely fractional wavelength dimensions (even including the weave of the impregnated fabric comprising the circuit board) may represent a significant disturbance to signal integrity, stressing available equalization and compensation methods.
Encoding Information Using Hadamard Transforms
As taught in [Cronie I], the Hadamard Transform, also known as the Walsh-Hadamard transform, is a square matrix of entries +1 and −1 so arranged that both all rows and all columns are mutually orthogonal. Hadamard matrices are known for all sizes 2N as well as for selected other sizes. In particular, the description herein utilizes the 4×4 Hadamard matrix as the example encoder.
The order 4 Hadamard matrix used in our examples is:
and encoding of the three informational bits A, B, C may be obtained by multiplying those informational bits times the rows 2, 3, and 4 of the Hadamard matrix H4 to obtain four output values, subsequently called “symbol values”. By convention, the results are scaled by an appropriate constant factor so as to bound the symbol values to the range +1 to −1. It may be noted that the first row of H4 corresponds to common mode signaling, which is not used herein, with the next three vectors being used to encode bits A, B, and C respectively into outputs W, X, Y, Z, these vectors also being called “modes” or “subchannels” of the Hadamard code. As the encoded outputs simultaneously carry information derived from the encoding of A, B, and C, the outputs will be a superposition or summation of modes, i.e. a sum of the sub-channel code vectors of the vector signaling code.
One familiar with the art will note that all possible values of A, B, C encoded in this manner result in mode summed values for W, X, Y, Z which are balanced; that is, summing to the constant value zero. If the mode summed values for W, X, Y, Z are scaled such that their maximum absolute value is 1 (that is, the signals are in the range +1 to −1 for convenience of description,) it will be noted that all achievable values are permutations of the vector (+1, −1/3, −1/3, −1/3) or of the vector (−1, 1/3, 1/3, 1/3). These are called the codewords of the vector signaling code H4. As used herein, this H4 code will subsequently be called Ensemble NRZ code or ENRZ and will be used as a representative example of vector signaling code in subsequent examples, without implying limitation.
ENRZ
[Hormati I] teaches that ENRZ has optimum Inter Symbol Interference (ISI) characteristics, and [Holden I] and [Ulrich I] teach it is capable of efficient detection. As previously described, ENRZ encodes three binary data bits into a four-symbol codeword for transmission, as one example, over four wires of a transport medium. If ENRZ signaling is used over four wires of the proposed channel, the data transfer rate may be achieved with merely a 75 Gigasymbol/second signaling rate, equivalent to 112 Gbps per wire pair, for the two pair transport channel.
Duobinary Encoding
Duobinary encoding is a solution known in the art in which consecutive bits of a serially transmitted data stream are processed to shape and constrain the resulting transmit data spectrum. It is well known that Inter-Symbol Interference (ISI) such as may be produced by transmission medium perturbations will result in the received amplitude of a signal in one unit interval to be perturbed by residual energy from previous unit intervals. As one example, inverted pulse reflections from a perturbation of the transmission medium will cause a received signal to be reduced by the residual influence of previously transmitted signals. Thus, a transmitter informed of this effect might combine a presently transmitted signal value with that of a previous transmission, in an attempt to anticipate or pre-compensate for this inter-symbol interference effect. Thus, use of partial response codes such as duobinary are often described as a particular form of pre-equalization filtering intended to produce constructive ISI, rather than as a literal data encoding means.
As described in [Beyene], other partial-response codes are known to have comparable ISI management capabilities. For reference purposes, the characteristic equations defining these encodings or filterings are listed in Table I.
Unless otherwise described, as used herein the duobinary processing performed is assumed to be a summation of the present and immediately previous transmit unit interval signal, each scaled by a factor of 0.5. Optionally, this may be combined with a transmit lowpass filter to further control the transmit spectrum. In other embodiments, ISI-controlling encoding is combined in any order with Hadamard encoding, where the ISI-controlling encoding is any of duobinary, modified duobinary, dicode, class2, or a Hamming filter as subsequently described. In such embodiments, the ISI-controlling encoding may also be described as being performed by a partial response encoder, embodying any of the partial response encodings or filterings above.
If the characteristics of the communications channel are extremely well understood, it may be possible to configure the ISI-controlling operation of the transmitter such that no explicit complementary operation is required at the receiver, the effective action of the channel characteristics themselves serving to perform the inverse operation. Other embodiments may explicitly detect, as one example, the ternary signals produced by duobinary encoding of binary data, followed by an explicit duobinary to binary decoding operation. Alternatively, commonly used receiver ISI elimination techniques such as DFE will also efficiently address the effects of such transmitter ISI compensation. As example receivers in this document incorporate DFE, no further receiver duobinary (or other partial response code) processing will be shown.
Channelization
Physical transport channel limitations have been seen and addressed before, albeit at far lower data rates, during the efforts to provide high speed digital services over the legacy copper wire infrastructure of the telephony network. For DSL at its desired 3 Megabit data rate, a propagating signal wavelength was several hundred meters, which correlated strongly with the typical spacing of wire stubs, splices, and insulation abrasions seen in the field. Thus, an uncompensated frequency response for a typical copper telephony signal path would exhibit numerous notches and slopes caused by reflective interference among those anomalies, dissipative attenuation from degraded wires and insulation, and intrusive noise from sources such as AM radio transmitters.
Ultimately, multichannel frequency domain channelization was used to constrain the effect of those legacy transport issues. One commonly deployed Asymmetric Digital Subscriber Line (ADSL) solution, for example, partitioned the approximate 1 MHz of available transport medium bandwidth into 4.3125 kHz channels. Each channel was then independently tested for attenuation and signal-to-noise ratio, with different data throughput rates assigned to each channel depending on those test results. Thus, a channel frequency coinciding with a frequency response notch or significant external noise source would not be used, while other channels not presenting those issues could be used at full capacity. Unfortunately, the generation and detection of such a high channel count protocol relies on the availability of inexpensive digital signal processing solutions, and such technology has scaled in performance over time by perhaps a factor of ten, versus the approximate factor of 100,000 data rate increase in the present application.
Thus, although the present channel attenuation issues suggest a broadband approach may be useful, the conventional high-channel-count embodiment methods known to the art are incompatible with the anticipated data rate. A new approach specifically designed for high speed processing will be described.
Broadband Duobinary ENRZ
[Hormati III] gives examples of several embodiments combining ENRZ signaling with an additional serial transmission encoding such as Duobinary, utilizing multiple frequency-domain channels. Those examples and teachings are incorporated by reference herein, in their entirety for all purposes.
As in [Hormati III], a carrier frequency of 37.5 GHz is assumed. Both baseband and carrier channels run at a signaling rate of 37.5 Gsymbols/second, with a first set of three data bits being transported over the four wires of the baseband channel, and a second set of three data bits being transported over the same four wires using the carrier channel.
Other embodiments are known in which the baseband signaling rate differs from the carrier signaling rate, and/or differ from the carrier frequency. Generally speaking, however, there are implementation advantages in keeping these relationships fixed, often being expressed as ratios of small integer values, as in the 1:1:1 example provided above. As one example of such advantage, a receiver embodiment may then maintain a single local oscillator clock derived from one such received signal, and then derive the other necessary receive clocks from it through known phase lock or delay lock methods.
Filters 110 and 115 separate the received signals into a broadband component including a set of carrier-modulated symbols of a carrier-modulated codeword and a baseband component including a set of baseband symbols of a baseband codeword. For descriptive simplicity,
As shown in
As with the baseband data path, the broadband data detection path incorporates MIC-demodulation circuits 120, samplers 127, and CDR 150 functions. However, as broadband encoded data is modulated onto a carrier, simple data detection cannot be performed without addressing the carrier signal as well.
As is well understood in the art, a signal modulated on a carrier may be mixed with a demodulations signal provided by e.g., a local oscillator, to return the carrier-modulated signals to baseband (a heterodyne receiver,) or data detection may be timed relative to not only data sampling rate, but also relative to the carrier rate (a synchronous detector.) In
Alternative embodiments may synchronize a receiver clock to the carrier and derive other sampling clocks from that derived reference source, may synchronize a receiver clock to a detected data stream and derive other sampling clocks from that derived reference source, or utilize a combination of said methods. Synchronization may utilize a local voltage controlled oscillator (VCO) or voltage controlled delay in a phase-locked or delay-locked loop generating a local clock signal. Alternatively, synchronization may rely upon utilizing a phase comparator result that configures a phase interpolator or adjustable delay to modify the phase of a local clock signal.
Synchronously-Switched Multi-Input Demodulating Comparator
Q=(w0+w2)−(w1+w3) (Eqn. 2)
As described in [Holden I], three instances of Eqn. 2 with different permutations of the input signals efficiently detect the three subchannel data outputs of the ENRZ code. Thus, the baseband detector 130 of
In the examples of
Operation of the half-wave and full-wave synchronous detectors is illustrated in the waveforms of
The illustrated Return-to-Zero (RTZ) waveform in
Separately, an independent PLL configuration generates a local clock signal aligned to the carrier frequency of the received carrier-demodulated data, and a sampling clock suitable for optimum sampling of carrier-demodulated data.
In an alternative embodiment, one or more of the necessary local clock signals may be derived from another clock signal.
In some embodiments, hybrid clock generation embodiments are also possible, including embodiments utilizing secondary or slave PLLs that produce a second local clock that is derived from a first local clock generated as described above. In such a system configuration, the secondary PLL may have different lock characteristics than the primary PLL, allowing independent optimization of characteristics such as lock time, free-running drift, jitter, etc.
In some embodiments, controlling the conductivity of the set of transistors includes selectably enabling a current source according to the demodulation signal CK_d, as shown in
In some embodiments, controlling the conductivity further includes alternately connecting each transistor of the set of transistors between the pair of output nodes according to the demodulation signal. In such embodiments, each transistor circuit is alternately connected between the pair of output nodes using a respective differential pair of transistors connected to the pair of output nodes according to the sub-channel vector. In some embodiments, the respective differential pair of transistors receives the demodulation signal and a complement of the demodulation signal and is composed of same-type transistors (e.g., NMOS or PMOS only), while alternative embodiments may include differential pairs of transistors that include an NMOS and a PMOS transistor both receiving the demodulation signal CK_d. Such a configuration is illustrated in
In some embodiments, the conductivity of each transistor of the set of transistors is further controlled by a symbol value of the applied carrier-modulated symbol. In such embodiments, the amount of current drawn through each transistor is proportional to the symbol value applied at each transistor. Signal amplitudes in one particular embodiment are:
500 mV center,
500+180=680 mV (+1)
500−60=440 mV (−1/3)
500−60=440 mV (−1/3)
500−60=440 mV (−1/3)
where a symbol of magnitude ‘1’ corresponds to a 180 mV deviation from the 500 mV center voltage and a symbol of magnitude ‘1/3’ corresponds to a 60 mV deviation from the 500 mV center voltage.
In some embodiments, the method further includes pre-charging the pair of output nodes in response to a sampling clock, and wherein the conductivity of the set of transistors is further controlled according to the sampling clock. Such embodiments are referred to above as “discrete” or “dynamic” MIC-demodulation circuits.
In some embodiments, the differential voltage on the pair of output nodes is formed by drawing currents through impedance elements connected to the pair of output nodes. In some embodiments, the impedance elements may be resistors connected between a power supply and the pair of output nodes to control a voltage drop across the resistors. The differential amount of current drawn through the resistors will form a differential voltage output on the pair of output nodes.
In some embodiments, the method further includes low-pass filtering the demodulated sub-channel data output.
In some embodiments, obtaining the set of carrier-modulated symbols includes high-pass filtering a superposition codeword comprising the set of carrier-modulated symbols of the carrier-modulated codeword and a set of baseband symbols of a baseband codeword.
In some embodiments, the sub-channel vector is part of a plurality of mutually orthogonal sub-channel vectors that compose rows of an orthogonal matrix. In some such embodiments, the orthogonal matrix is a Hadamard matrix.
In some embodiments, the demodulation signal has an equal rate as a sampling clock associated with a baud rate of the data streams. In alternative embodiments, the demodulation signal has a differing rate than the sampling clock. In some such embodiments, the demodulation signal may be an integer multiple of the sampling clock, and may initiate multiple discharge periods in a single unit interval. Alternatively, the demodulation signal may be a fraction of the sampling clock. In such embodiments, the sampling clock may initiate multiple pre-charge/discharge cycles in a half cycle of the demodulation signal. In some embodiments, the demodulation signal is generated by multiplying the sampling clock using a frequency multiplier. Alternatively, the demodulation signal may be generated by dividing the sampling clock using a frequency divider.
This application is a continuation of U.S. application Ser. No. 16/909,529, filed Jun. 23, 2020, now U.S. Pat. No. 11,063,799, naming Armin Tajalli, entitled “Synchronously-Switched Multi-Input Demodulating Comparator”, which is a continuation of U.S. application Ser. No. 16/236,012, filed Dec. 28, 2018, now U.S. Pat. No. 10,693,688, naming Armin Taj alli, entitled “Synchronously-Switched Multi-Input Demodulating Comparator”, which claims the benefit of U.S. Provisional Application No. 62/611,523, filed Dec. 28, 2017, naming Armin Tajalli, entitled “Combined Multi-Input Comparator and Demodulator”, all of which are hereby incorporated by reference in their entirety for all purposes. The following references are herein incorporated by reference in their entirety for all purposes: U.S. Patent Publication No. 2011/0268225 of U.S. patent application Ser. No. 12/784,414, filed May 20, 2010, now U.S. Pat. No. 9,288,089, granted Mar. 15, 2016, naming Harm Cronie and Amin Shokrollahi, entitled “Orthogonal Differential Vector Signaling”, hereinafter identified as [Cronie I]; U.S. patent application Ser. No. 13/030,027, filed Feb. 17, 2011, now U.S. Pat. No. 8,649,445, granted Feb. 11, 2014, naming Harm Cronie, Amin Shokrollahi and Armin Tajalli, entitled “Methods and Systems for Noise Resilient, Pin-Efficient and Low Power Communications with Sparse Signaling Codes”, hereinafter identified as [Cronie II]; U.S. patent application Ser. No. 14/158,452, filed Jan. 17, 2014, now U.S. Pat. No. 9,124,557, granted Sep. 1, 2015, naming John Fox, Brian Holden, Peter Hunt, John D Keay, Amin Shokrollahi, Richard Simpson, Anant Singh, Andrew Kevin John Stewart, and Giuseppe Surace, entitled “Chip-to-Chip Communication with Reduced SSO Noise”, hereinafter identified as [Fox I]; U.S. patent application Ser. No. 13/842,740, filed Mar. 15, 2013, now U.S. Pat. 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