Applying digital signal processing algorithms to an input analog signal requires an interface between the input analog signal and a digital signal processor. As an example of such an interface, an ADC apparatus, also known as an AD converter, may be used, whose tasks are to sample and quantize a continuous-time continuous-amplitude (i.e. analog) signal in order to create discrete-time discrete-valued (i.e. digital) inputs required by any digital signal processing algorithm. If input analog signals are bandlimited and sampled at the Nyquist rate or above and quantized with very high precision, then the effects of the AD converters are negligible, since digital signals reconstructed at the digital signal processor from the discrete-time digital inputs approximate the input analog signals with negligible distortion.
In some applications, very high-precision AD converters are however not cost and/or power-efficient or not even feasible using the existing technology. For example, this is the case when the ADC is applied to wideband multi-GHz analog signals. Indeed, the existing ADC technology working at very high sampling rates and high resolution is limited by a timing (or aperture) jitter, i.e. the failure to sample at precisely defined times. More specifically, electronic-based AD converters cannot achieve timing jitters smaller than one femtosecond and, hence, photonic-based AD converters are preferred to meet the strict timing jitter required by sampling frequencies in the order of tens of GHz. Furthermore, wideband AD converters with very high resolution are challenging even theoretically. Indeed, their accuracy is strictly below 8 bits, and this is not enough in some applications. For example, it cannot guarantee high-order modulations required in envisioned THz wireless communications to support very high throughputs. Therefore, new ADC strategies are being investigated.
One such ADC strategy has been recently proposed in the literature under the name of modulo-based ADC or modulo-ADC. The modulo-based ADC allows avoiding clipping errors caused by the conventional ADC but requires additional digital signal processing to reconstruct a digital estimate of the original analog signal from modulo-reduced discrete-time digital inputs resulting from the modulo-based ADC. This is not always possible to do and requires some conditions placed on the input analog signals to hold. In case an ADC is applied to a single input analog signal, the input analog signal needs to present some time correlation, or it needs to be generated by means of oversampling.
In general, the prior art solutions relating to the modulo-based ADC involve using corresponding digital reconstruction algorithms for specific ADC problems. However, the prior art solutions have not specified the actual modulo-based ADC implementation. There is therefore a need to provide an ADC apparatus configured to implement a modulo-based ADC and a corresponding method.
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure.
It is an objective of the present disclosure to provide a technical solution that allows modulo-based ADC to be performed on analog signals.
One or more of the objectives above is achieved by the features of the independent claims in the appended claims. Further embodiments and examples are apparent from the dependent claims, the detailed description and the accompanying drawings.
According to a first aspect, an ADC apparatus is provided, which comprises a signal-to-phase conversion unit, an ADC unit, and a digital signal processing (DSP) unit. The signal-to-phase conversion unit is configured to convert an input analog signal into phases of M periodic reference signals based on at least one transfer function, wherein M≥2. The phase of each of the M periodic reference signals comprises a folded signal. The folded signal corresponds to the input analog signal that is amplitude-folded to fall within an amplitude range. Given this, the signal-to-phase conversion corresponds to the outcome of a modulo operation. The ADC unit is configured to obtain M discrete-time digital signals by performing an ADC operation on the M periodic reference signals within the amplitude range. The DSP unit is configured to obtain, based on the M discrete-time digital signals, a digital representation of the input analog signal. By so doing, it is possible to perform the modulo-based ADC on the input analog signal. Furthermore, such a configuration of the ADC apparatus may provide the high-resolution quantization of the input analog signal at a very high sampling rate and very high signal bandwidths. Given this, the accuracy of obtaining the digital representation of the input analog signal may be increased.
In one embodiment of the first aspect, the phases of at least two of the M periodic reference signals have a difference other than 0 or π. By using at least one pair of periodic reference signals with such a phase difference, it is possible to cope with the problem of phase sign ambiguity which occurs, for example, when the pair of periodic reference signals are represented by two sine functions such that sin(x(t))=sin(π−x(t)), where x(t) is the input analog signal.
In one embodiment of the first aspect, the input analog signal changes in a predefined dynamic range, and each of the at least one transfer functions is a bijective function in the predefined dynamic range of the input analog signal. By using the bijective function, it is possible to provide a proper relationship between the phases of the reference signals and the input analog signal, thereby increasing the accuracy of obtaining the digital representation of the input analog signal.
In one embodiment of the first aspect, the at least one transfer function comprises a first transfer function and a second transfer function, and, in the predefined dynamic range of the input analog signal, the first transfer function and the second transfer function are a same bijective function. In this embodiment, the first transfer function has a first constant phase shift and the second transfer function has a second constant shift. The first constant phase shift of the first transfer function and the second constant phase shift of the second transfer function have a difference other than 0 or π. By using such phase shifts for the same bijective function, it is possible to cope with the above-mentioned problem of phase sign ambiguity arising, for example, from sin(x(t))=sin(π−x(t)).
In one embodiment of the first aspect, each of the at least one transfer function is an affine function. By using the affine functions, it is possible to provide a proper relationship between the phases of the reference signals and the input analog signal, thereby increasing the accuracy of obtaining the digital representation of the input analog signal. Furthermore, the possibility of choosing among the affine functions and the bijective functions makes the ADC apparatus according to the first aspect more flexible in use.
In one embodiment of the first aspect, the ADC unit comprises M synchronized ADC subunits each configured to perform the ADC operation on one of the M periodic reference signals. By so doing, it is possible to perform the ADC operation on the M periodic reference signals in parallel, thereby increasing the accuracy of obtaining the digital representation of the input analog signal.
In one embodiment of the first aspect, at least one of the M ADC subunits has a different bit resolution or different quantization level (i.e., different quantization function) compared to the other synchronized ADC subunits of the M synchronized ADC subunits. This may allow one to differently quantize the M periodic reference signals, if required and depending on particular applications, thereby making the ADC apparatus according to the first aspect more flexible in use.
In one embodiment of the first aspect, the DSP unit is configured to obtain the digital representation of the input analog signal by:
By so doing, it is possible to obtain the digital representation of the input analog signal by using only two discrete-time digital signals or, in other words, only two periodic reference signals.
In one embodiment of the first aspect, the signal-to-phase conversion unit comprises an optical source and M phase-biased electro-optic modulators. The optical source is configured to generate a pulse train that serves as the M periodic reference signals. Each of the M phase-biased electro-optic modulators has an electro-optical response as one of the at least one transfer function and is configured to receive the input analog signal and modulate the pulse train with the input analog signal, thereby converting the input analog signal into the phases of the M periodic reference signals. By so doing, it is possible to implement the modulo-based ADC with photonic sampling.
In one embodiment of the first aspect, the optical source comprises a mode-locked laser. The mode-locked laser may generate an ultra-stable pulse train that may be used to optically sample the input analog signal, while addressing the problem of a timing jitter.
In one embodiment of the first aspect, each of the M phase-biased electro-optic modulators comprises a Mach-Zehnder modulator (MZM). This type of electro-optic modulator is preferred due to its low optical relative loss, high optical power processing capability, and wide optical bandwidth.
In one embodiment of the first aspect, at least two of the M MZMs have a modulation index that is more than 1. If the transfer function is represented by a sine/cosine function, the MZMs with such a modulation index may fully use the sine/cosine transfer function and not only its linear part (as would be the case for the MZMs with the modulation index less than 1).
In one embodiment of the first aspect, the at least two MZMs have a same bijective transfer function supplemented by different constant phase shifts which are obtained by applying different DC bias voltages to the at least two MZMs. By using different DC bias voltages in this embodiment, it is possible to ensure that the phase difference between the corresponding periodic reference signals is other than 0 or π.
In one embodiment of the first aspect, the DSP unit is configured to obtain the digital representation of the input analog signal by applying a machine-learning algorithm. The machine-learning algorithm may speed-up the operation of obtaining the digital representation of the input analog signal.
According to a second aspect, an ADC method is provided. The ADC method starts with the step of converting an input analog signal into phases of M periodic reference signals based on at least one transfer function, wherein M≥2. The phase of each of the M periodic reference signals comprises a folded signal. The folded signal corresponds to the input analog signal that is amplitude-folded to fall within an amplitude range. Given this, the signal-to-phase conversion corresponds to the outcome of the modulo operation. The method further proceeds to the step of obtaining M discrete-time digital signals by performing an ADC operation on the M periodic reference signals within the amplitude range. After that, the method goes on to the step of using the M discrete-time digital signals to obtain a digital representation of the input analog signal. By so doing, it is possible to perform the modulo-based ADC on the input analog signal. Furthermore, the method according to the second aspect may provide the high-resolution quantization of the input analog signal at a very high sampling rate and very high signal bandwidths. Given this, the accuracy of obtaining the digital representation of the input analog signal may be increased.
In one embodiment of the second aspect, the phase of at least two of the M periodic reference signals have a difference other than 0 or π. By using at least one pair of periodic reference signals with such a phase difference, it is possible to cope with the problem of phase sign ambiguity which occurs, for example, when the pair of periodic reference signals are represented by two sine functions such that sin(x(t))=sin(π−x(t)), where x(t) is the input analog signal.
In one embodiment of the second aspect, the input analog signal changes in a predefined dynamic range, and each of the at least one transfer functions is a bijective function in the predefined dynamic range of the input analog signal. By using the bijective function, it is possible to provide a proper relationship between the phases of the reference signals and the input analog signal, thereby increasing the accuracy of obtaining the digital representation of the input analog signal.
In one embodiment of the second aspect, the at least one transfer function comprises a first transfer function and a second transfer function, and, in the predefined dynamic range of the input analog signal, the first transfer function and the second transfer function are a same bijective function. In this embodiment, the first transfer function has a first constant phase shift and the second transfer function has a second constant phase shift. The first constant phase shift of the first transfer function and the second constant phase shift of the second transfer function have a difference other than 0 or π. By using such phase shifts for the same bijective function, it is possible to cope with the above-mentioned problem of phase sign ambiguity arising, for example, from sin(x(t))=sin(π−x(t)).
In one embodiment of the second aspect, each of the at least one transfer functions is an affine function. By using the affine functions, it is possible to provide a proper relationship between the phases of the reference signals and the input analog signal, thereby increasing the accuracy of obtaining the digital representation of the input analog signal. Furthermore, the possibility of choosing among the affine functions and the bijective functions makes the method according to the second aspect more flexible in use.
In one embodiment of the second aspect, the digital representation of the input analog signal is obtained by:
By so doing, it is possible to obtain the digital representation of the input analog signal by using only two discrete-time digital signals or, in other words, only two periodic reference signals.
In one embodiment of the second aspect, the digital representation of the input analog signal is obtained by applying a machine-learning algorithm. The machine-learning algorithm may allow one to reduce the time required to obtain the digital representation of the input analog signal.
According to a third aspect, a computer program product is provided. The computer program product comprises a computer-readable storage medium storing a computer code which, when executed by at least one processor, causes the at least one processor to perform the method according to the second aspect. By using such a computer program product, it is possible to simplify the implementation of the method according to the second aspect in any ADC apparatus, like the ADC apparatus according to the first aspect.
According to a fourth aspect, a signal processing apparatus is provided. The signal processing apparatus comprises a receiving unit and the ADC apparatus according to the first aspect. The receiving unit is configured to receive the input analog signal and provide the input analog signal to the ADC apparatus according to the first aspect for its processing in the above-described manner. By using such an ADC apparatus in the signal processing apparatus according to the fourth aspect, it is possible to perform the modulo-based ADC on the input analog signal at a very high sampling rate and very high signal bandwidths. This, in turn, makes it possible to use the signal processing apparatus according to the fourth aspect, for example, in THz wireless communications.
Other features and advantages of the present disclosure will be apparent upon reading the following detailed description and reviewing the accompanying drawings.
The present disclosure is explained below with reference to the accompanying drawings, in which:
Various embodiments of the present disclosure are further described in more detail with reference to the accompanying drawings. However, the present disclosure may be embodied in many other forms and should not be construed as limited to any certain structure or function discussed in the following description. In contrast, these embodiments are provided to make the description of the present disclosure detailed and complete.
According to the detailed description, it will be apparent to the ones skilled in the art that the scope of the present disclosure encompasses any embodiment thereof, which is disclosed herein, irrespective of whether this embodiment is implemented independently or in concert with any other embodiment of the present disclosure. For example, the apparatuses and method disclosed herein may be implemented in practice by using any number of the embodiments provided herein. Furthermore, it should be understood that any embodiment of the present disclosure may be implemented using one or more of the features presented in the appended claims.
The word “exemplary” is used herein in the meaning of “used as an illustration”. Unless otherwise stated, any embodiment described herein as “exemplary” should not be construed as preferable or having an advantage over other embodiments.
Although the numeric terminology, such as “first”, “second”, etc., may be used herein to describe various embodiments, it should be understood that these embodiments should not be limited by this numeric terminology. This numeric terminology is used herein only to distinguish one embodiment from another embodiment. Thus, a first embodiment discussed below could be called a second embodiment, without departing from the teachings of the invention.
As used in the embodiments disclosed herein, an ADC apparatus or, in other words, AD converter may refer to a device configured to convert an analog signal into its digital representation by means of a modulo-based ADC. The basic idea behind the modulo-based ADC is to apply a modulo operation to the analog signal before its quantization such that a resulting folded signal perfectly matches a quantizer input range. It should be noted that the analog signal may be represented by any one of an RF signal received by a receiver, an acoustic signal picked up by a microphone, a light signal entering a digital camera, etc. Generally speaking, the analog signal to be digitally processed in the embodiments disclosed herein may be any wireless or wired signal. Furthermore, the ADC apparatus may be integrated into any signal processing apparatus which may be implemented, for example, as a part of a communication apparatus (e.g., a user equipment (UE) or network node), a radar, a sensing apparatus (e.g., a measurement bridge or voltmeter), etc.
The UE may refer to a mobile device, a mobile station, a terminal, a subscriber unit, a mobile phone, a cellular phone, a smart phone, a cordless phone, a personal digital assistant (PDA), a wireless communication device, a desktop computer, a laptop computer, a tablet computer, a gaming device, a netbook, a smartbook, an ultrabook, a medical device or medical equipment, a biometric sensor, a wearable device (for example, a smart watch, smart glasses, a smart wrist band, etc.), an entertainment device (for example, an audio player, a video player, etc.), a vehicular component or sensor, a smart meter/sensor, an unmanned vehicle (e.g., an industrial robot, a quadcopter, etc.), industrial manufacturing equipment, a global positioning system (GPS) device, an Internet-of-Things (IoT) device, an Industrial IoT (IIoT) device, a machine-type communication (MTC) device, a group of Massive IoT (MIoT) or Massive MTC (mMTC) devices/sensors, or any other suitable device configured to support wireless communications. In some embodiments, the UE may refer to at least two collocated and inter-connected UEs thus defined.
The network node may relate to a fixed point of communication for the UE in a particular wireless communication network. The network node may be implemented as a Radio Access Network (RAN) node referred to as a base transceiver station (BTS) in terms of the 2G communication technology, a NodeB in terms of the 3G communication technology, an evolved NodeB (eNodeB) in terms of the 4G communication technology, and a gNB in terms of the 5G New Radio (NR) communication technology. The RAN node may serve different cells, such as a macrocell, a microcell, a picocell, a femtocell, and/or other types of cells. The macrocell may cover a relatively large geographic area (for example, at least several kilometers in radius). The microcell may cover a geographic area less than two kilometers in radius, for example. The picocell may cover a relatively small geographic area, such, for example, offices, shopping malls, train stations, stock exchanges, etc. The femtocell may cover an even smaller geographic area (for example, a home). Correspondingly, the RAN node serving the macrocell may be referred to as a macro node, the RAN node serving the microcell may be referred to as a micro node, and so on.
Turning back to the modulo-based ADC, how the modulo-based ADC may be implemented from an ideal point of view will now be described. The present disclosure provides a modulo-based ADC implementation which behaves as close as possible to the ideal modulo-based ADC, as will be explained further.
An ideal response of a modulo-based ADC apparatus with a sample frequency fs=1/Ts, an input range [−λ/2, λ/2], and a resolution of b bits may be described as follows. Let x(t) be an input analog signal (bandlimited with a bandwidth BW≤fs/2), then the ideal modulo-based ADC may be mathematically expressed as:
y[]=Qb(modλ(x(Ts))),
where
modλ(·) is the modulo-λ operation that folds the input analog signal whenever its amplitude is higher than λ/2 or lower than −λ/2. Mathematically, it is defined as the following transfer function:
modλ(x)=x−λ(1+[x/λ−1/2]),
where [·] denotes the floor function.
and reconstruction levels μ0, μ1, μ2, . . . , μ2
where (·) denotes the indicator function.
The above-given mathematical expression of the ideal modulo-based ADC, i.e. y[], does not impose any particular order between performing the sampling and modulo operations. In fact, these operations may be even simultaneously performed. The quantization function Qb(·) remains general and, hence, includes, for example, non-uniform quantizers.
As an example, for a uniform quantizer with the resolution of b bits, the input range [−λ/2, λ/2], and a quantization step-size μ=2−bλ, the quantization function Qb(·) is given by
Any practical implementation of the modulo-based ADC cannot support an infinite number of folds, as implied by the above-given definition of the modulo operation, i.e. modλ(x). Otherwise, this would require supporting an infinite dynamic range of the input analog signal x(t), which is physically impossible. In fact, there is even no need to support the infinite number of folds, and, in practice, it is enough to guarantee the maximum number of folds [max ∥x(t)∥/λ] for the optimum λ, i.e. the minimum possible λ guaranteeing the recovery of the input analog signal from discrete-time folded samples outputted by the modulo-based ADC apparatus. Consequently, the number of folds to be supported depends on the application: typically less than 10 in general-purpose AD converters or several order of magnitudes higher in the context of a full duplex transceiver.
It should be also noted that there are no commercially available devices implementing the modulo-based ADC concept as such, and only “ad-hoc” solutions or proof-of-concept designs have been proposed in the past.
For example, one approach consists in using commercially available folding AD converters or self-reset AD converters. These AD converters follow the so-called bit-per-stage architecture. There are as many stages as a bit resolution b, each of which has a “bit” output and a “residue” output. The residue output of one stage is an input to the next stage and the last bit is detected with a single comparator. It turns out that the b bits outputted by a folding AD converter may be interpreted as follows: the m most significant bits are used to count the number of folds and the remaining b−m least significant bits give a quantization index of a residual signal after folding. Hence, by using the folding AD converter with the resolution of b bits, one may implement the modulo-based ADC with the resolution of b−m bits, which allows the analog signal being folded 2m−1 times by discarding the m most significant bits outputted by the folding AD converter. An alternative design for the self-reset AD converters includes special circuits configured to compute the modulo operation and count the number of folds followed by a quantization module of a successive approximation AD converter. The main problem with the folding AD converters or self-reset AD converters is that they are not cost or power-efficient, since, for example, the hardware used to count the number of folds is not necessary under the paradigm of the modulo-based ADC. Even more importantly, the number of times that the analog signal may be folded is small and intrinsically limited by the design of such AD converters. This prevents them from being used, for example, in full-duplex applications.
A different approach for implementing the modulo-based ADC implies that the modulo operation relies on a circular chain of inverter circuits, where the output of each inverter in the chain is connected to the input of the next inverter in the chain. The inversion for all inverters is then controlled by the same input signal. Such a circuit is called a ring oscillator. When wired this way, the frequency of oscillation in the ring oscillator will be a function of the input signal and it will generate a frequency modulated signal. Such a circuit has been long used for generating such frequency modulated signals, for example, for frequency modulated radio diffusion, but it may be repurposed as a modulo operator. The response of ring oscillators used as the modulo operation tends to have an uneven resolution, and the AD converters based on it also appear to perform relatively worse for high bitrates.
Besides the architectural limitations of the previous approaches, they also inherit the intrinsic limitation of electronic ADC technologies when converting high-speed RF signals, namely the so-called timing jitter (also referred to as aperture ambiguity or aperture jitter) and comparator ambiguity. The timing jitter is a random variation in the position of a temporal sampling interval. The result is that the sampling interval is not constant, but varies randomly, leading to accuracy degradation. The comparator ambiguity, a major limiting factor at high signal frequencies, comes from a finite speed with which an ADC comparator responds to small variations in an input analog signal to produce a correct quantization decision relative to a comparator reference.
The exemplary embodiments disclosed herein provide a technical solution that allows mitigating or even eliminating the above-mentioned drawbacks of the prior art. In particular, the technical solution disclosed herein relies on the fact that a phase of an input analog signal is naturally measured modulo 27λ. Given this, it is possible to convert the input analog signal into phases of other M periodic analog signals (hereinafter referred to as reference signals), where M≥2. The phase of each of the M periodic reference signals comprises a folded signal corresponding to the input analog signal that is amplitude-folded to fall within a required amplitude range. Thus, this signal-to-phase conversion allows the modulo operation to be implemented over the input analog signal. Further, the M periodic reference signals are used to obtain M discrete-time digital signals which, in turn, are used to obtain a digital representation of the input analog signal. By so doing, it is possible to perform the modulo-based ADC on the input analog signal.
Each of the ADC subunits 304-1, 304-2, . . . , 304-M may be implemented as integrated circuits (ICs). These ICs may be implemented based on any suitable semiconductor technology, such, for example, as Complementary Metal-Oxide-Semiconductor (CMOS), Bipolar CMOS technology, etc. As a certain example, these ICs may take the form of mixed-signal IC chips that integrate both analog and digital circuits.
The DSP unit 306 may be implemented as a CPU, general-purpose processor, single-purpose processor, microcontroller, microprocessor, application specific integrated circuit (ASIC), field programmable gate array (FPGA), digital signal processor, complex programmable logic device, etc. In some embodiments, the DSP unit 306 may be implemented as any combination of the aforesaid, e.g., as two or more microprocessors.
As for the signal-to-phase unit 302, it may be implemented by using electro-optic modulators or ring oscillators. In a preferred embodiment, the signal-to-phase unit 302 comprises the combination of an optical source (e.g., a mode-locked laser) and Mach-Zehnder modulators (MZMs).
As can be seen from
However, the phase structures shown in
In one embodiment, the DSP unit 306 may perform the step S406 of the method 400 as follows. At first, the DSP unit 306 determines a phase of at least one of the M discrete-time digital signals obtained by the ADC subunits 304-1, 304-2, . . . , 304-M in the step S404 of the method 400. Then, the DSP unit 306 inverts one of the transfer functions ϕ1(x(t)), . . . ϕM(x(t)) based on the determined phase, while using at least one other of the M discrete-time digital signals to solve the problem of phase sign ambiguity. After that, the DSP unit 306 obtains the digital representation y[] of the input analog signal x(t) based on the inverted transfer function. By so doing, it is possible to use only two periodic reference signals when performing the modulo-based ADC on the input analog signal x(t).
In another embodiment, the DSP unit 306 may use, in the step 406 of the method 400, a suitable machine learning algorithm to properly process the M discrete-time digital signals outputted by the ADC subunits 304-1, 304-2, . . . , 304-M. This may improve the accuracy of the step S406 of the method 400.
The following is one non-restrictive example of how to implement the modulo operation by using the step S402 of the method 400. First, assume that the input analog signal x(t) is converted in the step S402 of the method 400 into the phase of a periodic reference signal y(t), for example, as follows:
y(t)=A sin(ϕ)(x(t))+ψ),
where A is the amplitude, ψ is the initial constant phase shift, and ϕ(·) denotes the phase transfer function, which is assumed to be any bijective function such that its inverse function ϕ−1(·) exists and satisfies
ϕ(x(t)+k·λ)=ϕ(x(t))+k·2π, k=±1, ±2, . . . .
This operation effectively folds the analog input signal x(t), since it holds
y(t)=A sin(ϕ(x(t))+ψ)=A sin(ϕ(modλ(x(t)))+ψ).
However, the function relating y(t) with ϕ(x(t)) is not linear and not even invertible in one 2π period, i.e. when ϕ(x(t)) ∈ [−π, π), due to the phase ambiguity arising from sin(x)=sin(π−x). In order to have enough information to recover modλ(x(t)) from y(t), the analog input signal x(t) is converted into the phases of at least two periodic reference signals. Consider the general case of the signal-to-phase converter 302 with the following M outputs:
y
i(t)=Ai sin(ϕ(x(t))+ψi), i=1,2, . . . , M.
Then, the only requirement for uniquely obtaining modλ(x(t)) from y(t) is that there exists at least one pair of periodic reference signals yi(t) and yj(t) whose corresponding phase shifts ψi and ψj are neither equal nor separated by π modulo 2π:
∥ψi−mod2π(ψ)∥≠0 and ∥ψi−mod2π(ψ)∥≠π.
In this case, the following is computed:
ϕA,i=mod2π(arcsin(yi(t)/Ai)−ψi), i=1,2, . . . , M
ϕB,j=mod2π(π−arcsin(yj(t)/Aj)−ψj), j=1,2, . . . , M
A further step comprises uniquely recovering ϕ(x(t)) ∈ ]−π, π) as
ϕ(x(t))=ϕA,i if ϕA,1=ϕA,2= . . . =ϕA,M, (i)
ϕ(x(t))=ϕB,i if ϕB,1=ϕA,2= . . . =ϕB,M, or ϕ(x(t))=ϕA,i, if for any j such that (ii)
ϕA,i≠ϕA,j, it holds that ϕA,i=ϕB,j.
Finally, it is possible to invert the phase transfer function and obtain the modulo operation as follows:
modλ(x(t))=ϕ−1(ϕ(x(t)))
Given the above-given example, the whole modulo-based ADC implemented by using the method 400 may be described as follows:
ŷi[]=Qb
According to the present disclosure, ϕ(x(t)) ∈ [−π, π) it) is recovered in the digital domain, after the M periodic reference signals outputted by the signal-to-phase conversion unit 302 have been converted to the M discrete-time digital signals using the ADC units 304-1, 304-2, . . . , 304-M.
and with only two outputs providing a phase difference of 7r/2, namely:
Then, upon performing, by the ADC subunits 504-1, 504-2, the ADC with quantization functions Qb
At this point, there are different options to solve the problem of phase sign ambiguity and invert the transfer function of the phase-to-signal conversion unit 502, which basically depend on the quantization function applied by both the ADC subunits 504-1, 504-2.
For example, let us assume that the ADC subunit 504-1 is a high-resolution ADC subunit, while the ADC subunit 504-2 is a 1-bit ADC subunit. In case of converting y1(t) using the high-resolution ADC subunit 504-1, one may assume that
Then, converting y2(t) using the 1-bit ADC subunit 504-2 is as follows:
Given this, the modulo-based ADC output, i.e. the output of the DSP unit 506, may be simply written as follows:
One problem associated with the above-given exemplary implementation is that equivalent quantization errors become higher as the phase shift ϕ(x(t)) approaches π/2, since sin(ϕ(x(Ts))) is far from linear. This problem may be alleviated by carefully designing the quantization thresholds and reconstruction levels associated with the high-resolution ADC subunit 504-1.
More specifically,
A different option, which also alleviates the above-mentioned problem of the quantization errors (becoming higher as the phase shift ϕ(x(t)) approaches π/2) comes from using two identical ADC subunits 504-1, 504-2 with the same quantization function Qb(·) for converting both the outputs of the signal-to-phase conversion unit 502, i.e. the periodic reference signals y1(t) and y2(t). In this case, the digital representation may be obtained as follows:
Thus, the DSP unit 506 (as well as the DSP unit 306) may select different DSP algorithms depending on the transfer function used in the signal-to-phase conversion unit and the quantization functions used in the ADC subunits to convert the periodic reference signals to the digital signals.
More specifically, the signal-to-phase conversion unit 802 is configured as the combination of an optical source 810, two identical MZMs (A and B) 812, 814, and a bias control unit 816. The optical source 810 may be implemented as a mode-locked laser configured to generate an ultra-stable pulse train serving as the M periodic reference signals. The ultra-stable pulse train avoids the problem of the timing jitter. The MZMs 812, 814 driven by the optical source 810 are configured to receive the input analog signal x(t) and modulate the pulse train with the input analog signal x(t) such that the input analog signal x(t) is related to the phases of the M periodic reference signals via the transfer function, as discussed earlier. The MZMs 812, 814 may be further configured to receive corresponding DC bias voltages VDC,A and VDC,B from the bias control unit 816. The DC bias voltages VDC,A and VDC,B are controlled such that the difference between the associated phases ϕDC(VDC,A) and ϕDC(VDC,B) is equal to a desired value, such as π/2. It should be noted that the present disclosure is not limited to the application of the MZMs, and any other suitable electro-optic modulators may be used in the signal-to-phase conversion unit 802 for the same purpose. At the same time, it is preferable to use the MZMs due to their low optical relative loss, high optical power processing capability, and wide optical bandwidth. It is also worth noting that the number, arrangement and interconnection of the constructive elements constituting the ADC apparatus 800, which are shown in
As mentioned above, the ADC unit 804 comprises the two groups of ADC subunits schematically denoted in
In one preferred embodiment, each of the MZMs 812, 814 has a modulation index mRF»1. This is in contradiction with the conventional application of MZMs for ADC, which requires the modulation index mRF«1. To explain such a selection of the modulation index for the MZMs 812, 814, the electro-optical response of a conventional MZM with a single output working in push-pull mode is described mathematically. Let P0 be the light power at the MZM input, x(t) be the input RF analog signal, and VDC be the DC bias voltage, then the photocurrent at the MZM output may be accurately modeled as follows:
where α is the optical loss in the MZM, β is the contrast ratio, ϕ is the intrinsic phase caused by the length difference in the MZM arms, and ϕRF(x(t)), ϕRF(VDC) are the phase shifts caused by the RF analog signal x(t) and the VDC bias voltage, respectively, which are given by
where VRF,π is the half-wave voltage at RF and VDC,π is the half-wave voltage at DC.
Since it is desirable to obtain a highly linear response to the RF analog signal x(t) in case of ADC using conventional MZMs, the MZM parameters may be configured such that the electro-optical response of each of the conventional MZMs behaves as
Thus, if the modulation index
the linear region of a sine function is used, as shown in
As opposed to the conventional MZM, the MZMs 812, 814 are configured such that they may operate in a regime where
∥X(t)∥»>VRF,π,
because, in the case of the modulo-based ADC, the RF analog signal x(t) should expand as many 2π periods of the MZM transfer function as desired, so that the signal x(t) is effectively folded in the step S402 of the method 400. In fact, in this case, the MZM modulation index,
directly determines the maximum number of folds supported by the modulo-based ADC implementation in accordance with the method 400. In consequence, as opposed to the conventional MZM, mRF»1, which allows one to fully use the sine/cosine transfer function of the MZM and not only its linear part.
To solve the problem of phase sign ambiguity arising, for example, from sin(x)=sin(π−x), the MZMs 812, 814 should operate in parallel, for example, with the phase difference of π/2, namely:
Therefore, the ADC apparatus 800 comprises the two identical MZMs (A and B) 812, 814 with VRF,π=λ driven by the same optical source 810 and with the RF analog signal x(t) and the corresponding bias voltages VDC,A and VDC,B controlled such that the difference between the associated phases ϕDC(VDC,A) and ϕDC(VDC,B) is π/2.
The later steps S404 and S406 of the method 400 may be performed in the ADC apparatus 800 as follows. The digital representation y [] may be obtained from the outputs of the two groups of ADC subunits:
when the ADC subunits of the group called “Electronic ADC A” have a quantization function Qb(·) with a resolution of bA=b bits and the ADC subunits of the group called “Electronic ADC B” are 1-bit ADC subunits, or as
when both the groups “Electronic ADC A” and “Electronic ADC B” have a quantization function Qb(·) with a resolution of b=bA=bB bits.
It should be noted that each step or operation of the method 400, or any combinations of the steps or operations, can be implemented by various means, such as hardware, firmware, and/or software. As an example, one or more of the steps or operations described above can be embodied by processor executable instructions, data structures, program modules, and other suitable data representations. Furthermore, the executable instructions which embody the steps or operations described above can be stored on a corresponding data carrier and executed by at least one processor. This data carrier can be implemented as any computer-readable storage medium configured to be readable by said at least one processor to execute the processor executable instructions. Such computer-readable storage media can include both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, the computer-readable media comprise media implemented in any method or technology suitable for storing information. In more detail, the practical examples of the computer-readable media include, but are not limited to information-delivery media, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile discs (DVD), holographic media or other optical disc storage, magnetic tape, magnetic cassettes, magnetic disk storage, and other magnetic storage devices.
Although the exemplary embodiments of the present disclosure are described herein, it should be noted that any various changes and modifications could be made in the embodiments of the present disclosure, without departing from the scope of legal protection which is defined by the appended claims. In the appended claims, the word “comprising” does not exclude other elements or operations, and the indefinite article “a” or “an” does not exclude a plurality. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be advantageously used.
This application is a continuation of International Application No. PCT/CN2021/093101, filed on May 11, 2021, the disclosure of which is hereby incorporated by reference in its entirety.
Number | Date | Country | |
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Parent | PCT/CN2021/093101 | May 2021 | US |
Child | 18506447 | US |