# Patent

## Title
Transmitter signal shaping

## Abstract

A system that includes combiner circuitry configured to combine a first signal and a second signal to generate a third signal, wherein said third signal is output for transmission onto a communication medium. The system also includes nonlinearity modeling circuitry configured to model a nonlinear response of a nonlinear circuit, and generate a fourth signal through nonlinear distortion of a fifth signal using said model. The system also includes bin modification circuitry configured to generate said second signal through application of one or more weighting factors to frequency bins of said fourth signal, or of a transformed version of said fourth signal, and determine said weighting factors based on a difference, or squared difference, error metric.

## Background
PRIORITY CLAIM
This application is a continuation of U.S. application Ser. No. 14/687,861 filed Apr. 15, 2015 (now U.S. Pat. No. 9,246,523) which claims priority to U.S. provisional patent application 62/042,356 filed on Aug. 27, 2014, and U.S. provisional patent application 62/126,881 filed on Mar. 2, 2015. Each of the above mentioned documents is hereby incorporated herein by reference in its entirety.


BACKGROUND
Limitations and disadvantages of conventional and traditional approaches to electronic communications will become apparent to one of skill in the art, through comparison of such systems with some aspects of the present invention as set forth in the remainder of the present application with reference to the drawings.
BRIEF SUMMARY
Systems and methods are provided for transmitter signal shaping, substantially as shown in and/or described in connection with at least one of the figures, as set forth more completely in the claims.
These and other advantages, aspects and novel features of the present invention, as well as details of an illustrated embodiment thereof, will be more fully understood from the following description and drawings.



BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS
FIG. 1 is a diagram illustrating an example transmitter with TX nonlinear shaping circuit.
FIG. 2 is a diagram illustrating additional details of an example transmitter with Tx nonlinear shaping circuit.
FIGS. 3A-3D depict example transmitters which uses a PA PSD shaper circuitry with or without other aspects of the TX nonlinear shaping circuitry of FIG. 1.
FIG. 4 illustrates an example response of digital nonlinear function circuit.
FIG. 5 is a diagram illustrating control of the PA PSD Shaper in accordance with an example implementation of this disclosure.
FIG. 6A illustrates an alternate implementation of the transmitter of FIG. 3A.
FIG. 6B illustrates an alternate implementation of the transmitter of FIG. 3B.



DETAILED DESCRIPTION
Conventional receivers can manage relatively low amounts of nonlinear distortion of their input communication signal. In contrast, receivers in accordance with various implementations of this disclosure may be capable of handling deep communication signal distortion by measuring and modeling the nonlinear response. This capability allows communication systems to handle deep Power Amplifier (PA) nonlinearity. This capability can also be used to handle intentional distortion digitally applied by the transmitter in order to improve various signal characteristics. Circuitry for introducing such digital distortion is referred to herein as a TX nonlinear shaper. In various implementations, the TX nonlinear shaper can achieve one or more the following goals:

    
    
        Reduce signal peak to average power ratio, which has many uses. One use applicable to working with deep PA distortion and unraveling it at the receiver using PA model is preventing the signal from getting too close to the power rails. An advantage of this is that PA modeling near the power rails may be difficult (e.g., costly in terms of time, memory, processing power, etc.).
        Reduce signal cubic metric (a metric defined by 3GPP) in order to reduce transmitted signal out-of-band distortion (i.e. to reduce occurrence of exceeding allowed out-of-band spectral emission mask or Adjacent Channel Leakage Ratio), while working relatively close to PA compression.
        Allowing to work at lower PA output backoff for a particular level of receiver performance
        Trading off, at the receiver, noise enhancement due to a distortion cancellation process in the receiver, vs Minimizing received signal clips due PA signal exceeding PA rails.
        Optimizing distortion function for operation with a receiver that is capable of handling nonlinear distortion. Where the optimizing may, for example, be in the sense of maximum coded signal transmission performance.
    
    


The composite response of the TX nonlinear shaper and the PA is referred to in this disclosure as the composite nonlinear response. This composite nonlinear response may include memory. As compared to Digital Pre-distortion (DPD) techniques which attempts to substantially linearize the PA response, thus producing a linearized composite response (typically referred to as “soft limiter”), the TX nonlinear shaper of various implementations of this disclosure aims for a nonlinear composite response that is soft (well behaved derivative) and monotonic, and allows substantially better receiver performance (for a receiver that can manage distorted signal) than the linearized composite achieved with conventional DPD.
Referring now to FIGS. 1 and 2, in an example implementation, the uplink (UL) transmitter (e.g., of each of multiple mobile units) have the general block diagram shown in FIGS. 1 and 2. It is understood that the same principles described by this disclosure can be applied in other orthogonal frequency division multiplexed (OFDM) or frequency division multiple access (FDMA) systems such as orthogonal frequency division multiple access (OFDMA), and single carrier FDMA (LTE ScFDMA). The example transmitter 101 comprising forward error correction (FEC) encoding circuit 110, interleaving circuit 112, constellation mapping circuit 114, bin mapping circuitry 116, buffer 118, inverse discrete Fourier transform (IDFT) circuit 120, upsampler 122, Tx nonlinear shaper circuit 100, parallel to serial conversion (P/S) and cyclic prefix (CP) insertion circuit 124, digital filtering and/or windowing circuitry 128, digital-to-analog conversion (DAC) and lowpass filter circuit 128, and power amplifier (PA) circuit 130.
The FEC encoding circuit 110 is operable to encode an incoming bitstream in accordance with any suitable FEC encoding algorithm such as Reed-Solomon encoding, low density parity check (LDPC) encoding, turbo encoding, and/or the like to output FEC codewords.
The interleaving circuit 112 is operable to interleave the FEC symbols/bits output by FEC encoding circuit 110 such that the order in which the FEC symbols/bits emerge from the interleaving circuit 112 is different than the order in which they emerge from the FEC encoding circuit 110.
The constellation mapping circuit 114 is operable to map bits of the FEC codewords to symbols of a selected constellation (e.g., BPSK, QPSK, N-QAM, or the like).
The bin mapping circuitry 116 is operable to assign each of the frequency-domain symbols output by the constellation mapping circuit 114 to a respective one of a plurality of frequency bins. The frequency mapping may, for example, be based on frequency bins assigned to the transmitter 101 by a link partner. For example, where the transmitter 101 is in a LTE handset, the frequencies may be assigned by the base station currently handling the handset. The output of the bin mapping circuitry 116 may be zero padded relative to its input.
The buffer 118 is operable to store the frequency-mapped symbols until an OFDM symbol's worth of constellation symbols (e.g., an integer number F) are buffered, at which point the constellation symbols are passed to the IDFT circuit 120.
The IDFT circuit 120 converts the frequency-domain representation of the constellation symbols to a time-domain representation (e.g., comprising T time-domain samples).
The upsampler 122 is operable to upsample the time-domain representation by a factor of L (e.g., resulting if L×T samples from the original T samples).
The P/S and CP add circuit 124 is operable to convert the parallel stream of time-domain samples to a serial stream and then adds a cyclic prefix.
The digital filtering and/or windowing circuit 126 is operable to apply a windowing function and/or other filtering to the output of circuit 124, resulting in a digital-domain OFDM symbol.
The DAC and lowpass filtering circuit is operable to filter and convert to analog the digital-domain OFDM symbol output by circuit 126, resulting in an analog-domain OFDM symbol.
The power amplifier (PA) 130 is operable to transmit the OFDM symbol onto a wired, wireless, or optical communication medium.
In the example implementation shown in FIGS. 1 and 2, the Tx nonlinear shaper circuit 100 comprises digital nonlinear function (DNF) circuit 102, DNF power spectral density (PSD) shaper 104, PA compensation circuit 106, and iterative PA PSD shaper circuit 108. Each of these circuits is described in further detail below.
In the example transmitter of FIGS. 1 and 2, the input bit stream is encoded by FEC encoder 110, interleaved by interleaver 112, mapped to symbols according to a selected constellations (i.e. QAM mapping) by mapping constellation mapping circuit 114, and then mapped in frequency by frequency mapping circuit 116 to subcarriers allocated to the transmitter 101. These subcarriers are typically allocated by the base station, and may or may not be continuous in frequency. Inverse discrete Fourier transform (IDFT) circuit 120 operates to transform the signal from frequency domain to time domain and the signal is then interpolated by interpolator 122. The resulting oversampled signal x(n) is then passed through the digital nonlinear function (DNF) circuit 102, in order to reduce its PAPR and/or Cubic Metric and improve nonlinear receiver performance. The resulting digitally compressed signal y(n) is fed to the DNF PSD shaper 104 that substantially cancels the out-of-band re-growth due to distortion introduced by DNF circuit 102. The signal z(n) output by PSD shaper circuit 104 is processed by PA compensation circuit 106 which uses a gross model of the PA 130 to approximately compensate for the nonlinearity of the PA 130. The effect of the PA compensation circuitry may be a composite response of the PA compensation circuit 106 and PA 130 that is a soft limiter (i.e., exhibits a clipped linear response). This composite may not need to be an accurate soft limiter, since it just serves to transform the composite response of the DNF 102, the PA compensation circuit 106, and the power amplifier (PA) such that it approximates the nonlinear response targeted by the DNF circuit 102. Therefore the PA compensation circuit 106 can be far less accurate than conventional digital pre-distortion (DPD) functions. The PA compensated signal s(n) is fed to the iterative PA PSD shaper 108, which may operate, when an accurate model of the PA 130 is known, to cancel out the out-of-band distortion produced by the PA 130. A cyclic prefix (CP) is then added by circuit 124 to the output of the iterative PA shaper 108, and windowing may be applied by circuit 126. The resulting signal is DAC converted and filtered by circuit 128, up-converted and amplified by the PA 130.
I. DNF Circuit 102
The DNF circuit 102 may be optimized to compress the transmitted signal to limit out-of-band distortion introduced by the Power Amplifier (e.g. reducing cubic metric) and maximize receiver performance. In various example implementations, the DNF circuit 102 results in a smooth and monotonic nonlinearity designed to allow operation under deep compression at the Power Amplifier 130 without violating transmission mask and still allowing for sufficient receiver performance. A few example Approaches to configuring the DNF circuit 102 will now be discussed. It will be understood, however, that many design approaches are possible and fall within the scope of this disclosure.
The following is notation used in this disclosure.

    
    
        1. x(n)—Original transmission signal
        2. y(n)—Distorted signal
        3. gNL—Digital Nonlinear function (DNF)
        4. fNL—PA nonlinearity
        5. cNL—Composite nonlinearity
        6. xsat—Lowest x value that is saturated by none linearity, i.e.

cNL(x)=cNL(xSAT)=ASAT for any |x|≧xSAT 

        7. hNL—inverse function
        8. ASAT—the maximum PA output signal.
        9. CM—Is the desired cubic metric of the transmission signal.
        10. BPA_O—The PA Output Backoff
        11. σx—RMS of input OFDM signal to DNF
        12. v′,σn—Receiver input noise and its standard deviation of receiver input noise
        13. v,σn—Nonlinear-Solver Receiver output noise and its standard deviation of receiver enhanced noise due to receiver distortion cancellation
        14. σvd—Standard deviation of total distortion and noise at output of distortion cancelling receiver
    
    


A. Example 1
In a first example implementation, the DNF 102 aims to minimize the average total noise and clip distortion experienced by the receiver in the process of cancelling out the distortion. In such an implementation, the DNF 102 approximately models distortion cancellation at the receiver as an inversion of the composite cNL. In other words, the received distorted signal is

y[n]=cNL(x[x])

Thus, the inverting function is denoted hNL (y) such that

hNL(y[n])=hNL(cNL(x[n])+v′[n])≈x[n]

Based on AM/AM and AM/PM distortion curves for the inversion of the composite cNL, the amplitude of the received samples can be used, i.e.

hNL(y[n])=hamp(|y[n]|)·hphase(|y[n]|)·exp(j·arg(y))

where hamp and hphase compute the correct amplitude and phase correction.

The inversion, however, is noisy and biased, two impairments may be desirable to minimize

hNL(y[n])=hNL(cNL(x[n])+v′[n])=x[n]+v[n]+b[n]

where b[n] is the bias occurring when |x[n]|>xSAT, since in this case y[n] cannot be inverted since x[n] is saturated by cNL(x).

To estimate the noise enhancement, the basic identity




  
    
      h
      ′
    
    ⁡
    
      (
      
        
          c
          NL
        
        ⁡
        
          (
          x
          )
        
      
      )
    
  
  =
  
    1
    
      
        c
        NL
        ′
      
      ⁡
      
        (
        x
        )
      
    
  




can be used, which can be easily derived by differentiating h(cNL(x))=x. Where ƒ′( ) denotes the derivative of function ƒ( ).

Thus the total noise+distortion due to clipping is




  
    σ
    vd
    2
  
  =
  
    
      
        2
        
          σ
          x
          2
        
      
      ⁢
      
        
          
            ∫
            0
          
          
            x
            SAT
          
        
        ⁢
        
          
            x
            ·
            
              exp
              ⁡
              
                (
                
                  -
                  
                    
                      x
                      2
                    
                    
                      σ
                      x
                      2
                    
                  
                
                )
              
            
            ·
            
              
                σ
                n
                2
              
              
                
                  (
                  
                    
                      c
                      NL
                      ′
                    
                    ⁡
                    
                      (
                      x
                      )
                    
                  
                  )
                
                2
              
            
          
          ⁢
          dx
        
      
    
    +
    
      
        2
        
          σ
          x
          2
        
      
      ⁢
      
        
          
            ∫
            
              X
              SAT
            
          
          ∞
        
        ⁢
        
          
            x
            ·
            
              exp
              ⁡
              
                (
                
                  -
                  
                    
                      x
                      2
                    
                    
                      σ
                      x
                      2
                    
                  
                
                )
              
            
          
          ⁢
          
            
              (
              
                x
                -
                
                  x
                  SAT
                
              
              )
            
            2
          
          ⁢
          dx
        
      
    
  




Since the inversion is based on the received signal amplitude, and the OFDM signal is complex Gaussian, the underlying distribution determining the noise enhancement is Rayleigh (with corresponding complex Gaussian signal power of σX2).
An example process for configuring the DNF circuit 102 for minimizing average total noise and distortion is as follows:
Using Lagrange multipliers it can be shown that a good choice for the composite function cNL(x) would be such that:




  
    
      
        c
        NL
        ′
      
      ⁡
      
        (
        x
        )
      
    
    3
  
  =
  
    
      
        K
        ·
        x
        ·
        
          exp
          ⁡
          
            (
            
              -
              
                
                  x
                  2
                
                
                  2
                  ·
                  
                    σ
                    x
                    2
                  
                
              
            
            )
          
        
      
      ⁢
      
        
      
      ⁢
      for
      ⁢
      
        
          
        
        ⁢
        
          
        
      
      ⁢
      x
    
    <
    
      X
      SAT
      ′
    
  




And to bound |cNL(x)|≦ASAT K is determined such that




  
    A
    SAT
  
  =
  
    
      
        ∫
        0
      
      
        X
        SAT
        ′
      
    
    ⁢
    
      
        
          c
          NL
          ′
        
        ⁡
        
          (
          x
          )
        
      
      ⁢
      dx
    
  




The parameter X′SAT may be optimized numerically by searching for the X′SAT that minimizes σvd2(X′SAT)
B. Example 2
In another example implementation using a more heuristic criteria, the DNF circuit 102 is used in order transform the complex Gaussian distribution of x[n] at the input of the DNF circuit 102 to another distribution having preferred characteristics at the output of the PA 130. For example, the output distribution may be configured to maximize capacity (or achieve a desired minimum threshold capacity) for the particular power backoff at which the PA 130 is operating. For example, for very low PA output backoff of 3 dB and high signal-to-noise ratio (SNR) at the receiver, the system could transform the input distribution such that the distribution at the output of PA 130 is uniform within a circle of a radii ASAT. This maximizes the entropy of the power-limited transmitted signal, which approximately maximizes capacity in the assumed high SNR case.
The distribution of y=CNL(x) when x is complex Gaussian in again influenced by the derivative c′NL(x). Using the basic identity py (y)=px(cNL−1(y))/cNL′(cNL−1(y)), then to get a uniform distribution the following is needed:




  
    
      
        1
        =
        
        ⁢
        
          
            p
            y
          
          ⁡
          
            (
            y
            )
          
        
      
    
  
  
    
      
        =
        
        ⁢
        
          
            1
            
              πσ
              x
              2
            
          
          ⁢
          
            exp
            ⁡
            
              (
              
                -
                
                  
                    
                      
                        c
                        NL
                        
                          -
                          1
                        
                      
                      ⁡
                      
                        (
                        y
                        )
                      
                    
                    2
                  
                  
                    σ
                    x
                    2
                  
                
              
              )
            
          
          ⁢
          
            1
            
              
                c
                NL
                ′
              
              ⁡
              
                (
                
                  
                    c
                    NL
                    
                      -
                      1
                    
                  
                  ⁡
                  
                    (
                    y
                    )
                  
                
                )
              
            
          
        
      
    
  




Thus to output a uniform distribution the derivative c′NL(x) is set as follows:





  
    
      c
      NL
      ′
    
    ⁡
    
      (
      x
      )
    
  
  =
  
    K
    ·
    
      exp
      ⁡
      
        (
        
          -
          
            
              
                
                  c
                  NL
                  
                    -
                    1
                  
                
                ⁡
                
                  (
                  y
                  )
                
              
              2
            
            
              σ
              x
              2
            
          
        
        )
      
    
  




and to bound |cNL(x)|≦ASAT it is also needed to determine K such that





  
    A
    SAT
  
  =
  
    
      
        ∫
        0
      
      
        X
        SAT
        ′
      
    
    ⁢
    
      
        
          c
          NL
          ′
        
        ⁡
        
          (
          x
          )
        
      
      ⁢
      dx
    
  




As before, the system can select XSAT′ to minimize the overall clip distortion, or optimize it based on receiver performance.
C. Example 3
The approaches in examples 1 and 2 above have a general form of cNL′(x)=K·pdf(x), where the probability density function (pdf(x)) is the underlying Rayleigh or complex Gaussian probability density function. These approaches can be generalized to:

cNL′(x)=K·pdf(x)α

where α is a real positive value, pdf(x) is some probability density function, and K is chosen such that





  
    A
    SAT
  
  =
  
    
      
        ∫
        0
      
      
        X
        SAT
        ′
      
    
    ⁢
    
      
        
          c
          NL
          ′
        
        ⁡
        
          (
          x
          )
        
      
      ⁢
      dx
    
  




This family of DNF functions contains example 2 (above) when pdf(x) is Gaussian and α=1. Empirically, the whole set of functions gives a good tradeoff between noise enhancement and backoff.

As can be seen in FIG. 4, the example DNF functions (for α=0.5 and α=0.2) have larger slope at X=0 than a conventional soft limiter, therefore providing lower backoff and cubic metric. On the other hand, they have soft behavior near ASAT, thus improving receiver performance. Empirically the soft limiter performance achieved by conventional DPD is lower than the performance achieved using the methods and systems described herein.
In example implementations 1-3, above, the composite cNL( ) has been optimized. The composite, however, accounts for the responses of both the DNF 102 and the PA 130. Thus, it is needed to compensate DNF for PA existence to get the desired composite. In other words, fNL(gNL(x))=cNL(x)=>gNL(x)=fNL−1(cNL(x)), where gNL(x) is nonlinear response of the DNF circuit 102. Accurate modeling of the PA 130 is not needed for this purpose. One alternative is to get desired properties of the DNF circuit 102 itself. For example, with low input backoff to the PA 130, the system could optimize gNL(x) directly instead of cNL( ).
D. Example 4
In another example implementation, criteria of optimizing gNL( ) may be used to allow mask compliance at higher transmit power. In some instances, such an optimized gNL( )(e.g., optimized using numerical methods) outperforms conventional DPD in terms of mask compliance.
E. Example 5
In another example implementation, gNL( ) may be optimized (e.g., using numerical methods) to relax the requirements of PA PSD Shaper 108. For example, by optimizing gNL( ) to reduce distortion at high frequency offsets, the requirements of the PA PSD shaper 108 at high frequency offset are relaxed and therefore the PA PSD Shaper 108 may operate at lower overall sampling rate.
II. DNF PSD Shaper Circuit 104
The DNF PSD shaper circuit 104 may operate to reject out-of-band distortion introduced by the DNF 102. In FIGS. 1 and 2, the Digital Nonlinear Function (DNF) PSD shaper 104 is located right after the DNF circuit 102 and is used to reject distortion components generated by the DNF circuit 102. Since the DNF circuit 102 operates digitally, the distortion component it generates are known exactly and therefore can be completely cancelled before being input to the DAC. Some example implementations of the DNF PSD shaper 104 are discussed next.
In a first example implementation, the DNF PSD shaper 104 is operable to compute the distortion in the frequency domain and cancel it. This may comprise the DNF PSD shaper 104 performing discrete Fourier transform (DFT) on the oversampled DNF output y(n) (e.g. at 2× oversampling) to obtain high frequency content of the output of the DNF circuit 102, which contains out-of-band (OOB) components introduced by the DNF circuit 102. The DNF PSD Shaper 104 may then zero, or attenuate below an applicable spectral mask, the OOB components. The DNF PSD shaper 104 may then perform an inverse DFT (IDFT) to convert the signal back to the time domain.
One drawback with the example implementation just discussed, is that cancelling the OOB components increases the PAPR/cubic metric of the signal. Accordingly, in a second example implementation, the DNF PSD Shaper 104 adjusts the filtering/zeroing of the OOB components based on the resulting cubic metric (e.g., attempts to keep the increase in cubic metric within determined bounds).
In another example implementation, the DNF PSD shaper 104 may actively generate an OOB cancelling signal dic[x] that, on one hand, attenuates the OOB components, and on the other hand does not increase PAPR/Cubic Metric. This can be expressed as follows:

CM(y[n]+dic[n])≦CM0 

and

|F(y[n]+dic[n])−F(x[n])|2≦DistortionMask(f)

where CM( ) computes the cubic metric; CM0 is a target cubic metric (e.g. 1.3 dB); and DistortionMask(f) is the maximum allowed DNF distortion mask. For in-band frequencies (as defined by the applicable standard, and which may include some guard band), DistortionMask(f) takes into account the EVM and in-band emissions. For out-of-band frequencies, DistortionMask(f) takes into account adjacent channel leakage ratio (ACLR), and spectral emissions requirements, and also incorporates some margin to allow for distortion introduced by the PA 130.

III. PA Compensation Circuit 106

The foregoing discussed ways to optimize the DNF circuit 102 such that signal characteristics at the output of the PA are improved. Since the PA 130 is part of the composite response from the input of the DNF circuit 102 to the output of the PA 130, in some implementations it is desirable or necessary for the transmitter 101 to compensate for the PA 130, in order to get the desired composite response. As compared to conventional DPD, which turns the composite response into a soft limiter (linear response that is clipped at some level), the PA compensation circuit 106 is not a soft limiter, and can use a much less accurate model of the PA 130.
An aim of the PA compensation circuit 106 can be expressed as

fNL(gNL(x))=cNL(x)

Several example implementations of the PA compensation circuit 106 will now be described.
A first example implementation, already discussed above, directly incorporates the response of the PA compensation circuit 106 into the configuration/operation of the DNF circuit 102. By setting gNL(x)=fNL−1(cNL(x)), then cNL(x)=fNL(gNL(x)). With this approach, the transmitter 101 doesn't need a separate PA compensation circuit 106 in order to comply with an applicable mask and enable sufficient receiver performance.
In another example implementation, the PA compensation circuit 106 is separated from the DNF circuit 102 and the PA Compensation circuit 106 is applied to the output of the DNF PSD Shaper 104. In other words, the processing performed by the PA compensation circuit 106 is s[n]=fNL−1(z[n]) (where fNL( ) may be an approximation). An advantage of the PA compensation circuit 106 operating on the output of the DNF PSD Shaper 104 is that is reduces OOB distortion introduced by the PA 130.
IV. Iterative PA PSD Shaper Circuit 108
FIG. 2 shows details of an example implementation of the PA PSD shaper 108. The example implementation comprises a discrete Fourier transform (DFT) circuit 208, an inverse DFT (IDFT) 210, a composite nonlinear distortion modeling circuit 212, DFT circuit 214, a bin modification circuit 216, a memory 218, a switch 220, and a combiner 222.
The DFT circuit 208 is operable to convert the time-domain signal s(n) to frequency-domain signal S[k] (e.g., using a fast Fourier transform algorithm). The IDFT circuit 210 is operable to convert the frequency-domain signal A[k] to time-domain signal a(n). The discrete Fourier transform (DFT) circuit 208, an inverse DFT (IDFT) 210 may be synchronized to OFDMA or single carrier frequency division multiple access (ScFDMA) symbol time, such that out-of-band corrections would be orthogonal to the desired signal.
The composite nonlinear distortion modeling circuit 212 processes the time-domain signal a(n) to distort the signal using the composite nonlinear distortion model cNL( ). In FIG. 2, cNL( ) may be the composite response of DNF circuit 102, DNF PSD shaper 104, PA compensation circuit 106, and PA 130. Thus, the circuit 212 attempts to distort the signal a(n) in a manner that estimate/predicts the distortion that would result from a(n) passing through the DNF circuit 102, the PA compensation circuit 106, and the PA 130.
The DFT circuit 214 is operable to convert the time-domain signal j(n) to frequency-domain signal J[k] (e.g., using a fast Fourier transform algorithm).
The bin modification circuit 216 is operable to select one or more frequency bins of the signal J[k] to be modified, and modify the selected bin(s). Modification of a bin may comprise, for example, adjusting a real and/or imaginary component (i.e., amplitude and/or phase) of that bin. Additional details of operation of the bin modification circuit 216 are described below.
The combiner 222 comprises circuitry, for example, an adder or adder-subtractor. In the example shown, combiner 222 is configured for of one complex number from another.
The PA PSD shaper circuit 108 may operate to combine its input signal with a pre-distortion signal in order to reject out-of-band distortion due to the PA 130. In an example implementation, the PA PSD shaper circuit 108 may implement an iterative algorithm. The PA PSD shaper circuit 108 may enhance performance in when only a relatively accurate model of the PA 130 is available. As discussed in further detail with reference to FIGS. 3A-3C, in some implementation of the transmitter 101, the PA PSD shaper circuit 108 may be used without use of the other components of the TX nonlinear shaper 100 (i.e., without DNF circuit 102, DNF PSD shaper circuit 104, and PA compensation circuit 106).
A goal of the iterative PA PSD shaper circuit 108 is to mitigate out-of-band (OOB) distortion that may be introduced by the PA 130 and/or the DNF circuit 102 (e.g. when the DNF circuit 102 is located between PA PSD shaper 108 and PA 130, as in the example implementations described below with reference to FIGS. 3A-3C). Unlike conventional DPD, the PA PSD shaper 108 does not change the desired signal, which provides a variety of advantages.
For example, where mask requirements are more difficult than EVM requirements (thus permitting correction of out-of-band distortion at the expense of increasing in-band distortion), as is the case for some communication standards such as LTE ScFDMA, keeping the desired signal intact may reduce the power of pre-distortion signal for the same level of out-of-band rejection (since no need to correct in-band), thus allowing the PA PSD shaper 108 to operate at stronger compression than a conventional DPD system while achieving the same level of out-of-band rejection.
Also, unlike conventional modulation, the fact that the PA PSD shaper 108 keeps the desired signal intact mean that it may be used even in conjunction with high modulations requiring low EVM, when the receiver is capable of dealing with nonlinear distortion introduced by both the PA 130 and the PA PSD shaper 108.
Furthermore, when used with the DNF circuit 102, the fact that the PA PSD shaper circuit 108 keeps the desired signal intact means that desired/intended nonlinearity introduced by the DNF circuit 102 is not disturbed (e.g., not inverted).
The desired signal is a frequency region, e.g. a subset of OFDM bins. As a non-limiting example for illustration, but not limitation, the desired signal in a frequency division multiple access channel (e.g. uplink OFDMA or uplink ScFDMA) may be considered to be either: (1) the entire carrier bandwidth including guard bands; (2) the allocation of a single user within the multiple concurrent OFDMA/ScFDMA allocations sharing the carrier bandwidth; or (3) some superset or subset thereof. In the first case, the PA PSD shaper circuit 108 may correct only distortion violating the transmission mask (not touching in band and guard band distortion). In the second case, the PA PSD shaper 108 also corrects distortion that may leak into frequency bins allocated to other users.
In an example implementation, the iterative PA PSD shaper 108 may correct distortion in the frequency domain (e.g. the OFDM bins domain, that is, correct distortion on an OFDM-bin-by-OFDM-bin basis) by transmitting over frequency regions, not including the desired signal (Desired OFDM bins), a pre-distortion signal generated to cancel the out-of-band distortion introduced by DNF circuit 102, the PA 130, and/or other components of the transmitter 101. When cancellation is done in the OFDM bins domain, the PA PSD shaper circuit 108 can restore OFDMA orthogonality despite the PA compression-induced distortion. Therefore, the TX nonlinear shaper 100 can manage both mask and in-band orthogonality requirements.
As mentioned above, the PA PSD shaper 108 may be used independent of the other components of the Tx nonlinear shaper 100. Examples of this are shown in FIGS. 3A-3C. When applied separately, the PA PSD shaper 108 may improve performance even in communication systems where the receiver is not equipped to handle deep communication signal distortion (e.g., by measuring and modeling the nonlinear response.) In this regard:

    
    
        Assuming the composite response of the analog front-end is known (including both linear and nonlinear components), the PA PSD shaper 108 may be used to cancel the out-of-band distortion (to comply with applicable transmission mask) for any communication system.
        In some communication systems having out-of-band mask requirement that are tougher than error vector magnitude (EVM) requirement, power may, due to nonlinear distortion introduced by the PA 130, need to be reduced to maintain mask compliance while not being limited by receiver EVM. One example is LTE uplink (UL) single carrier FDMA (ScFDMA), the same is typical with other mobile telephony and cellular standards. In this case, use of the PA PSD shaper circuit 108 without the DNF circuit 102, the DNF PSD shaper circuit 104, and the PA compensation circuit 106 may sufficiently reduce out-of-band distortion to meet mask requirements, at the expense of somewhat increasing EVM. In other words, the PA PSD Shaper 108 may enable taking advantage of the EVM headroom. Moreover, in this scenario of not being EVM limited, loss in sensitivity as a result of the use of the PA PSD shaper 108 may be negligible, thus not requiring an advanced receiver that is equipped (e.g., with nonlinearity measuring and/or modeling circuitry) to compensate for the nonlinear distortion introduced by the PA PSD Shaper 108.
        When the PA 130 is linearized by a Digital Pre Distortion and/or envelope tracking circuit (DPD/ET circuit 306 of FIGS. 3A-3C), the composite response of the PA nonlinear response is substantially a soft limiter (i.e. linear response for signals with power below threshold, and saturation for signal with power above threshold). In this case, the composite response of the DPD/ET circuit 306 and PA 130 can be specified simply by saturation power (below which DPD/ET/PA provide a linear response), thus simplifying the configuration and operation of the PA PSD shaper 108. (When the PA PSD Shaper 108 is used without the DPD/ET circuit 306, the nonlinear response of the PA 130 may be tracked and provided to the PA PSD Shaper 108.)
    
    


Referring to FIG. 3A, the example transmitter 301 comprises a generic modulator 302, an interpolator 304, the PA PSD Shaper 108, the P/S and CP circuit 124, the filtering and/or windowing circuit 126, the DNF circuit 102, the DAC and lowpass filter circuit 128, the DPD/ET circuit 306, and the PA 130. The generic modulator 302 represents any communication signal modulator such as, for example, an OFDM, OFDMA, single carrier, single carrier FDMA (ScFDMA) modulator.
Referring to FIG. 3B, the transmitter 351 is similar to the transmitter 101 but with the generic modulator 302 replaced by a ScFDMA modulator composed of the constellation mapper 114, a serial-to-parallel conversion circuit 354, an L-DFT circuit 356, and bin mapper 116. In FIG. 3B, the DFT 208 is absent, or bypassed, since x(n) is already in the frequency domain.
Referring to FIG. 3C, the transmitter 371 is similar to the transmitter 351 but with a different implementation of the PA PSD shaping circuit 108. In FIG. 3C, when the PA PSD Shaper is ready for the next S[K] from bin mapper 116, the switch 220 is configured to convey S[K] to IDFT 210. IDFT 210 then transforms S[K] to a time domain representation. During iteration i on symbol S[K], the output of IDFT 210 is scaled, by matrix multiplier 374, by dcNL−1@Si-1(n), which is the inverse of the derivative of the composite nonlinear distortion model at the point corresponding to the value of Si-1(n) (stored in memory 218). For the first iteration (i.e., i=1) on a particular symbol, the signal stored in memory 218 may be all zeros, and, assuming the cNL is normalized, dcNL−1 at 0=1. For any second and subsequent iteration i on the same symbol, the value stored in the memory 218 is Si-1(n). The output of multiplier 374 is then added to the output of memory 218 to generate Si[n]. Si[n] is then distorted by circuit 212 to generate Ji(n). The signal Ji(n) is then transformed to the frequency domain signal Ji[k] by DFT circuit 214. S[k] for the current symbol is then subtracted off of Ji[k] by combiner 222 to generate Ei[k]. Bin modification circuit 216 then operates on Ei[k] to generate the pre-distortion signal Di[k], which is multiplied by −1 before being fed back via the switch 220 for iteration i+1 on the current symbol (if i is not the last iteration). In an example implementation, the derivative of cNL( ) may be calculated using the Jacobian—viewing the complex function CNL, which has complex input and complex output (C→C), as real function with two-dimensional real input and two-dimensional real output (R2→R2). That is, dcNL−1 may be calculated as the generalized inverse of the Jacobian matrix.
In FIGS. 3A-3C, the P/S and CP circuit 124 is present only for multi-carrier modulations (OFDM, OFDMA, SCFDMA) and not for single carrier modulations. Similarly, the DNF circuit 102 is optional in the transmitters of FIGS. 3A-3C.
In FIGS. 3A-3C, the DNF 102 is optional and is as described above with respect to FIGS. 1 and 2. In transmitters 301 and 351, however, the DNF circuit 102 is a part of the composite nonlinear response of the DNF circuit 102, the DPD/ET circuit 306, and the PA 130. Assuming the DPD/ET circuit 306 effectively linearizes the PA 130 (i.e. the composite response of the two is a soft limiter), the composite response of the DNF 102, DPD/ET circuit 306, and PA 130 will resemble the response of the DNF circuit 102 for input powers below the saturation point. If the DNF circuit 102 were omitted in transmitters 301 and 351, the composite nonlinear response of the DPD/ET circuit 306 and PA 130 is a soft limiter response. Since, in this case, the PA PSD Shaper 108 precedes the DNF 102, it handles the nonlinearity introduced both by the DNF 102 and by the linearized PA response (i.e., the soft limiter response of the DPD/ET circuit 306 and PA 130).
Operation of the example transmitter 301 will now be described. Transmission symbols x[n] are modulated by modulator 302 and then interpolated to a shaper oversampling rate. The resulting samples s(n) are converted to frequency by DFT circuit 208, the resulting frequency domain signal is denoted S[k]. In an example implementation, the PA PSD shaper 108 processes S[k] in an iterative way, using a relatively accurate composite nonlinear distortion model cNL( ). For the first iteration on a particular symbol, the switch 220 is configured to connect the output of the DFT 208 to the combiner 222. The signal S[k] is combined with an initial value of D[k] (output by bin modification circuit 216) to result in an initial value of A[k]. A[k] is then stored to memory 218. For subsequent iterations (if any) on the same symbol, the switch 220 is configured to connect the output of memory 218 to the input of the combiner 222. That is, for second and subsequent iterations on a particular symbol, A[k] is generated from the value of A[k] generated during the previous iteration. In each iteration, A[k] is converted to time domain signal a(n) by IDFT circuit, then circuit 212 distorts the signal a(n) according to cNL( ) to generate signal j(n). The distorted signal j(n) is then converted to frequency domain signal J[k].
In an example implementation, the frequency bins of signal J[k] corresponding to desired signal (i.e., the desired frequency bins of signal S[k]) are then zeroed by bin modification circuit 216, resulting in the frequency distortion signal D[k]. That is, in such an implementation, the signal D[k] is zero valued in one or more frequency bins corresponding to the desired signal and non-zero valued in other bins. These non-zero values of the signal D[k] thus correspond to interference cancelling signals located in undesired frequency bins (i.e., in FIG. 3A, out-of-band frequency bins and/or frequency bins that are in-band but allocated to transmitters other than 301). The frequency distortion signal D[k] is then subtracted from A[k] of the previous iteration (output by memory 218) and the process may be repeated for one or more iterations (e.g. resulting in 1 to 4 iterations in total). In such an implementation, distortion is moved (“shaped”) from undesired frequency bins to desired frequency bins. Thus, upon completion of the ith iteration on a particular symbol, A[k] comprises the original S[k] combined with a pre-distortion signal which is the cumulative result of i values of D[k].
In an example implementation, the frequency bins of signal J[k] corresponding to undesired signal (i.e., undesired frequency bins of signal S[k] and/or additional frequency bins not corresponding to components of signal s(n)) are then zeroed by bin modification circuit 216, resulting in the frequency distortion signal D[k]. That is, in such an implementation, the signal D[k] is zero valued in one or more bins corresponding to undesired signal and non-zero valued in one or more frequency bins corresponding to the desired signal. These non-zero values of the signal D[k] thus correspond to interference cancelling signals located in desired frequency bins (i.e., in FIG. 3A, frequency bins allocated to the transmitter 301). The frequency distortion signal D[k] is then subtracted from A[k] of the previous iteration (output by memory 218) and the process may be repeated for one or more iterations (e.g. resulting in 1 to 4 iterations in total). Thus, upon completion of the ith iteration on a particular symbol, A[k] comprises the original S[k] combined with a pre-distortion signal which is the cumulative result of i values of D[k].
After the ith iteration on a particular symbol, a next symbol S[k] arrives at the PA PSD Shaper 108 and the process repeats. Thus, D[k] is updated for each symbol and thus is periodic with a periodicity synchronized to the symbol timing of S[k].
In the above example, the bin modification circuit 216 gives each bin of J[K] a weight of either 0 or 1 which results in each bin of J[K] being either completely subtracted from A[K], or not at all subtracted. The bin modification circuit 216 is not, however, limited to using only weights of 0 and 1. Any real or complex weights may be used. For example, relatively lower, non-zero real weights may be used for weaker cancellation of distortion on a first set of bins, and relatively higher, non-zero real weights may be used for stronger cancellation of distortion on a second set of bins. Such weightings may be chosen, for example, based on a priori knowledge that weaker cancellation suffices on the first set and/or that stronger cancellation is need on the second set. Alternately, PA PSD Shaper may change the weights dynamically from iteration to iteration based on an amount of excess distortion in a bin at the end of a previous iteration. For example, if distortion of a specific bin is lower than a determined threshold (e.g., determined based on the applicable standard, based on knowledge of the intended receiver, and/or the like) then PA PSD shaper 108 may use a low weight for partial distortion cancellation for that bin, but if distortion is above the threshold, the PA PSD Shaper may apply a higher weight (e.g. up to a weight of 1 to fully cancel distortion for that bin).
In an example implementation, the bin mapper circuit 116 and/or the bin modification circuit 216 may apply a complex weight to frequency bins of signal S[k] corresponding to pilots. Such a weighting may enable better channel estimation in a receiver and thus reduce EVM in the receiver. To explain, the transmitter may insert pilots which a receiver may use to train its equalizer. The pilots may be, for example, scattered among the bins of an OFDM symbol or may be on all bins of certain SC-FDMA symbols (e.g., the UL Reference signal in LTE). Pilots, however, have low-PAPR and thus do not experience significant nonlinear distortion. Therefore, equalizer training based on such low-PAPR pilots does not take into account the nonlinear distortion introduced by the system (including, for example, the PA PSD Shaper 108, the DNF 102, the DPD 306, and/or the PA 130). In some instances, where the receiver is capable, this may be compensated for by providing the nonlinear model (CNL) to the receiver (e.g., via a control channel) and the receiver may thus take it into account when configuring its equalizer and/or other circuitry. In other instances (e.g., in the case of a conventional LTE receiver), however, the receiver is not capable of receiving CNL and knowing how to use it for configuring its circuitry. In these other instances, the transmitter may intentionally distort the pilot symbols (i.e., modify the amplitude and/or phase of the pilots) so that equalizer training in the receiver inherently takes the multiplicative part of the distortion into account.
The complex weight applied to bins of S[k] corresponding to pilots is designated Wp here and may correspond to expectancy, over the set of all possible transmission symbols (i.e., for OFDM, all possible OFDM symbols or, for SC-FDMA, all possible SC-FDMA symbols), of the amplitude reduction and phase rotation caused by the nonlinear elements of the transmitter. The expectancy may be calculated from CNL using a model, formula, or lookup table, for example. The expectancy may depend on the particular allocation of bins among the users.
Although the complex weighting of pilots may occur in the frequency domain, as just described, in other implementations it may be applied in the time domain. Complex weighting of pilots in the time domain may be particularly straightforward where all bins of a particular symbol carry pilots, such as in an LTE UL Reference Signal. This is shown in FIG. 3D where multiplier 390 multiplies S(n) by 1 for data symbols and by Wp for pilot symbols.
In an example implementation (e.g., where the transmitter is in a basestation using downlink (DL) OFDMA), the distortion may be shaped by moving it to frequencies allocated for use with relatively lower-order modulation constellations. For example, if out-of-band distortion is too high and is desired to be moved in-band, the frequencies onto which to move that distortion may be selected to be frequencies allocated for use with relatively lower-order modulation constellations. Similarly, if distortion in a first frequency bin is too high and it is desired to move it to a second one or more bin(s), those second bins may be selected from subcarriers using a lower-order modulation constellation than the constellation being used on the first bin. (e.g., the higher-order constellation may be NQAM and the lower order constellation may be MQAM with N>M). Such distortion shaping may be selected to take advantage of the fact that frequencies allocated for use with higher-order modulation constellations would typically require lower distortion floors than the frequencies allocated for use with the lower-order modulation constellations. Such shaping may be achieved by more aggressive cancelling of distortion on frequencies allocated for use with higher-order modulation constellation allocations and less aggressive cancelling (or no cancelling at all) on frequencies allocated for use with lower-order modulation constellations. The PA PSD Shaper 108 may also operate to move distortion from in-band to out-of-band in cases where very low in-band EVM is needed, and out-of-band rejection requirements can tolerate some additional out-of-band distortion.
In an example implementation (e.g., where the transmitter is in a handset using uplink (UL) ScFDMA), different weights to be applied to different in-band allocated frequencies may be determined based on known noise and/or interference at the receiver. For example, if the noise plus interference floor at receiver is not flat by design of the network (e.g., in a network using fractional frequency re-use), such that there is lower interference on some frequencies than others, the bin modification circuit 216 may take this into account when determining weights to apply to the various frequencies.
Operation of the example transmitter 351 will now be described. A bit stream b[ ] is constellation mapped (e.g., according to a selected QAM constellation) into the symbol stream x[n]. S/P circuit 354 groups the symbol stream into groups of size L, where L is the number of frequency bins allocated for ScFDMA burst transmission. A L-size DFT is performed by L-DFT circuit 356 to transform ScFDMA symbols into L frequency domain bins. The bin mapper 116 then maps the resulting L bins according to specific burst allocation in frequency (i.e., maps the bins to the frequencies allocated to the transmitter 351). The output of the bin mapper 116 represents a DPD oversampled signal, and consists of Nfft*DPD_OVS frequency bins (where Nfft corresponds to ScFDMA carrier BW, and DPD_OVS is the DPD oversampling rate). This frequency domain signal is taken directly as signal S[k] and input to the PA PSD shaper 108. The rest of the processing blocks are the same as described for FIG. 3A. This results in the pre-distortion cancellation signal (accumulation of D[k]) being non-overlapping in frequency and synchronized in time to the desired ScFDMA transmission, and therefore—disregarding non-linearity—orthogonal at the base station receiver to the desired ScFDMA transmission. This type of cyclical and synchronized pre-distortion ensures ScFDMA orthogonality despite nonlinear distortion introduced in the transmitter.
In an example implementation, D[k] for the first iteration may be configured based on a priori knowledge about the communication system. In another example implementation, D[k] for the first iteration may be simply all zeroes. In such an implementation, the IDFT circuit 210 may be skipped for the first iteration and circuit 212 may operate directly on s(n) for the first iteration.
In the example implementations of FIGS. 3A-3C, the PA PSD Shaper 108 is followed by adding CP, filtering and OFDM windowing, optionally applying the Digital Nonlinear Function (DNF), and then digital-to-analog conversion. The DAC output is optionally filtered and processed by DPD/ET which drives the input of the PA 130. The DNF circuit 102 and DPD/ET circuit 306 are optional, and thus any combination of DNF circuit 102, DPD/ET circuit 306, and PA 130 determines the composite nonlinear response cNL( ). That is, the composite nonlinear distortion model cNL( ) may, for example, be a model of the PA 130 (i.e., cNL( )=fNL( )) if neither DPD/ET circuit 306 nor DNF circuit 102 are in use, a soft limiter model when using DPD/ET circuit 306 in combination with the PA 130, or the response of the DNF circuit 102 when using the DNF 102, DPD/ET circuit 306, and PA 130.
When the DPD/ET circuit 306 is present and DNF circuit 102 is not used (i.e., not present or bypassed), then cNL( )=fNL( ) (an estimation of the nonlinear distortion introduced by PA 130). This model may be a memoryless nonlinearity (in the simpler case), or consist of nonlinearity with memory. Estimation of fNL( ) may, for example, be based on feedback from the PA 130 and/or based on a priori information about the PA 130 (e.g., its part number, its bias voltage, characterization data from a manufacturer of the PA, etc.).
When the DPD/ET circuit 306 is present, it may use feedback from PA 130 to estimate, and compensate for, fNL( ). This may result in a composite response that is approximately a soft-limiter (an example soft-Limiter response is shown in FIG. 4). In other words, in this case the cNL( ) used by the PA PSD Shaper 108 may be either a soft limiter or approximately a soft limiter. In the case that the composite response is approximately a soft limiter, the response of the PA may not be completely inverted and the result may be a time invariant response that may compress when the signal approaches saturation. The compression effect may or may not have memory (i.e., depend on previous data). In the case that the composite response is approximately a soft limiter, a representation of the composite nonlinearity may be conveyed from the DPD/ET circuit 306 to the PA PSD shaper 108. In the case that the composite response is a soft-limiter, only power amplifier input power backoff may need to be conveyed to the PA PSD Shaper 108, thus having a very simple interface. In some implementation, however, a soft limiter response (or approximation thereof), may not provide the best performance when used in conjunction with the PA PSD Shaper 108. In such implementations, the DNF circuit 102 may be used to turn the soft limiter response (or approximation thereof) to a response that provides better performance in conjunction with the PA PSD Shaper 108. In this case, the composite non-linearity cNL( ) is composed of the response of the DNF circuit 102, the response of the DPD/ET circuit 306, and the response of the PA 130, and may be computed by the DNF circuit 102 processing the composite nonlinearity model provided by the DPD/ET circuit 306.
In an example implementation, the PA PSD shaper 108 may use numerical optimization to, for example, determine which weights to apply to various bins of J[k]. This may comprise optimization of a performance metric using numerical techniques such as gradient descent. One example of such a performance metric is the mean squared error between permissible out-of-band distortion (as set by an applicable standard and/or regulatory body) and the out-of-band distortion predicted by D[k]. The result of the numerical optimization may be that the bin modification circuit 216 weights differently distortion in different frequency bands. For example, the bin modification circuit 216 may apply higher weights to out-of-band distortion components exceeding an applicable spectral mask and lower weights to distortion components leaking into bins allocated to other users. The use of numerical optimization may use, for example, relatively few gradient descent iterations, thus resulting in a cost-effective implementation.
It is noted that, in the example implementations of FIGS. 1-3C, the TX nonlinear shaping operates cyclically (i.e. CP extended), in order to maintain orthogonality to the desired OFDM signal and possibly weight distortion of different OFDM bins differently. However, in another implementation, the TX nonlinear shaping may be applied after adding the cyclic prefix. Such an implementation is also applicable when CP is replaced by PRBS as in TDS-OFDM, but, in that case, the resulting PRBS interference into the desired signal may need to be corrected (as is the case with conventional PRBS CP systems).
FIG. 5 is a diagram illustrating control of the PA PSD Shaper in accordance with an example implementation of this disclosure. Shown in FIG. 5 is a block 502 representing circuitry operable to configure and control operation of the PA PSD Shaper 108. The control circuitry 502 may, for example, be implemented by a microcontroller of the transmitter, by dedicated control circuitry, and/or by the PA PSD Shaper 108 itself.
The control circuitry 502 is operable to configure the switch 220. This control circuit is also operable to control when the circuit 124 reads in the output of the PA PSD Shaper 108. Through these two controls, the control circuitry 502 can thus control the number of iterations performed on any given symbol. The number of iterations performed on any particular symbol may be determined a priori and/or in real-time. The number of iterations performed on any particular symbol may be determined based on any one or more of a variety of parameters such as: the constellation used to generate the symbol, the particular constellation points in the symbol, the peak to average power ratio (PAPR) of the symbol, the number of subcarriers in the symbol, which subset of a larger subset of subcarriers have been allocated for transmission of the symbol, a spectral mask of the standard with which transmission of the symbol is to comply, a permissible error vector magnitude (e.g., set by an applicable standard and/or by the capabilities of the receiver for which the symbol is destined), the power backoff setting of the power amplifier, a performance metric, and/or the like. A performance metric used to control the number of iterations may be measured by the transmitter and/or may be measured by a receiver and fed back to the transmitter via a control channel. A performance metric used to control the number of iterations may be, for example, an error (e.g., a difference or squared difference) between the signal S(n) or J(n) and a requirement set forth by an applicable standard (e.g., maximum out-of-band power, EVM, and/or the like).
The control circuitry is also operable to configure the bin modification circuit 216. This may comprise selecting which of the bins may be modified and the extent to which the selected bins may be modified. Configuration of the bin modification circuit 216 may be determined a priori and/or in real-time (e.g., on a per-symbol or per-link basis). The configuration of the bin modification circuit 216 for any particular symbol may be determined based on any one or more of a variety of parameters such as: the constellation used to generate the symbol, the particular constellation points in the symbol, the peak to average power ratio (PAPR) of the symbol, the number of subcarriers in the symbol, which subset of a larger subset of subcarriers have been allocated for transmission of the symbol, a spectral mask of the standard with which transmission of the symbol is to comply, a permissible error vector magnitude (e.g., set by an applicable standard and/or by the capabilities of the receiver for which the symbol is destined), the power backoff setting of the power amplifier, a performance metric, and/or the like. A performance metric used to for configuring the bin modification circuit 216 (e.g., configuring weights applied to various bins for any particular iteration i on a symbol) may be measured by the transmitter and/or may be measured by a receiver and fed back to the transmitter via a control channel. A performance metric used to configure the bin modification circuit 216 may be, for example, an error (e.g., a difference or squared difference) between the signal S(n) or J(n) and a requirement set forth by an applicable standard (e.g., maximum out-of-band power, EVM, and/or the like).
In an example implementation, processing
FIG. 6A illustrates an alternate implementation of the transmitter of FIG. 3A. Relative to the implementation shown in FIG. 3A, the implementation in FIG. 6A additionally comprises IDFT 602, accumulator 604, and combiner 606. The IDFT 602 converts D[k] to a time domain representation D(n). The accumulator 604 then sums the values of D[k] over the iterations on symbol s(n). After the last iteration on symbol s(n), the pre-distortion signal output by the accumulator 604 is subtracted from s(n) by combiner 606. In yet another implementation, D[k] may be accumulated in the frequency domain prior to conversion to time-domain representation which may then be subtracted from s(n).
FIG. 6B illustrates an alternate implementation of the transmitter of FIG. 3B. Relative to the implementation shown in FIG. 3B, the implementation in FIG. 6B additionally comprises IDFT 602, accumulator 604, combiner 606, and switch 608. The IDFT 602 converts D[k] to a time domain representation D(n). The switch 608 routes D(n) to accumulator 604 which sums the values of D[k] over the iterations on symbol s(n). After the last iteration on symbol s(n), switch 608 routes s(n) to the combiner 606 and the pre-distortion signal output by the accumulator 604 is subtracted from s(n) by combiner 606. In yet another implementation, D[k] may be accumulated in the frequency domain prior to conversion to time-domain representation which may then be subtracted from s(n).
In accordance with an example implementation of this disclosure, a transmitter (e.g., 301 or 351) comprises at least one nonlinear circuit, and a power spectral density (PSD) shaping circuit (e.g., 108). The PSD shaping circuit is operable to receive a symbol of a modulated signal (e.g., time domain symbol s(n) or frequency domain symbol s[k]), wherein the symbol corresponds to a first one or more frequency bins. The PSD shaping circuit is operable to perform iterative processing of the symbol, wherein each iteration of the processing comprises: generation of a first pre-distortion signal (e.g., frequency domain signal D[k] or time-domain signal D(n)) based on a model of the at least one nonlinear circuit, wherein the pre-distortion signal corresponds to a second one or more frequency bins; and combination of the symbol (e.g., S[k]), or a pre-distorted version of the symbol (e.g., A[k]), with the pre-distortion signal. The generation of the pre-distortion signal may comprises generation of a nonlinearly-distorted signal (e.g., J(n) or J[k]), and adjustment of one or more components of the nonlinearly-distorted signal.
The adjustment may comprise weighting the one or more components of the nonlinearly-distorted signal. The weighting may be determined per frequency bin or per group of frequency bins. The weighting may be determined based on distortion remaining in the pre-distorted signal after an iteration of the iterative processing of the symbol. The one or more components may be in one or more desired signal frequency bands. The one or more desired signal frequency bands may be frequency bands assigned to the transmitter by a basestation. The one or more components may be in one or more undesired signal frequency bands. The one or more undesired signal frequency bands may be out-of-band frequency bands. The one or more undesired signal frequency bands may be frequency bands allocated, by a basestation, to one or more other transmitters. The adjustment of the one or more components may be controlled (e.g., by circuit 502) based on a performance metric (e.g., SNR) fed back to the transmitter from a receiver. The adjustment of the one or more components may be controlled based on order of a modulation constellation used for generation of the symbol. The adjustment of the one or more components may be controlled based on a determination of interference present at a receiver to which said symbol is to be transmitted.
The adjustment of the one or more components may be controlled based on which frequency bands have been allocated to the transmitter by a basestation. The adjustment of the one or more components may results in shifting distortion from out-of-band frequencies to in-band frequencies or from in-band frequencies to out-of-band frequencies. The adjustment of the one or more components may result in shifting distortion from in-band frequencies to out-of-band frequencies. The adjustment of the one or more components may be controlled based on whether a receiver to which the symbol is destined comprises circuitry for modeling and mitigating nonlinear distortion introduced by the transmitter. The at least one nonlinear circuit may comprise a power amplifier and/or a digital pre-distortion circuit. The at least one nonlinear circuit may comprise a digital nonlinear function circuit configured to compress a signal to be transmitted prior to input of the signal to be transmitted to a power amplifier of the transmitter. The said generation of the pre-distortion signal may be based on a seeking of a minimum, maximum, or desired value (e.g., above or below a threshold) of a performance metric. The transmitter may comprise a pilot distortion circuit (e.g., bin mapper 116 or multiplier 390) operable to distort pilots of said symbol.
In accordance with an example implementation of this disclosure, a transmitter (e.g., 301 or 351) may comprise a modulator circuit, a combiner circuit (e.g., 222 and/or 606), a nonlinear distortion modeling circuit (e.g., 212), and a modification circuit (e.g., 216). The modulator is operable to generate a symbol to be transmitted (e.g., time domain symbol s(n) or frequency domain symbol s[k]). The combiner circuit is operable to combine the symbol with a first portion of a pre-distortion signal (e.g., D[k] for a first iteration), a result of the combination being a pre-distorted signal (e.g., a(n)). The nonlinear distortion modeling circuit is operable to: model nonlinear distortion introduced by at least one nonlinear circuit of the transmitter; and nonlinearly distort the pre-distorted signal, a result of the nonlinear distortion being a distorted signal (e.g., J(n) or J[k]). The modification circuit is operable to modify the distorted signal to generate a second portion of a pre-distortion signal (e.g., D[k] for a second iteration). The modification of the distorted signal may be on a per subcarrier basis. The modification of the distorted signal by the modification circuit may comprise zeroing spectral components of the distorted signal.
As utilized herein the terms “circuits” and “circuitry” refer to physical electronic components (i.e. hardware) and any software and/or firmware (“code”) which may configure the hardware, be executed by the hardware, and or otherwise be associated with the hardware. As used herein, for example, a particular processor and memory may comprise a first “circuit” when executing a first one or more lines of code and may comprise a second “circuit” when executing a second one or more lines of code. As utilized herein, “and/or” means any one or more of the items in the list joined by “and/or”. As an example, “x and/or y” means any element of the three-element set {(x), (y), (x, y)}. In other words, “x and/or y” means “one or both of x and y”. As another example, “x, y, and/or z” means any element of the seven-element set {(x), (y), (z), (x, y), (x, z), (y, z), (x, y, z)}. In other words, “x, y and/or z” means “one or more of x, y and z”. As utilized herein, the term “exemplary” means serving as a non-limiting example, instance, or illustration. As utilized herein, the terms “e.g.,” and “for example” set off lists of one or more non-limiting examples, instances, or illustrations. As utilized herein, circuitry is “operable” to perform a function whenever the circuitry comprises the necessary hardware and code (if any is necessary) to perform the function, regardless of whether performance of the function is disabled or not enabled (e.g., by a user-configurable setting, factory trim, etc.).
Other embodiments of the invention may provide a non-transitory computer readable medium and/or storage medium, and/or a non-transitory machine readable medium and/or storage medium, having stored thereon, a machine code and/or a computer program having at least one code section executable by a machine and/or a computer, thereby causing the machine and/or computer to perform the processes as described herein.
Accordingly, the present invention may be realized in hardware, software, or a combination of hardware and software. The present invention may be realized in a centralized fashion in at least one computing system, or in a distributed fashion where different elements are spread across several interconnected computing systems. Any kind of computing system or other apparatus adapted for carrying out the methods described herein is suited. A typical combination of hardware and software may be a general-purpose computing system with a program or other code that, when being loaded and executed, controls the computing system such that it carries out the methods described herein. Another typical implementation may comprise an application specific integrated circuit or chip.
The present invention may also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein, and which when loaded in a computer system is able to carry out these methods. Computer program in the present context means any expression, in any language, code or notation, of a set of instructions intended to cause a system having an information processing capability to perform a particular function either directly or after either or both of the following: a) conversion to another language, code or notation; b) reproduction in a different material form.
While the present invention has been described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the present invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present invention without departing from its scope. Therefore, it is intended that the present invention not be limited to the particular embodiment disclosed, but that the present invention will include all embodiments falling within the scope of the appended claims.

## Claims

1. A system comprising:
combiner circuitry configured to combine a first signal and a second signal to generate a third signal, wherein said third signal is output for transmission onto a communication medium;
nonlinearity modeling circuitry configured to:
model a nonlinear response of a nonlinear circuit, and
generate a fourth signal through nonlinear distortion of a fifth signal using said model; and

bin modification circuitry configured to:
generate said second signal through application of one or more weighting factors to frequency bins of said fourth signal, or of a transformed version of said fourth signal, and
determine said weighting factors based on a difference, or squared difference, error metric.

2. The system of claim 1, wherein said fifth signal is a transformed version of said third signal.

3. The system of claim 1, wherein:
said one or more weighting factors comprise a plurality of weighting factors;
a first weighting factor of said plurality of weighting factors is different than a second weighting factor of said plurality of weighting factors; and
said first weighting factor is applied to a first frequency bin of said fourth signal and said second weighting factor is applied to a second frequency bin of said fourth signal.

4. The system of claim 3, wherein said first frequency bin is a desired frequency bin and said second frequency bin is an undesired frequency bin.

5. The system of claim 3, wherein said first frequency bin is an in-band frequency bin and said second frequency bin is an out-of-band frequency bin.

6. The system of claim 1, wherein said combiner circuitry, said nonlinearity modeling circuitry, and said bin modification circuitry reside in a transmitter.

7. The system of claim 1, wherein said bin modification circuitry is configured to adjust said one or more weighting factors based on a performance metric fed back to said system from a receiver.

8. The system of claim 1, wherein said bin modification circuitry is configured to adjust said one or more weighting factors based on order of a modulation constellation used for generation of a symbol by the system.

9. The system of claim 1, wherein said bin modification circuitry is configured to adjust said one or more weighting factors based on a determination of interference present at a receiver to which a symbol is to be transmitted by the system.

10. A method comprising:
combining, by combiner circuitry of a transmitter, a first signal and a second signal to generate a third signal, wherein said third signal is output for transmission onto a communication medium;
generating, by nonlinearity modeling circuitry of said transmitter, a model of a nonlinear response of a nonlinear circuit of said transmitter;
generating, by said nonlinearity modeling circuitry, a fourth signal through nonlinear distortion of a fifth signal using said model;
generating, by bin modification circuitry of said transmitter, said second signal through application of one or more weighting factors to frequency bins of said fourth signal, or of a transformed version of said fourth signal; and
determining, by said bin modification circuitry, said weighting factors based on a difference, or squared difference, error metric.

11. The method of claim 10, wherein said fifth signal is a transformed version of said third signal.

12. The method of claim 10, wherein:
said one or more weighting factors comprise a plurality of weighting factors;
a first weighting factor of said plurality of weighting factors is different than a second weighting factor of said plurality of weighting factors; and
said first weighting factor is applied to a first frequency bin of said fourth signal and said second weighting factor is applied to a second frequency bin of said fourth signal.

13. The method of claim 12, wherein said first frequency bin is a desired frequency bin and said second frequency bin is an undesired frequency bin.

14. The method of claim 12, wherein said first frequency bin is an in-band frequency bin and said second frequency bin is an out-of-band frequency bin.

15. The method of claim 10, wherein said combiner circuitry, said nonlinearity modeling circuitry, and said bin modification circuitry reside in the transmitter.

16. The method of claim 10, further comprising adjusting, by said bin modification circuitry, said one or more weighting factors based on a performance metric fed back to said transmitter from a receiver.

17. The method of claim 10, further comprising adjusting, by said bin modification circuitry, said one or more weighting factors based on order of a modulation constellation used for generation of a symbol by the transmitter.

18. The method of claim 10, further comprising adjusting, by said bin modification circuitry, said one or more weighting factors based on a determination of interference present at a receiver to which a symbol is to be transmitted.