Classifications

• • H—ELECTRICITY
  • H03—ELECTRONIC CIRCUITRY
  • H03F—AMPLIFIERS
  • H03F1/00—Details of amplifiers with only discharge tubes, only semiconductor devices or only unspecified devices as amplifying elements
  • H03F1/32—Modifications of amplifiers to reduce non-linear distortion
  • H03F1/3241—Modifications of amplifiers to reduce non-linear distortion using predistortion circuits
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
  • H04B1/02—Transmitters
  • H04B1/04—Circuits
  • H04B1/0475—Circuits with means for limiting noise, interference or distortion
• • H—ELECTRICITY
  • H03—ELECTRONIC CIRCUITRY
  • H03F—AMPLIFIERS
  • H03F1/00—Details of amplifiers with only discharge tubes, only semiconductor devices or only unspecified devices as amplifying elements
  • H03F1/32—Modifications of amplifiers to reduce non-linear distortion
  • H03F1/3241—Modifications of amplifiers to reduce non-linear distortion using predistortion circuits
  • H03F1/3252—Modifications of amplifiers to reduce non-linear distortion using predistortion circuits using multiple parallel paths between input and output
• • H—ELECTRICITY
  • H03—ELECTRONIC CIRCUITRY
  • H03F—AMPLIFIERS
  • H03F1/00—Details of amplifiers with only discharge tubes, only semiconductor devices or only unspecified devices as amplifying elements
  • H03F1/32—Modifications of amplifiers to reduce non-linear distortion
  • H03F1/3241—Modifications of amplifiers to reduce non-linear distortion using predistortion circuits
  • H03F1/3258—Modifications of amplifiers to reduce non-linear distortion using predistortion circuits based on polynomial terms
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
  • H04L41/06—Management of faults, events, alarms or notifications
  • H04L41/0654—Management of faults, events, alarms or notifications using network fault recovery
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04B—TRANSMISSION
  • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
  • H04B1/02—Transmitters
  • H04B1/04—Circuits
  • H04B2001/0408—Circuits with power amplifiers
  • H04B2001/0425—Circuits with power amplifiers with linearisation using predistortion

Definitions

• This invention relates to digital compensation of a non-linear circuit, and in particular, to linearization of a non-linear power amplifier and transmitter chain.
• a concept of applying a digital compensation to restore the quality of an original signal passed through a circuit is a routine.
• a power amplifier in a radio of a wireless base station or handset is compensated digitally in the baseband to minimize the spectral leakage into adjacent channels.
• An audio amplifier in a speaker is compensated digitally to achieve high fidelity.
• variants of Volterra series have been adopted to account for dynamical nature of nonlinearity. Wiener, Wiener-Hammerstein, General Memoryless Polynomial are popular structures for digital pre-distorters, which are used to modify an input signal prior to passing through a non-linear circuit.
• these structures have an exponential complexity if the polynomial order exceeds 3 to 5, as well as robustness issues due to sensitivity of compensator parameters to variations of a particular device (Device Under Test, DUT), including process, temperature, supply voltage, and other operating conditions.
• DUT Device Under Test
• a digital input signal x[n] at a baseband or intermediate frequency is passed through a Digital Pre-Distorter (DPD) 1 10 to produce a "pre-distorted" input y[n] , which is passed through a transmit chain 140 to produce a driving signal pit) that drives an antenna 150.
• the transmit chain may include a Digital-to-Analog Converter (DAC) 142, an analog lowpass filter (LPF) 144, and a modulator (e.g., multiplication by a local oscillator) of the output of the LPF 144.
• the output of the modulator is passed to a power amplifier (PA) 148.
• PA power amplifier
• the PA 148 may introduce non- linearities, which may be manifested in the driving signal p(t) as harmonic and/or intermodulation distortion of the input signal x[n] .
• the DPD 1 10 also introduces non-linearities that are intended to "pre-invert" (i.e. pre-distort) the non-linear effects of the transmit chain.
• the DPD performs the transformation of the desired signal x[n] to the input y[n] of the transmit chain by using delay elements 120 to form a set of delayed versions of the desired signal, and then using a non-linear polynomial function 130 of those delayed inputs.
• the non-linear function is a Volterra series:
• an approach to digital compensation uses a particular structure for a digital pre-distorter (DPD) which acts as a relatively accurate pre-inverse of a nonlinear circuit (e.g., a non-linear transmit chain involving digital-to-analog converter (DAC), lowpass filter, modulator, bandpass filter, and power amplifier) while making use of a relatively small number of parameters that characterize the non-linearity and/or parameters that provide accurate linearization without requiring continual updating.
• DPD digital pre-distorter
• DAC digital-to-analog converter
• this approach is more closely related to the underlying sources of non- linearity arising from the modulation and subsequent (e.g., non-linear) amplification of the modulated signal.
• the approach more directly captures harmonic and intermodulation distortion effects without requiring a large number of parameters.
• a pre-distorter implements an overall non-linear transformation of a sampled input signal u[n ⁇ (e.g., an upsampled version of a baseband encoding of a desired signal to be transmitted) to yield an input y[m] to a transmit chain.
• the overall non-linear transformation is implemented using a combination of time filtered versions of linear and non-linear functions of the input signal. In this description, these time filtered versions are referred to as basis functions of the input signal. Some examples of such basis functions include
• f j ( ) may be a non-linear function of u , for example, ⁇ ⁇ k , and G ; ( ) may be a linear time domain filtering.
• a set of basis functions is combined using a "balanced polynomial" form, which can be ex ressed as: where i J
• the parameters for a device are determined prior to operation, for example, at a fabrication, manufacture, deployment, and/or periodic maintenance time, and then set for subsequent operation.
• different sets of parameters are determined for different operating conditions (e.g., operating temperature, supply voltage, etc.), and in operation different sets of parameters are used according to sensing of the operating conditions.
• external parameters such as temperature, supply voltage, output power, modulation mode, part age, sampling rate and part signature are inputs to a previously configured predictor unit. Based on these, the unit determines the regime of operation and outputs updated coefficients for the compensator.
• the part signature is obtained by short fabrication-time characterization (e.g. few tones or a special transmit sequence).
• One or more approaches described above have advantages including reduced operation-time computation complexity, thereby reducing power requirements and use of other computation-related resources, while providing relatively accurate linearization (e.g., relative to other approaches that use comparable computation resources).
• the predictor can continuously update the coefficients in response to, for example, temperature changes, or supply voltage changes.
• FIG. 1 is a block diagram of a conventional digital pre-distortion approach
• FIG. 2 is a block diagram representing a number of embodiments of the present approach
• FIG. 3 is a block diagram illustrates a coefficient interpolation approach
• FIG. 4 is a block diagram that shows a operation-time parameter estimation approach
• FIG. 5 is a block diagram that shows a pre-operation coefficient modeling approach
• FIG. 6 is a block diagram showing a combined coefficient interpolation and operation time parameter estimation approach
• FIG. 7 is a block diagram of an exemplary basis formation and polynomial combination embodiment.
• FIG. 8 is a block diagram of an alternative basis formation approach incorporating normalization. Description
• a first embodiment of a Digital Pre-Distorter 200 accepts a desired input signal x[m] in digital form (e.g., 12-14 bits per time sample), sampled at a sampling rate sufficient to represent the bandwidth (e.g., 20- 120MHz) of the desired signal.
• the input signal is complex, with the real and imaginary parts representing quadrature components of the signal to be transmitted.
• the desired input is a baseband encoding (e.g., an OFDM encoding) of one or more channels of communication, for instance, for a cellular telephone transmitter (e.g., according to an LTE communication standard).
• the input signal is upsampled using a conventional upsam ling/interpolation component 210, for example, in some embodiments by a factor equal to one plus the degree of nonlinearity of interest in the transmit chain divided by two (e.g., if nonlinearity of interest is 7 th order, then upsampling by a factor of four is used), and then optionally filtered. Upsampling enables the DPD by shrinking the spectrum to avoid aliasing of undesirable harmonics in the target band.
• an optional LTI (Linear Time Invariant) filtering component 212 processes the signal after upsampling.
• the LTI filter is selected to "mimic" the long- term behavior of the elements of the transmit chain 140, for example, for the DAC 142, the LPF 144, etc.
• the fixed-coefficient reconstruction filter mimics the zero- order hold properties of the DAC.
• the upsampled and filtered input signal u(n) is then used to compute 5 basic signals, w n through w s [n] , each sampled at the upsampled rate, using a set of basis formation elements 220a-s, most of which represent non-linear transformations (e.g., polynomial function) of the input.
• the basis formation can incorporate polynomial function of the input, or alternatively non-polynomial function, for example, a polynomial X
• the basis signals are applied to balanced polynomial computation element 230, or in alternative embodiments another form of non-linear combination, which outputs a combined signal z[n] at the upsampled rate. This combined signal is then downsampled in a
• downsampling/filtering component 240 and optionally further filtered in a LTI filtering component 242, for example, yielding the original sampling rate of the input signal x [m]
• the output y[m] of the DPD 200 is passed through a transmit chain 140 to produce the driving signal pit) for the antenna
• the DPD 200 and more particularly the balanced polynomial computation is configured according to numerical parameters, the DPD coefficients ⁇ 235.
• these coefficients are determined using a database of coefficients 344, and values that essentially characterize the operation
• “regime” i.e., a class of physical conditions of the transmit chain.
• These values include environment variables 342 (e.g., temperature, transmitter power level, supply voltage, frequency band) and/or a part "signature" 343, which represents substantially invariant characteristics and which may be unique to the electronic parts of the transmit chain 140.
• the coefficient interpolator 340 takes these inputs and the coefficient database and outputs corresponding DPD coefficients 235.
• a variety of approaches may be implemented by the coefficient interpolator, including selection and/or interpolation of coefficient values in the database according to the inputs, and/or applying a mathematical mapping of the input represented by values in the coefficient database.
• the DPD coefficients 235 are determined during operation of the system by using a receive chain 430 processes a sensing of the output p ⁇ t) , and though substantially linear demodulation, and
• the coefficients are adjusted in a substantially continuous manner during operation, while in other examples, the coefficients are updated relatively infrequently in batches (e.g., once an hour, day, etc.) using non-operational inputs. The determination of these parameters is discussed more fully below, and generally relies on sensing of an output of the transmit chain 140, and processing that sensed output using a receive chain 330, which is assumed to be substantially linear.
• an approach to forming the coefficient database 344 makes use of an analysis the transmit chain 140 prior to operational use. More generally, a set of instances of transmit chains (e.g., using separately manufactured parts) are analyzed to sample manufacturing and other part-to-part variations. Generally, different test signals x[m] are used to drive the transmit chain 140, and corresponding input y[m] and received output q[m] (i.e., after demodulating through the received chain 430), are used to estimate DPD coefficients 235 under various environmental conditions.
• each instance of the transmit chain may be characterized by passing specific test signals through the transmit chain 140 and using a signature measurement module 550 to determine signature values (e.g., quantitative or categorical values) from those measurements. For example, multi-tone test signals may be passed through the transmit chain and the magnitude of distortion products may be measured and recorded as elements of the part signature.
• signature values e.g., quantitative or categorical values
• the part signature for a transmit chain is provided in association with that transmit chain, and used in operation, for example, as part signature 343 as illustrated in FIG. 3.
• the part signature may be stored on a computer readable medium (e.g., non- volatile semiconductor memory) in, coupled to, or otherwise associated with the transmit chain or its components.
• the part signature imparts specific functionality on the DPD to compensate for non-linearities of the specific instance of the transmit chain.
• coefficient interpolator 340 may implement various forms or interpolation or approximation as long as they are compatible with the coefficient modeler 560 (e.g., FIG. 5).
• Such techniques can include the use of a piecewise linear interpolation as a nonessential example.
• Other ways of mapping from the environment and signature variables include use of other piecewise smooth functions, kernel approach, etc..
• FIG. 6 yet another embodiment combines aspects shown in FIG. 3 and in FIG. 4, namely that the DPD coefficients 235 depend not only on an interpolation based on a coefficient database 344 and environment variables 342 and/or part signature 343, but also depend on feedback of sensed and demodulated via a receive chain 330 of the output of the transmit chain 140.
• the set of basis formation elements 220a-s include elements that can be represented as basis formation element 220i shown in FIG. 7.
• each such basis formation element includes a representative transformation element 410i and a (e.g., LTI) filter element 420i.
• 2 , f(u)
• u I 3 , f(u) u ⁇ u ⁇ 2 , etc.
• the filter elements are generally linear and time invariant (LTI), for example, implementing one-pole or two-pole linear infinite-impulse-response (IIR) filters.
• the poles of such filters may correspond to time constants of 1 to 4 samples and Q factors of 10.
• H(w, , w 2 , w 3 ) -j W, W,W2 + w 3 .
• some or all of the basis formation blocks 220a-s may use "non-polynomial" forms.
• a normalization block 820i may be used to normalize a basis value by dividing by an average value (e.g., a long time scale decaying average). It should be recognized that this type of normalization is only an example of a non-polynomial form of basis formation.
• the output z[n] is then downsampled and filtered, for example, to the original sampling rate of the input x[m] to yield the output y[m] .
• this downsampling may be omitted, or the sampling rate of the output may be between the sampling rate of the input and the upsampled rate.
• an optional LTI filtering stage 242 is applied at the output of the DPD 200 prior to passing the signal to the transmit chain.
• the structure of the DPD described above is robust to variation during operation and does not necessarily have to be adapted quickly during operation in order to maintain the linearization of the system.
• the parameters for the DPD may be estimated once for long periods of operation, for example, being estimated during manufacturing or deployment of the system.
• a receive chain 330 processes a sensing of the output p(t) , and though substantially linear demodulation, and digitization, produces an digital output q[m] at the same sampling rate as the input y[m] of the transmit chain. Note that as introduced above, this estimation may be uses as part of formation of the coefficients of the database 344, and may also be used in operational adjustment of the coefficients as illustrated in FIGS. 4 and 6.
• the collected data sequences e K _ ] [rn ⁇ ., representing the pre-distortion added to the original signal are obtained through iterations as follows:
• the parameters ⁇ are determined based on a predictor, which accepts parameters, for instance, temperature, power supply voltage (Vdd), sampling rate, modulation mode, frequency band, part signature (e.g., obtained by short in-fab part characterization using a few tones or a special transmit sequences), and part age. Based on these, the predictor unit determines the regime of operation for the compensator and outputs updated coefficients for the compensator and selects parameters of a predetermined set of parameters.
• Vdd power supply voltage
• Vdd power supply voltage
• sampling rate sampling rate
• modulation mode e.g., obtained by short in-fab part characterization using a few tones or a special transmit sequences
• part signature e.g., obtained by short in-fab part characterization using a few tones or a special transmit sequences
• Implementations of the approaches described above may use hardware, software, or a combination of hardware and software.
• Software may include instructions for a general purpose, a special purpose processor or a heterogeneous processor, with the instructions being stored on a non-transitory machine readable medium and read from the medium for execution by the processor.
• the instructions may be machine level, or may be represented in programming language form.
• at least some of the transmit chain is implemented in software, and the DPD approach is implemented as further software executed on the sample signal processor or system that implements that part of the transmit chain.
• the software is executed on a processor specifically dedicated to implementation of the DPD.
• circuitry which generally includes circuitry for digital signal processing (e.g., arithmetic computation circuitry) which may be dedicated (e.g., as application specific integrated circuits, ASICs, or Field- Programmable Gate Arrays) to particular functions described above and/or may be controlled by software instructions that implement the functions.
• digital signal processing e.g., arithmetic computation circuitry
• ASICs application specific integrated circuits
• Field- Programmable Gate Arrays e.g., field- Programmable Gate Arrays
• a computer accessible storage medium includes a database
• a computer accessible storage medium may include any non-transitory storage media accessible by a computer during use to provide instructions and/or data to the computer.
• a computer accessible storage medium may include storage media such as magnetic or optical disks and semiconductor memories.
• the database representative of the system may be a database or other data structure which can be read by a program and used, directly or indirectly, to fabricate the hardware comprising the system.
• the database may be a behavioral-level description or register-transfer level (RTL) description of the hardware functionality in a high level design language (HDL) such as Verilog or VHDL.
• HDL high level design language
• the description may be read by a synthesis tool which may synthesize the description to produce a netlist comprising a list of gates from a synthesis library.
• the netlist comprises a set of gates which also represent the functionality of the hardware comprising the DPD.
• the netlist may then be placed and routed to either produce the configuration bitfile for the Field-Programmable Gate Array or produce a data set describing geometric shapes to be applied to masks.
• the masks may then be used in various semiconductor fabrication steps to produce a semiconductor circuit or circuits corresponding to the DPD
• the database may itself be the netlist (with or without the synthesis library) or the data set

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• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• Nonlinear Science (AREA)
• Power Engineering (AREA)
• Computer Networks & Wireless Communication (AREA)
• Signal Processing (AREA)
• Algebra (AREA)
• General Physics & Mathematics (AREA)
• Mathematical Analysis (AREA)
• Mathematical Optimization (AREA)
• Pure & Applied Mathematics (AREA)
• Amplifiers (AREA)
• Transmitters (AREA)

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• 2015
  • 2015-11-30 US US14/953,762 patent/US9590668B1/en active Active
• 2016
  • 2016-11-30 EP EP16820391.7A patent/EP3384597B1/en active Active
  • 2016-11-30 JP JP2018526946A patent/JP6774492B2/ja not_active Expired - Fee Related
  • 2016-11-30 WO PCT/US2016/064127 patent/WO2017095869A1/en not_active Ceased
  • 2016-11-30 KR KR1020187018592A patent/KR20180088882A/ko not_active Withdrawn
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