# US 2014/0192922 A1 · Modeling transmitter and/or transmit observation receiver frequency response and utilization thereof > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0192922 A1 - Document ID: US20140192922A1 - Status: Published application - Kind: A1 - Application number: 13/734,238 - Filed: 2013-01-04 - Published: 2014-07-10 - Earliest claimed: 2013-01-04 - Assignees: Telefonaktiebolaget L M Ericsson (publ) - Applicants: Telefonaktiebolaget L M Ericsson (Publ) - Inventors: Mark Wyville - Web page: https://patentgrep.com/patent/US20140192922A1 ## CPC - H04B 1/62: for providing a predistortion of the signal in the transmitter and corresponding correction in the receiver, e.g. for improving the signal/noise ratio - H03F 1/3241: {using predistortion circuits (H03F1/3211, H03F1/3217 take precedence)} - H04B 1/04: Circuits - H04B 1/0475: {with means for limiting noise, interference or distortion (H04B1/0483 takes precedence)} - H04B 1/40: Circuits - H04B 2001/0425: {with linearisation using predistortion} - H04B: TRANSMISSION - H03F: AMPLIFIERS ## Abstract Systems and methods for training, or calibrating, a model of a frequency response of a transmitter and/or a model of a frequency response of a transmit observation receiver coupled to an output of the transmitter are disclosed. In one embodiment, in order to train a model of the frequency response of the transmitter and/or a model of the frequency response of the transmit observation receiver, a nonlinear component is connected between an output of the transmitter and an input of the transmit observation receiver. A combined model for the frequency response of the transmitter, a nonlinear characteristic of the nonlinear component, and the frequency response of the transmit observation receiver is then trained. Preferably, once the combined model is trained, the nonlinear component is disconnected for normal operation of the transmitter and the transmit observation receiver. ## Claims ### Claim 1 A method comprising: connecting a nonlinear component between an output of a transmitter and an input of a transmit observation receiver that is coupled to the output of the transmitter; and training a combined model of a frequency response of the transmitter, a nonlinear characteristic of the nonlinear component, and a frequency response of the transmit observation receiver, the combined model comprising concatenation of a model of a first linear filter that corresponds to a model of the frequency response of the transmitter, a model of a quasi-memoryless nonlinearity that represents a model of the nonlinear characteristic of the nonlinear component, and a model of a second linear filter that represents a model of the frequency response of the transmit observation receiver. ### Claim 2 (depends on 1) The method of claim 1 further comprising disconnecting the nonlinear component after training the combined model. ### Claim 3 (depends on 1) The method of claim 1 wherein connecting the nonlinear component comprises connecting the nonlinear component between the output of the transmitter and a coupler that couples the output of the transmitter to the input of the transmit observation receiver. ### Claim 4 (depends on 1) The method of claim 1 wherein connecting the nonlinear component comprises connecting the nonlinear component between a coupler that couples the output of the transmitter to the input of the transmit observation receiver and the input of the transmit observation receiver. ### Claim 5 (depends on 1) The method of claim 1 wherein training the combined model of the frequency response of the transmitter, the nonlinear characteristic of the nonlinear component, and the frequency response of the transmit observation receiver comprises: providing one or more test signals to an input of the transmitter; receiving one or more observed test signals from an output of the transmit observation receiver in response to providing the one or more test signals to the input of the transmitter; and training the combined model based on the one or more test signals and the one or more observed test signals. ### Claim 6 (depends on 5) The method of claim 5 wherein the one or more test signals are small signals such that components of the transmitter operate linearly. ### Claim 7 (depends on 6) The method of claim 6 wherein the one or more test signals comprise a plurality of test signals at different frequencies. ### Claim 8 (depends on 1) The method of claim 1 wherein the transmitter comprises a digital predistortion subsystem, and training the combined model of the frequency response of the transmitter, the nonlinear characteristic of the nonlinear component, and the frequency response of the transmit observation receiver comprises training the combined model during normal operation while the digital predistortion subsystem is active. ### Claim 9 (depends on 8) The method of claim 8 wherein connecting the nonlinear component comprises connecting the nonlinear component between a coupler that couples the output of the transmitter to the input of the transmit observation receiver and the input of the transmit observation receiver. ### Claim 10 (depends on 1) The method of claim 1 further comprising, after training the combined model: disconnecting the nonlinear component; and applying an inverse of the model of the frequency response of the transmit observation receiver to an output signal of the transmit observation receiver during normal operation. ### Claim 11 (depends on 1) The method of claim 1 further comprising, after training the combined model: disconnecting the nonlinear component; and applying an inverse of the model of the frequency response of the transmitter to an input signal of the transmitter during normal operation. ### Claim 12 (depends on 1) The method of claim 1 wherein the nonlinear component has a known nonlinear characteristic, and training the combined model comprises training the combined model based on the known nonlinear characteristic of the nonlinear component. ### Claim 13 (depends on 1) The method of claim 1 wherein the nonlinear component is a quasi-memoryless nonlinear component. ### Claim 14 A system comprising: a transmitter; a transmit observation receiver having an input that is coupled to an output of the transmitter; a nonlinear component connected between the output of the transmitter and the input of the transmit observation receiver; and a baseband processor configured to train a combined model of a frequency response of the transmitter, a nonlinear characteristic of the nonlinear component, and a frequency response of the transmit observation receiver, the combined model comprising concatenation of a model of a first linear filter that corresponds to a model of the frequency response of the transmitter, a model of a quasi-memoryless nonlinearity that represents a model of the nonlinear characteristic of the nonlinear component, and a model of a second linear filter that represents a model of the frequency response of the transmit observation receiver. ### Claim 15 (depends on 14) The system of claim 14 wherein the nonlinear component is disconnected after the combined model is trained. ### Claim 16 (depends on 14) The system of claim 14 wherein the nonlinear component is connected between the output of the transmitter and a coupler that couples the output of the transmitter to the input of the transmit observation receiver. ### Claim 17 (depends on 14) The system of claim 14 wherein the nonlinear component is connected between a coupler that couples the output of the transmitter to the input of the transmit observation receiver and the input of the transmit observation receiver. ### Claim 18 (depends on 14) The system of claim 14 wherein, in order to train the combined model, the baseband processor is further configured to: provide one or more test signals to an input of the transmitter; receive one or more observed test signals from an output of the transmit observation receiver in response to providing the one or more test signals to the input of the transmitter; and train the combined model based on the one or more test signals and the one or more observed test signals. ### Claim 19 (depends on 18) The system of claim 18 wherein the one or more test signals are small signals such that components of the transmitter operate linearly. ### Claim 20 (depends on 19) The system of claim 19 wherein the one or more test signals comprise a plurality of test signals at different frequencies. ### Claim 21 (depends on 14) The system of claim 14 wherein the transmitter comprises a digital predistortion subsystem, and the baseband processor is configured to train the combined model during normal operation while the digital predistortion subsystem is active. ### Claim 22 (depends on 21) The system of claim 21 wherein the nonlinear component is connected between a coupler that couples the output of the transmitter to the input of the transmit observation receiver and the input of the transmit observation receiver. ### Claim 23 (depends on 14) The system of claim 14 wherein, after the combined model is trained, the nonlinear component is disconnected, and an inverse model component applies an inverse of the model of the frequency response of the transmit observation receiver to an output signal of the transmit observation receiver during normal operation. ### Claim 24 (depends on 14) The system of claim 14 wherein, after the combined model is trained, the nonlinear component is disconnected, and an inverse model component applies an inverse of the model of the frequency response of the transmitter to an input signal of the transmitter during normal operation. ### Claim 25 (depends on 14) The system of claim 14 wherein the nonlinear component has a known nonlinear characteristic, and the baseband processor is configured to train the combined model based on the known nonlinear characteristic of the nonlinear component. ### Claim 26 (depends on 14) The system of claim 14 wherein the nonlinear component is a quasi-memoryless nonlinear component.