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US 11,387,859 B2Granted
Method and apparatus for mitigating image interference in a receiver
AssigneeMotorola Solutions, Inc.
InventorsSumit A Talwalkar, Geetha B. Nagaraj, Nicholas G. Cafaro
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Abstract
An improved superheterodyne receiver for a portable radio is provided. The receiver includes a frequency controller that applies pulse-shaped modulation to first and second LO signals in a synchronized manner. The frequency controller is steered by Artificial Intelligence (AI) based machine learning (ML) to determine first and second LOs that minimize image interference in the baseband signal.
Claims18
A receiver, comprising:
- a first mixer receiving a radio frequency (RF) signal and a first local oscillator (LO) signal to generate an intermediate frequency (IF) signal;
- an IF filter filtering the IF signal to generate a filtered IF signal;
- a second mixer receiving the filtered IF signal and a second local oscillator (LO) signal to generate a baseband signal;
- a frequency controller coupled between the first and second mixers, the frequency controller applying pulse-shaped modulation to the first and second LO signals in a synchronized manner;
- and
- the frequency controller being steered by Artificial Intelligence (AI) based machine learning (ML) to determine first and second LO modulations that cancel each other to generate the baseband signal, and the first and second LO modulations add to each other to spread image interference.
3 more elements
A method of controlling interference to a receiver, comprising:
- mixing a radio frequency (RF) signal and a first local oscillator (LO) signal to generate an intermediate frequency (IF) signal;
- filtering the IF signal to generate a filtered IF signal;
- mixing the filtered IF signal and a second local oscillator (LO) signal to generate a baseband signal;
- and controlling frequency modulation of the first and second LO signals synchronously using pulse shaping via a frequency controller, the frequency controller being steered by Artificial Intelligence (AI) based machine learning (ML) to determine first and second LO modulations that cancel each other to generate the baseband signal, and the first and second LO modulations add to each other to spread image interference.
1 more element
Dependencies are inferred from the claim text.