Method and apparatus for determining a set of optimal coefficients
AssigneeHuawei Technologies Co., Ltd.
InventorsShayan Shahramian, Ryan Bespalko
Life of this patent
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Abstract
The disclosed systems, structures, and methods are directed to a method for determining a set of N optimal coefficients to be supplied to an equalizer, the equalizer being employed in at least one of a serializer and a deserializer, the method comprising: receiving N different parameters, searching an initial set of N coefficients on an N-dimensional performance surface, in accordance with a genetic algorithm, wherein the N-dimensional performance surface corresponds to various coefficients in the N parameters, and fine tuning the initial set of N coefficients to provide the set of N optimal coefficients, in accordance with a gradient descent algorithm.
Claims19
A method for determining a set of N optimal coefficients to be supplied to an equalizer, the equalizer being employed in at least one of a serializer and a deserializer, the method comprising:
- receiving N different operational parameters, each operational parameter including a plurality of coefficients;
- searching an initial set of N coefficients on an N-dimensional performance surface, in accordance with a genetic algorithm, wherein the N-dimensional performance surface corresponds to various coefficients of the N operational parameters, wherein searching the initial set of N coefficients comprises:
- randomly selecting k sets of coefficients from the N operational parameters;
- selecting first top sets s1 of coefficients from N operational parameters, in accordance with a cost function;
- evolving second sets s2 of coefficients in accordance with the first top sets s1 of coefficients;
- randomly selecting other sets of coefficients in a controlled random manner and providing third sets s3 of coefficients, wherein the third sets s3 of coefficients includes the first set of coefficients s1 and the second set of coefficients s2 and the other sets of coefficients;
- randomly selecting fourth m sets s4 of coefficients from the N operational parameters;
- and
- providing the initial set of N coefficients in accordance with the third sets s3 of coefficients and the fourth sets s4 of coefficients;
- and
- fine tuning the initial set of N coefficients to provide the set of N optimal coefficients, in accordance with a gradient descent algorithm.
A system for determining a set of N optimal coefficients to be supplied to an equalizer, the equalizer being employed in at least one of a serializer and a deserializer, the system comprising:
- a genetic algorithm module configured to receive N operational parameters, each operational parameter including a plurality of coefficients and search an initial set of N coefficients on an N-dimensional performance surface, in accordance with a genetic algorithm, wherein the N-dimensional performance surface corresponds to various coefficients of the N operational parameters, wherein the genetic algorithm module further comprises:
- a random children selector configured to randomly select k sets of coefficients from the N operational parameters;
- an evolution module configured to select first top sets s1 of coefficients in accordance with a cost function and to evolve second sets s2 of coefficients in accordance with the first top set s1 of coefficients;
- a controlled mutation module configured to randomly select other sets of coefficients in a controlled random manner to provide a third sets s3 of coefficients wherein the third sets s3 of coefficients includes the first set of coefficients s1 and the second set of coefficients s2 and the other sets of coefficients;
- a random mutation module configured to randomly select fourth m sets s4 of coefficients from the N operational parameters;
- and
- a top children selector module configured to provide the initial set of N coefficients in accordance with the third sets s3 of coefficients and the fourth sets s4 of coefficients;
- and
- a gradient descent algorithm module configured to fine tune the initial set of N coefficients to provide the set of N optimal coefficients, in accordance with a gradient descent algorithm.
A non-transitory computer readable storage device on which is embedded computer software, the software comprising a program, the program performing a method for determining a set of N optimal coefficients to be supplied to an equalizer, the equalizer being employed in at least one of a serializer and a deserializer, the method comprising:
- receiving N different operational parameters, each parameter including a plurality of coefficients;
- searching an initial set of N coefficients on an N-dimensional performance surface, in accordance with a genetic algorithm, wherein the N-dimensional performance surface corresponds to various coefficients of the N operational parameters, wherein searching the initial set of N coefficients further comprises:
- randomly selecting k sets of coefficients from the N operational parameters;
- selecting first top sets s1 of coefficients from N operational parameters, in accordance with a cost function;
- evolving second sets s2 of coefficients in accordance with the first top sets s1 of coefficients;
- randomly selecting other sets of coefficients in a controlled random manner and providing third sets s3 of coefficients, wherein the third sets s3 of coefficients includes the first set of coefficients s1 and the second set of coefficients s2 and the other sets of coefficients;
- randomly selecting fourth m sets s4 of coefficients from the N operational parameters;
- and
- providing the initial set of N coefficients in accordance with the third sets s3 of coefficients and the fourth sets s4 of coefficients;
- and
- fine tuning the initial set of N coefficients to provide the set of N optimal coefficients, in accordance with a gradient descent algorithm.
A hybrid coefficient provider comprising:
- a genetic algorithm module configured to receive N operational parameters, each operational parameter including a plurality of coefficients, and search an initial set of N coefficients on an N-dimensional performance surface, in accordance with a genetic algorithm, wherein the N-dimensional performance surface corresponds to various coefficients of the N operational parameters, wherein the genetic algorithm module further comprises:
- a random children selector configured to randomly select k sets of coefficients from the N operational parameters;
- an evolution module configured to select first top sets s1 of coefficients in accordance with a cost function and to evolve second sets s2 of coefficients in accordance with the first top set s1 of coefficients;
- a controlled mutation module configured to randomly select other sets of coefficients in a controlled random manner to provide a third sets s3 of coefficients wherein the third sets s3 of coefficients includes the first set of coefficients s1 and the second set of coefficients s2 and the other sets of coefficients;
- a random mutation module configured to randomly select fourth m sets s4 of coefficients from the N operational parameters;
- and
- a top children selector module configured to provide the initial set of N coefficients in accordance with the third sets s3 of coefficients and the fourth sets s4 of coefficients;
- and
- a gradient descent algorithm module configured to fine tune the initial set of N coefficients to provide the set of N optimal coefficients, in accordance with a gradient descent algorithm.
Dependencies are inferred from the claim text.