Samsung Electronics Co., Ltd.

Hyunsang Cho

Inyup Kang

Mostafa El-Khamy

Hongrak Son

Arvind Yedla

Sang-Hyuck Ha

Seonghyeog Choi

Jiyoup Kim

Youngsik Moon

Hanbyeul Na

Taehyun Song

SangHyuck Ha

A device for supporting a homomorphic encryption operation includes a ciphertext conversion circuit configured to convert first ciphertexts corresponding to a first operation size to second ciphertexts corresponding to a second operation size, different from the first operation size, to convert the operated ciphertext having the second operation size to a third ciphertexts corresponding to the first operation size, and to perform a homomorphic encryption operation on the second ciphertexts.

Device for supporting homomorphic encryption operation and operating method thereof

Apparatuses (including user equipment (UE) and modern chips for UEs), systems, and methods for UE downlink Hybrid Automatic Repeat reQuest (HARQ) buffer memory management are described. In one method, the entire UE DL HARQ buffer memory space is pre-partitioned according to the number and capacities of the UE's active carrier components. In another method, the UE DL HARQ buffer is split between on-chip and off-chip memory so that each partition and sub-partition is allocated between the on-chip and off-chip memories in accordance with an optimum ratio.

Method and system for contiguous HARQ memory management with memory splitting

According to a method of controlling an operation of a nonvolatile memory device using machine learning, operating conditions of the nonvolatile memory device are determined by performing an inferring operation using a machine learning model. Training data that are generated based on feature information and error information are collected, where the error information indicate results of error correction code (ECC) decoding of the nonvolatile memory device. The machine learning model is updated by performing a learning operation based on the training data. Optimized operating conditions for individual user environments are provided by collecting training data in the storage system and performing the learning operation and the inferring operation based on the training data.

Method of controlling operation of nonvolatile memory device using machine learning and storage system

Apparatuses (including user equipment (UE) and modem chips for UEs), systems, and methods for UE downlink Hybrid Automatic Repeat reQuest (HARQ) buffer memory management are described. In one method, the entire UE DL HARQ buffer memory space is pre-partitioned according to the number and capacities of the UE's active carrier components. In another method, the UE DL HARQ buffer is split between on-chip and off-chip memory so that each partition and sub-partition is allocated between the on-chip and off-chip memories in accordance with an optimum ratio.

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Hwaseong-si, South Korea

Hyunsang Cho