Active User Detection and Channel Estimation Method and Device, Using Deep Neural Network
AssigneeSeoul National University R&Db Foundation
InventorsByonghyo Shim, Yongjun Ahn
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Abstract
Provided is an active user detection and channel estimation method of a base station in a wireless communication system based on grant-free uplink transmission. The method, according to one embodiment, comprises the steps of: receiving superimposed signals () from k active terminals; by using a first artificial neural network and using the received signals () as input, calculating, for all terminals in a cell of a base station, an estimated probability ({circumflex over (Ω)}) of each of the terminals being an active terminal; and estimating channels of the active terminals by using a second artificial neural network and using the received signals () and an active user detection result value as input.
Claims12
An active terminal detection and channel estimation method of abase station in a wireless communication system based on grant-free uplink transmission, the method comprising:
- receiving superimposed signals () from k active terminals;
- calculating, using a first artificial neural network and using the received signals () as input, an estimated probability ({circumflex over (Ω)}) that each of all terminals in a cell of the base station is an active terminal;
- and
- estimating channels of the active terminals using a second artificial neural network with the received signals () and an active terminal detection result value as input.
Abase station device for an active user detection and channel estimation in a wireless communication system based on grant-free uplink transmission, the base station device comprising:
- a receiver configured to receive superimposed signals () from k active terminals;
- and
- one or more processors configured to control an operation of the receiver,
- wherein the one or more processors:
- calculates, using a first artificial neural network and using the received signals () as input, an estimated probability ({circumflex over (Ω)}) that each of all terminals in a cell of the base station is an active terminal;
- and
- estimates channels of the active terminals using a second artificial neural network with the received signal () and an active user detection result value as input.
Dependencies are inferred from the claim text.