# US 12,758,870 B2 · Methods and apparatuses for signaling enhancement in wireless communications > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,758,870 B2 - Document ID: US12758870B2 - Status: Granted - Kind: B2 - Application number: 18/292,375 - Filed: 2022-08-04 - Published: 2024-10-03 - Granted: 2026-10-13 - Earliest claimed: 2021-08-06 - Assignees: InterDigital Patent Holdings, Inc. - Applicants: InterDigital Patent Holdings, Inc. - Inventors: Renan Krishna; Chonggang Wang; Xavier De Foy; Shamim Rahman - Web page: https://patentgrep.com/patent/US12758870B2 ## CPC - A63F 13/352: involving special game server arrangements, e.g. regional servers connected to a national server or a plurality of servers managing partitions of the game world - A63F: CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR ## Abstract Methods and apparatuses for signaling enhancement to meet low-latency requirements of cloud gaming applications in wireless communication networks are provided. In an example, a method implemented by a wireless transmit/receive unit (WTRU) includes transmitting a first message including neural network data and information indicating a first type of neural network data, the neural network data were marshaled into one or more byte arrays before transmission; receiving a first acknowledgement message indicating a second type of neural network data that an Edge device has received; receiving a second message including marshaled data based on the transmitted neural network data and the information; and transmitting a second acknowledgement message indicating a third type of neural network data that the WTRU has received. ## Claims ### Claim 1 A method implemented by a wireless transmit/receive unit (WTRU) for wireless communications, the method comprising: selecting, based at least in part on telemetry data for a wireless path between the WTRU and an Edge device, one of a plurality of rendering-and-prediction procedures for an XR or cloud-gaming session; transmitting, to the Edge device, a first message including prediction values associated with a neural network and information indicating a type of the prediction values associated with the neural network, wherein the prediction values represent predicted game-world changes or predicted user-view changes for rendering one or more video frames of the XR or cloud-gaming session, the prediction values having been marshaled into one or more byte arrays before transmission; receiving, from the Edge device, a first acknowledgement message indicating the type of the prediction values associated with the neural network that the Edge device has received; receiving, from the Edge device, a second message including video data based on the prediction values and the type of the prediction values; and transmitting, to the Edge device, a second acknowledgement message indicating that the video data was received. ### Claim 2 (depends on 1) The method of claim 1, further comprising receiving a third message including a different type of prediction values associated with the neural network. ### Claim 3 (depends on 1) The method of claim 1, further comprising: unmarshalling the video data received in the second message; and decoding the unmarshalled video data. ### Claim 4 (depends on 1) The method of claim 1, wherein the second message comprises one or more parameters indicating the type of the prediction values. ### Claim 5 (depends on 4) The method of claim 4, wherein the one or more parameters are selected by a decision policy. ### Claim 6 (depends on 4) The method of claim 4, wherein the one or more parameters are received as a byte array. ### Claim 7 (depends on 1) The method of claim 1, wherein the type of the prediction values associated with the neural network comprises a point estimate or a probability distribution for the predicted game-world changes or the predicted user-view changes. ### Claim 8 (depends on 2) The method of claim 2, wherein the different type of prediction values associated with the neural network comprises a point estimate or a probability distribution and is different from the type of the prediction values associated with the neural network. ### Claim 9 (depends on 1) The method of claim 1, further comprising: determining a first set of procedures performed by the WTRU; transmitting an acknowledgement in response to the determined first set of procedures; and executing a second set of procedures in response to the determined first set of procedures, wherein any of the first set of procedures or the second set of procedures are provided by a server interaction module. ### Claim 10 (depends on 1) The method of claim 1, further comprising selecting one or more following procedures: (1) using low-quality video rendering and low-quality prediction; (2) using low-quality video rendering and high-quality prediction; (3) using low-quality prediction and high-quality video rendering; or (4) using high-quality video rendering and high-quality prediction. ### Claim 11 A wireless transmit/receive unit (WTRU) comprising circuitry, including a processor, a transmitter, a receiver, and memory, the WTRU configured to: select, based at least in part on telemetry data for a wireless path between the WTRU and an Edge device, one of a plurality of rendering-and-prediction procedures for an XR or cloud-gaming session; transmit to the Edge device a first message including prediction values associated with a neural network and information indicating a type of the prediction values associated with the neural network, wherein the prediction values represent predicted game-world changes or predicted user-view changes for rendering one or more video frames of the XR or cloud-gaming session, the prediction values having been marshaled into one or more byte arrays before transmission; receive a first acknowledgement message indicating the type of the prediction values associated with the neural network that an Edge device has received; receive a second message including video data based on the prediction values and the type of the prediction values; and transmit a second acknowledgement message indicating that the video data was received. ### Claim 12 (depends on 11) The WTRU of claim 11, wherein the WTRU is further configured to receive a third message including a different type of prediction values associated with the neural network. ### Claim 13 (depends on 11) The WTRU of claim 11, wherein the WTRU is further configured to: unmarshall the video data received in the second message; and decode the unmarshalled video data. ### Claim 14 (depends on 11) The WTRU of claim 11, wherein the second message comprises one or more parameters indicating the type of the prediction values. ### Claim 15 (depends on 14) The WTRU of claim 14, wherein the one or more parameters are selected by a decision policy. ### Claim 16 (depends on 14) The WTRU of claim 14, wherein the one or more parameters are received as a byte array. ### Claim 17 (depends on 11) The WTRU of claim 11, wherein the type of the prediction values associated with the neural network comprises a point estimate or a probability distribution for the predicted game-world changes or the predicted user-view changes. ### Claim 18 (depends on 12) The WTRU of claim 12, wherein the different type of prediction values associated with the neural network comprises a point estimate or a probability distribution and is different from the type of the prediction values associated with the neural network. ### Claim 19 (depends on 11) The WTRU of claim 11, wherein the WTRU is further configured to: determine a first set of procedures performed by the WTRU; transmit an acknowledgement in response to the determined first set of procedures; and execute a second set of procedures in response to the determined first set of procedures, wherein any of the first set of procedures or the second set of procedures are provided by a server interaction module. ### Claim 20 (depends on 11) The WTRU of claim 11, wherein the WTRU is further configured to select one or more following procedures: (1) using low-quality video rendering and low-quality prediction; (2) using low-quality video rendering and high-quality prediction; (3) using low-quality prediction and high-quality video rendering; or (4) using high-quality video rendering and high-quality prediction.