This application provides a wireless communication method and a communication apparatus. The method includes a terminal device receives a data frame from a second device by using a first device, and notifies the first device when the terminal device determines that a communication data block from the first device is not successfully received. After determining a protocol data packet corresponding to the communication data block, the first device notifies the second device that the first protocol data packet is not successfully transmitted. After determining a data unit that is in the data frame and that corresponds to the communication data block, the terminal device notifies the second device through second-step feedback.

A system processing hard e executes a machine learning (ML) model-based video compression encoder to receive uncompressed video content and corresponding motion compensated video content, compare the uncompressed and motion compensated video content to identify an image space residual, transform the image space residual to a latent space representation of the uncompressed video content, and transform, using a trained image compression ML model, the motion compensated video content to a latent space representation of the motion compensated video content. The ML model-based video compression encoder further encodes the latent space representation of the image space residual to produce an encoded latent residual, encodes, using the trained image compression ML model, the latent space representation of the motion compensated video content to produce an encoded latent video content, and generates, using the encoded latent residual and the encoded latent video content, a compressed video content corresponding to the uncompressed video content.

A system processing hard e executes a machine learning (ML) model-based video compression encoder to receive uncompressed video content and corresponding motion compensated video content, compare the uncompressed and motion compensated video content to identify an image space residual, transform the image space residual to a latent space representation of the uncompressed video content, and transform, using a trained image compression ML model, the motion compensated video content to a latent space representation of the motion compensated video content. The ML model-based video compression encoder further encodes the latent space representation of the image space residual to produce an encoded latent residual, encodes, using the trained image compression ML model, the latent space representation of the motion compensated video content to produce an encoded latent video content, and generates, using the encoded latent residual and the encoded latent video content, a compressed video content corresponding to the uncompressed video content.

A signaling of at least one characteristic for layers of a multi-layered video signal such as, for example, for each layer the indication of dependent layers to which the respective layer directly relates via inter-layer prediction, or the signaling of the afore-mentioned second inter-dependency syntax structure, is described. A maximum syntax element is signaled within the multi-layered video signal to indicate a maximally used value of an extension layer-ID field of the packets of the multi-layered video signal, the scope of the maximum syntax element being, for example, a predetermined portion of the multi-layered video signal extending, for example, across several portions of the multi-layered video signal. Accordingly, it is feasible for devices such as decoders or network elements receiving the multi-layered video signal to gain, for a relatively large predetermined portion of the multi-layered video signal, knowledge about the actually consumed portion of the possible domain of possible values.

A signaling of at least one characteristic for layers of a multi-layered video signal such as, for example, for each layer the indication of dependent layers to which the respective layer directly relates via inter-layer prediction, or the signaling of the afore-mentioned second inter-dependency syntax structure, is described. A maximum syntax element is signaled within the multi-layered video signal to indicate a maximally used value of an extension layer-ID field of the packets of the multi-layered video signal, the scope of the maximum syntax element being, for example, a predetermined portion of the multi-layered video signal extending, for example, across several portions of the multi-layered video signal. Accordingly, it is feasible for devices such as decoders or network elements receiving the multi-layered video signal to gain, for a relatively large predetermined portion of the multi-layered video signal, knowledge about the actually consumed portion of the possible domain of possible values.

A method of performing a rate-distortion optimization process comprising selecting a preferred encoding mode by optimizing a function comprising an estimate of distortion for a target image portion and a measure of bit rate required to encode that portion. The estimate of distortion is based on source coding distortion and an estimate of error propagation distortion due to loss. The method further comprises transmitting the same encoded version of the video stream from the transmitting terminal to each of a plurality of receiving terminals over respective lossy channels, using the same rate-distortion optimization process in relation to each of the plurality of receiving terminals, making the same encoding mode selection per target image portion based on the same optimization of said function. The estimate of error propagation distortion comprises an aggregate estimate of error propagation distortion that would be experienced due to possible loss over the plurality of channels.

A method of performing a rate-distortion optimization process comprising selecting a preferred encoding mode by optimizing a function comprising an estimate of distortion for a target image portion and a measure of bit rate required to encode that portion. The estimate of distortion is based on source coding distortion and an estimate of error propagation distortion due to loss. The method further comprises transmitting the same encoded version of the video stream from the transmitting terminal to each of a plurality of receiving terminals over respective lossy channels, using the same rate-distortion optimization process in relation to each of the plurality of receiving terminals, making the same encoding mode selection per target image portion based on the same optimization of said function. The estimate of error propagation distortion comprises an aggregate estimate of error propagation distortion that would be experienced due to possible loss over the plurality of channels.

An apparatuses for radio access network configuration for video approximate semantic communications includes a transceiver that receives from a transmitter a bitstream corresponding to a video coded data transmission wherein the received bitstream includes bitwise transmission errors and a processor that performs FEC decoding and correcting at least one bitwise transmission error of the video coded data transmission whereas at least one bitwise transmission error is left in a bit-inexact reception of the video coded data transmissions post FEC decoding, applies, by a smart video decoder in a video approximate semantic communications mode, semantic error correction to decoded video coded data transmissions to correct and conceal one or more video artifacts in response to the bit-inexact reception of the video coded data transmissions post FEC decoding, and reconstructs a video uncoded representation of concealed approximate semantic content relative to the received bitstream corresponding to the video coded data transmission.

An apparatuses for radio access network configuration for video approximate semantic communications includes a transceiver that receives from a transmitter a bitstream corresponding to a video coded data transmission wherein the received bitstream includes bitwise transmission errors and a processor that performs FEC decoding and correcting at least one bitwise transmission error of the video coded data transmission whereas at least one bitwise transmission error is left in a bit-inexact reception of the video coded data transmissions post FEC decoding, applies, by a smart video decoder in a video approximate semantic communications mode, semantic error correction to decoded video coded data transmissions to correct and conceal one or more video artifacts in response to the bit-inexact reception of the video coded data transmissions post FEC decoding, and reconstructs a video uncoded representation of concealed approximate semantic content relative to the received bitstream corresponding to the video coded data transmission.

Apparatuses, methods, and systems are disclosed for video codec aware RAN configuration and unequal error protection coding. An apparatus includes a processor that detects a video coded traffic stream and a video codec specification used to encode the video coded traffic stream, determines an awareness of video coded traffic application data units (“ADUs”) of the video coded traffic stream as video coded network abstraction layer (“NAL”) units of data, aligns the video coded NAL units of the video coded traffic stream to physical layer (“PHY”) transport elements and subsequent channel coding element partitions for a video coded traffic aware PHY transport, determines a channel coding rate allocation of the channel coding element partitions, and applies a forward error correction (“FEC”) coding given at least the determined channel coding rate allocation of the video coded traffic aware PHY transport to channel coding element partitions for protection against radio transmission errors.