A semiconductor device is provided. The semiconductor device includes a processing device that provides resource usage information including a utilization value; and a prediction information generating device that generates resource usage prediction information based on the resource usage information and provides the resource usage prediction information to the processing device. The prediction information generating device includes: an error calculator to calculate an error value between the utilization value and a predicted value included in the resource usage prediction information; a margin value calculator to receive the error value from the error calculator and calculate a margin value using the error value; an anchor value calculator to calculate an anchor value using the utilization value; and a predictor to output the predicted value using the anchor value and the margin value. The processing device controls resource allocation of the processing device based on the resource usage prediction information.

Aspects described herein relate to on-demand soft acknowledgement (ACK)/negative acknowledgement (NACK) in radio access and other wireless networks, such as fifth generation new radio (5G NR), 3GPP Long Term Evolution (LTE), 3GPP LTE-Advanced (LTE-A), Wi-Fi, and the like. In an example, the aspects may include receiving, from a network entity, a request to enable soft ACK/NACK feedback; enabling the soft ACK/NACK feedback based on the request, where the soft ACK/NACK feedback comprises at least a link quality metric per diversity branch; and transmitting, to the network entity, the soft ACK/NACK feedback based on a determination to enable the soft ACK/NACK feedback.

An apparatus and method are provided for using an MLP algorithm to map channel features to an RI and/or a CQI for CSI feedback. The method includes estimating a channel in the communication network for a signal; extracting at least one channel feature related to the estimated channel; determining RI and CQI pairs; inputting, to an MLP network, the extracted at least one channel feature and the RI and CQI pairs; receiving, for each of the RI and CQI pairs, an output of the MLP network, wherein the outputs of the MLP network indicate throughput or spectral efficiency for the electronic device; and selecting an RI and CQI pair of the RI and CQI pairs based on the received outputs.

An apparatus and method are provided for using an MLP algorithm to map channel features to an RI and/or a CQI for CSI feedback. The method includes estimating a channel in the communication network for a signal; extracting at least one channel feature related to the estimated channel; determining RI and CQI pairs; inputting, to an MLP network, the extracted at least one channel feature and the RI and CQI pairs; receiving, for each of the RI and CQI pairs, an output of the MLP network, wherein the outputs of the MLP network indicate throughput or spectral efficiency for the electronic device; and selecting an RI and CQI pair of the RI and CQI pairs based on the received outputs.

There are provided a data comparison unit that detects an FEC symbol error of a signal under test output from a DUT in accordance with an input of a jitter signal, an error counting unit that counts the number of detected FEC symbol errors for each codeword for each phase modulation amount, a codeword classification unit that classifies a plurality of codewords included in the signal under test into a plurality of groups based on the counted number of FEC symbol errors, a codeword number counting unit that counts the number of codewords in each group for each phase modulation amount, and a display control unit that controls a display of a first graph having a horizontal axis as the phase modulation amount and a vertical axis as a ratio of the number of codewords in each group, on a display screen.

A method, system and apparatus are disclosed. A network node configured to communicate with a wireless device (WD) is provided. The network node is configured to, and/or comprising a radio interface and/or comprising processing circuitry configured to: determine a radio link monitoring (RLM) state of a wireless device that is served by a first cell and configured to operate with at least a first operational mode and a second operation mode within an overlapping time, and schedule at least one signal associated with the wireless device based on the RLM state.

Intelligent hybrid automatic repeat request (HARQ) feedback can better support link adaption. Thus, in addition to the traditional HARQ feedback, which is to relay acknowledgement (ACK) and negative acknowledgement (NAK) data based on a decoding result, a new state for the HARQ feedback can be represented as “ACK+”. Consequently, ACK+ can be used to indicate to the network that a modulation and coding scheme (MCS) of a current data packet is too conservative, and the user equipment (UE) is capable of supporting a more aggressive MCS.

A method includes: receiving, at a first layer of a protocol stack, multiple code blocks from a base station, the multiple code blocks is a portion of a transport block and is associated with an error rate; transmitting, to a second layer of the protocol stack, the multiple code blocks; and determining, at the second layer and based on the error rate, whether to (1) store the multiple code blocks in memory or (2) process the multiple code blocks. A method for saving power in a physical (PHY) layer-to-medium access (MAC) layer interface and a network device, and a system are also provided.

A method includes: receiving, at a first layer of a protocol stack, multiple code blocks from a base station, the multiple code blocks is a portion of a transport block and is associated with an error rate; transmitting, to a second layer of the protocol stack, the multiple code blocks; and determining, at the second layer and based on the error rate, whether to (1) store the multiple code blocks in memory or (2) process the multiple code blocks. A method for saving power in a physical (PHY) layer-to-medium access (MAC) layer interface and a network device, and a system are also provided.

A faulted message element in 5G or 6G can often be identified according to its modulation parameters, including a large deviation of the branch amplitudes from the predetermined amplitude levels of the modulation scheme, and/or the SNR of the branch amplitudes, and/or an amplitude variation of the raw signal or the branches during the message element, and/or an inconsistency between the modulation state as determined by the amplitude and phase of the raw waveform versus the amplitudes of the orthogonal branch signals, among other measures of modulation quality. An AI model may be necessary to correlate the various quality measures, and optionally to determine the correct demodulation of faulted message elements. Costly, time-consuming retransmissions may be avoided by determining the correct demodulation of each message element at the receiver, thereby improving throughput and reliability with fewer delays.