A computer implemented method of handling threshold value of an antenna performance parameter of an antenna of a telecommunication network. A default antenna performance parameter threshold value of the antenna is obtained; a second antenna performance parameter threshold value for the antenna is determined based on the default antenna performance parameter threshold value and loss information related to the antenna, or based on gradually testing antenna performance parameter threshold values; and the second antenna performance parameter threshold value is taken into use for the antenna.

A test monitor extracts waveforms from a differential transmission line of an automobile network without disrupting the differential transmission line, and stores the data decoded from the extracted waveforms. The test monitor includes a first input configured to receive a voltage waveform from a voltage probe electrically coupled to the differential transmission line that electrically connects a first ECU device and a second device, a second input configured to receive a current waveform from a current probe electrically coupled to the differential transmission line, and one or more processors configured to receive the voltage waveform and the current waveform and determine a voltage of the first ECU device and a voltage of the second device based on the voltage waveform and the current waveform. The test monitor may be embodied in an FPGA. The test monitor enables monitoring of message transfers across a network in a non-intrusive and non-invasive manner, without the necessity of using a repeater or switch.

A test monitor extracts waveforms from a differential transmission line of an automobile network without disrupting the differential transmission line, and stores the data decoded from the extracted waveforms. The test monitor includes a first input configured to receive a voltage waveform from a voltage probe electrically coupled to the differential transmission line that electrically connects a first ECU device and a second device, a second input configured to receive a current waveform from a current probe electrically coupled to the differential transmission line, and one or more processors configured to receive the voltage waveform and the current waveform and determine a voltage of the first ECU device and a voltage of the second device based on the voltage waveform and the current waveform. The test monitor may be embodied in an FPGA. The test monitor enables monitoring of message transfers across a network in a non-intrusive and non-invasive manner, without the necessity of using a repeater or switch.

Artificial Intelligence (AI) can rapidly evaluate a faulted message in 5G or 6G, calculate a likelihood that each message element is faulted, and optionally suggest a most probable corrected version for each of the likely faulted message elements. To do so, the AI takes in numerous factors besides the message itself, such as the modulation quality of each message element, the proximity and quality of a nearest demodulation reference, a signal-to-noise ratio of the message element, a measure of current electromagnetic noise during the message element, an expected format or expected codewords based on prior messages or convention, and other factors. The AI model can then provide guidance as to mitigation, such as choosing whether to request a retransmission or attempting to vary the likely faulted message elements. The AI model can be adapted to fixed-site computers or to the more limited computers of a mobile user device.

Artificial Intelligence (AI) can rapidly evaluate a faulted message in 5G or 6G, calculate a likelihood that each message element is faulted, and optionally suggest a most probable corrected version for each of the likely faulted message elements. To do so, the AI takes in numerous factors besides the message itself, such as the modulation quality of each message element, the proximity and quality of a nearest demodulation reference, a signal-to-noise ratio of the message element, a measure of current electromagnetic noise during the message element, an expected format or expected codewords based on prior messages or convention, and other factors. The AI model can then provide guidance as to mitigation, such as choosing whether to request a retransmission or attempting to vary the likely faulted message elements. The AI model can be adapted to fixed-site computers or to the more limited computers of a mobile user device.

Certain aspects of the present disclosure provide techniques for ultra-reliable low latency communications (URLLC) indications with multi-physical downlink shared channel (PDSCH) and/or multi-physical uplink shared channel (PUSCH) grants. A method that may be performed by a user equipment (UE) includes receiving, from a network entity, downlink control information (DCI) scheduling a plurality of transmissions of a first priority, wherein the DCI comprises at least one field indicating one or more parameters to apply when at least one previously scheduled transmission of a second priority collides with: one or more of the plurality of transmissions of the first priority, or one or more transmissions acknowledging the one or more of the plurality of transmissions of the first priority; and applying the one or more parameters to process the plurality of the transmissions of the first priority.

Message faults are likely to be common in the noisy, high-density wireless environments planned for 5G and 6G. Disclosed is a method for a receiver to recover the correct message from one or more corrupted message copies, by (a) measuring the modulation quality of each message element, and (b) determining which message elements of two corrupted copies are “inconsistent”, that is, the corresponding message elements are different. The modulation quality can be determined according to how close the message element's modulation is to the predetermined modulation levels of the modulation scheme. The receiver can assemble a merged message by selecting whichever message elements of the two copies have the best modulation quality, and determine whether the merged message is still corrupted. If so, the receiver can sequentially replace the inconsistent message elements with those of the other copy, singly or in a comprehensive nested search, testing each version until successful.

Message faults are likely to be common in the noisy, high-density wireless environments planned for 5G and 6G. Disclosed is a method for a receiver to recover the correct message from one or more corrupted message copies, by (a) measuring the modulation quality of each message element, and (b) determining which message elements of two corrupted copies are “inconsistent”, that is, the corresponding message elements are different. The modulation quality can be determined according to how close the message element's modulation is to the predetermined modulation levels of the modulation scheme. The receiver can assemble a merged message by selecting whichever message elements of the two copies have the best modulation quality, and determine whether the merged message is still corrupted. If so, the receiver can sequentially replace the inconsistent message elements with those of the other copy, singly or in a comprehensive nested search, testing each version until successful.

A computer-implemented reconstruction method of discrete digital signal recovery in noisy overloaded wireless communication systems in the presence of hardware impairments that is characterized by a channel matrix of complex coefficients, the method including, receiving the signal from channel by a signal detector, estimation of hardware impairments parameter η is done at the receiver, estimation noise power is done by a noise power estimator, forwarding the detected signal and hardware impairments parameter η and noise power estimation to a decoder that estimates the transmitted symbol, wherein the estimation of the decoder produces a symbol that could probably have been transmitted it is forwarded to a de-mapper, which outputs the bit estimates corresponding to the estimated transmit signal and the corresponding estimated symbol to a microprocessor for further processing.

A computer-implemented reconstruction method of discrete digital signal recovery in noisy overloaded wireless communication systems in the presence of hardware impairments that is characterized by a channel matrix of complex coefficients, the method including, receiving the signal from channel by a signal detector, estimation of hardware impairments parameter η is done at the receiver, estimation noise power is done by a noise power estimator, forwarding the detected signal and hardware impairments parameter η and noise power estimation to a decoder that estimates the transmitted symbol, wherein the estimation of the decoder produces a symbol that could probably have been transmitted it is forwarded to a de-mapper, which outputs the bit estimates corresponding to the estimated transmit signal and the corresponding estimated symbol to a microprocessor for further processing.