Message faults are inevitable in the high-throughput environment of 5G and planned 6G. Retransmissions are costly in time and resources, while generating extra backgrounds and interference. Therefore, methods are disclosed for recovering a faulted message by identifying and correcting each mis-demodulated message element. The faulted message elements generally have substantially lower modulation quality than the correctly demodulated elements, and can be identified by determining the modulation quality of each received message element. If the number of faulted message elements is small, the receiver may correct them using a grid search tested by an associated error-detection code. If the number of faults exceeds a predetermined threshold, the receiver can request a retransmission, and then assemble a merged copy of the message by selecting the message element with the best modulation quality from each version. Substantial time and resources may be saved, and reliable communication may be restored despite poor reception.

In current practice, faulted messages are typically discarded and a retransmission is requested. Forward error-correction codes (FEC) in 5G and 6G are bulky, resource-expensive, and often unable to resolve the problem. Disclosed are systems and methods for determining which specific message elements are faulted, so that just the faulted portion can be retransmitted, instead of the entire message. For example, the amplitudes of the I and Q branches, of each message element, can be compared to the calibrated amplitude levels of the modulation scheme. Any message element with a large amplitude deviation is suspect. Other factors, such as the SNR, can also be considered in evaluating the validity of each message element. Usually, all of the faulted message elements occupy just a portion of the message. Compact formats are disclosed specifying which portion of the message is to be retransmitted, thereby saving time, power, and background generation.

A receiver includes an interface and a processor. The interface is configured to receive a signal including symbols carrying bit values in respective symbol intervals, and to convert the received signal into a serial sequence of digital samples, the received signal being modulated using a Differential Manchester Encoding (DME) scheme that (i) represents a first bit value by a first symbol type having a level transition in the corresponding symbol interval and (ii) represents a second bit value by a second symbol type having a constant level in the corresponding symbol interval. The processor is configured to derive an error signal from the digital samples, and to produce a quality measure of the received signal based on the derived error signal.

A method for sounding-interval adaptation using link quality for use in an apparatus is provided. The apparatus includes a sounding transceiver. The method includes the following steps: periodically transmitting a sounding packet to a beamformee through a downlink channel from the apparatus to the beamformee according to a first sounding interval; in response to the sounding transceiver receiving a data packet or a report packet from the beamformee, obtaining a current first channel profile from the received data packet or the received report packet; and adaptively adjusting the first sounding interval according to a first mobility indicator which is calculated according to the current first channel profile and the previous first channel profile.

A method for sounding-interval adaptation using link quality for use in an apparatus is provided. The apparatus includes a sounding transceiver. The method includes the following steps: periodically transmitting a sounding packet to a beamformee through a downlink channel from the apparatus to the beamformee according to a first sounding interval; in response to the sounding transceiver receiving a data packet or a report packet from the beamformee, obtaining a current first channel profile from the received data packet or the received report packet; and adaptively adjusting the first sounding interval according to a first mobility indicator which is calculated according to the current first channel profile and the previous first channel profile.

Message faults are inevitable in the high-throughput environment of 5G and planned 6G. Retransmissions are costly in time and resources, while generating extra backgrounds and interference. Therefore, methods are disclosed for recovering a faulted message by identifying and correcting each mis-demodulated message element. The faulted message elements generally have substantially lower modulation quality than the correctly demodulated elements, and can be identified by determining the modulation quality of each received message element. If the number of faulted message elements is small, the receiver may correct them using a grid search tested by an associated error-detection code. If the number of faults exceeds a predetermined threshold, the receiver can request a retransmission, and then assemble a merged copy of the message by selecting the message element with the best modulation quality from each version. Substantial time and resources may be saved, and reliable communication may be restored despite poor reception.

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.

Message faults are an increasing problem for 5G and expected 6G networks, due to growth, crowding, and signal fading problems. Disclosed are procedures for determining which particular message element of a corrupted message is faulted, and optionally the most likely correction. A receiver can identify the faulted message element by measuring the fluctuations, in phase and amplitude, of the waveform of each message element, as well as the modulation quality, frequency offset, and other signal measurements. Faulted message elements are likely to have higher fluctuations, higher modulation deviations, and higher signal irregularities, than the unfaulted ones. Mitigation can then be applied to the faulted message elements, thereby recovering the correct message and avoiding a costly retransmission delay. AI models may enhance the fault detection sensitivity by exploiting correlations between the various waveform measurement parameters, and then may predict the corrected value of the faulted message elements.

A major goal of 5G and especially 6G is reliable, low-latency communication. Unfortunately, higher density networks result in increasing interference, and higher frequency bands inevitably have signal fading problems, leading to frequency message faults. To restore high-speed, high-reliability messaging, methods are disclosed for evaluating the signal quality of each message element of a received message so that any faulting can be localized to the message elements with the lowest signal quality. Numerous contributions to signal quality are disclosed, including modulation, amplitude and phase stability, polarization and inter-symbol irregularities, expected message format and meaning, and common or unexpected bit sequences. Many further aspects are included.

A receiver can determine that a received message is corrupt according to an associated error-detection code in 5G/6G. The receiver can then calculate the modulation quality of each message element of the message by comparing a modulation value of the message element with a set of predetermined modulation levels, wherein a larger deviation from the closest predetermined modulation level corresponds to a lower modulation quality. Noise and interference usually generate random changes in the modulation as-received, and this generally results in a larger deviation relative to the predetermined modulation levels and hence a lower modulation quality. The receiver can count the number of faulted message elements with modulation quality below a threshold, and if the number of faults is less than some limit, the receiver can attempt to recover the message by altering the worst-quality message elements, testing each version for consistency.