Abstract:
A method and an arrangement for quality estimation when detecting an information frame, for instance a speech frame transmitted in a radio communication system in accordance with time division multiple access (TDMA), although the method can also be applied with frequency divided radio systems. There is used the soft information available in the radio receiver which is intended to detect the speech frame and process this signal information in accordance with those principles applicable to known neural nets. Prior to use, the neural net is aligned to the radio communication system concerned. The invention enables better information relating to possible error in the speech frame to be delivered to error correcting units in the radio receiver.
Abstract:
Methods, systems, and devices for wireless communications are described herein. A user equipment (UE) may generate a set of feedback bits corresponding to sidelink messages received via one or more sidelink channels. The UE may transmit a first sidelink message via a first feedback resource of a physical sidelink feedback channel occasion. The first sidelink message may include a first subset of the feedback bits. The UE may transmit at least two additional sidelink feedback messages via respective feedback resources. The first additional sidelink feedback message may include the first subset of feedback bits and a second subset of feedback bits encoded using an erasure coding function.
Abstract:
A classification apparatus includes a memory and a processor. The memory is configured to store rules corresponding to a corpus of rules in respective rule entries, each rule includes a respective set of unmasked bits having corresponding bit values, and at least some of the rules include masked bits. The rules in the corpus conform to respective Rule Patterns (RPs), each RP defining a respective sequence of masked and unmasked bits. The processor is configured to cluster the RPs, using a clustering criterion, into extended Rule Patterns (eRPs) associated with respective hash tables including buckets for storing rule entries. The clustering criterion aims to minimize an overall number of the eRPs while meeting a collision condition that depends on a specified maximal number of rule entries per bucket.
Abstract:
Message faulting is an increasing problem in 5G and future 6G due to network crowding, receiver motion, signal fading at higher frequencies, and greater phase-noise sensitivity. Disclosed herein are methods for analyzing waveform features of the received signal using artificial intelligence, and identifying the likely faulted message elements according to correlations of those waveform features. For example, after demodulating, the receiver can identify a subset of message elements that are all demodulated according to the same modulation level, and can measure a signal parameter for each message element in the subset. The processor can then average the deviations in the subset, and compare those message elements to the average for the subset. If one of the message elements shows an anomalously large deviation from the average, that message element is likely faulted.
Abstract:
AI-based fault detection, localization, and correction can improve message reliability in 5G and 6G communications by enabling the rapid recovery of faulted messages without wasting precious time and power on an unnecessary retransmission. The waveform of a received message is rich with information implicating the faulted message elements and, in many cases, suggesting the corrected value. In examples, message recovery can be based on the amplitude of the received waveform, its phase, any pathological variations in noise or in frequency or in polarization, and on inter-symbol transition regions, to list just a few waveform fault indicators revealing the fault locations. In addition, the AI model, or an algorithm derived from it, can discern the intent or meaning of a message, as well as its form and format, the bitwise content, the sequence of characters, and other error flags indicating which parts of the message are faulted.
Abstract:
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.
Abstract:
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.
Abstract:
A central challenge in next-generation 5G/6G networks is achieving high message reliability despite very dense usage and unavoidable signal fading at high frequencies. To provide enhanced fault detection, localization, and mitigation, the disclosed procedures can enable an AI model (or an algorithm derived from it) to discriminate between faulted and unfaulted message elements according to signal quality, modulation parameters, and other inputs. The AI model can estimate the likelihood that each message element is faulted, and predict the most probable corrected value, among other outputs. The AI model can also consider the quality of a demodulation reference used to demodulate the message, and the quality of the associated error-detection code. The AI model can also consider previously received messages to the same receiver, or messages of a similar type. Fault mitigation by the receiver can save substantial time and resources by avoiding a retransmission. Many other aspects are disclosed.
Abstract:
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.
Abstract:
An apparatus for handling an incoming communication data frame containing a plurality of bits is provided. The apparatus may include a plurality of data matchers, each data matcher configured to compare a subset of the plurality of bits of the communication data frame with a predetermined data pattern of a plurality of data patterns and to provide a data matcher output to indicate the result of the data matcher comparison, a plurality of selectors, each selector configured to compare a subset of the data matcher outputs of the plurality of data matchers with a predetermined selection pattern of a plurality of selection patterns and to provide a selector output to indicate the result of the selector comparison, and a frame filter configured to transfer the incoming frame to application logic only if the selector outputs of the plurality of selectors match a predetermined filter pattern, and to also transfer the selector outputs of the plurality of selectors to the application logic.