Abstract:
A method and apparatus for supervising a dedicated control channel when in the discontinuous transmission mode. The mobile station (4) receives a pilot strength measurement for each pilot signal contained in an active set of base stations and an aggregate of the pilot strength measurements is determined. An average for the aggregate is determined over a selected time interval and the remote station transmitter is disabled if said average is below a threshold for a designated time (T1). The received transmission may be deemed terminated if the average is below the threshold for a second designated time (T2), where T2 > T1.
Abstract:
A method of identifying a bad frame in a digital data decoder comprising implementation, in combination with parity checks, of a plurality of operations upon a set of values obtained from measurements of received frames, setting predetermined pass conditions for each operation and indicating a bad frame if at least one of said operations results in a pass condition.
Abstract:
An error detecting device for received digital data is provided which solves a problem of a conventional device in that error detection following the Viterbi decoding performed on most important bits cannot detect all errors if they include a considerable amount of errors. The present error detecting device includes a Viterbi decoder (4) for carrying out the Viterbi decoding of the received digital data, an error number decision portion (5) for comparing a threshold value with the number of errors of the path metric obtained by the Viterbi decoding, and a voice decoder (6) for decoding the received digital data, on which the error number decision portion (5) decides that the number of errors is below the threshold value.
Abstract:
An improved error detection and error concealment for Viterbi decoding of convolutionally encoded data is provided. The most sensitive part of the data is parity encoded and sent with parity and this data with the next most sensitive data are convolutionally encoded and sent with the least sensitive data over a transmission channel to a receiver. At the receiver the convolutionally encoded data is decoded using the Viterbi algorithm. The decoder compares the parity computed from decoded data with the decoded parity and if they are not equal generates a Bad Frame Indicator (BFI) flag and also determines which decoded parameters are likely bad and hence generates a Bad Parameter Indicator (BPI) flag for those parameters, by determining the confidence levels for the parameters and comparing against pre-selected thresholds. The decision to discard a decoded parameter is dependent on the BFI flag and the BPI flag of that parameter.
Abstract:
A method of insuring the accuracy of transmitted or stored digital data involves the use of a cyclical redundancy check (CRC) code. The method is particularly useful for ensuring the accuracy of frames transmitted between multi-mode vocoders. The method allows a different CRC code to be used for each mode of a transmitting multi-mode vocoder. A receiving multi-mode vocoder checks the CRC code against the CRC coding formulas of the various modes. If the CRC code is satisfied under any one of the modes, the frame is labeled as "good". If the CRC code fails under all the modes, the frame is labeled as "bad". If the bit frame includes bits for indicating the mode of the transmitting multi-mode vocoder, the receiving multi-mode vocoder checks the CRC code against the CRC coding formula for the indicated mode only. If the CRC code passes for the indicated mode, the frame is labeled as "good", otherwise, the frame is labeled as "bad".
Abstract:
A communication system implements detection of bad frames of information by utilizing multiple bit correction thresholds. Equipment used within the communication system adapts to different signaling environments by dynamically altering the bit correction threshold based on a history of the number of consecutive bad frames of information that have been previously erased and the number of bits corrected by a channel decoder (202). By implementing this dynamic bit correction threshold, sufficent bad frame indication (BFI) detection and receiver sensitivity can be obtained simultaneously, which results in an improved perceived audio quality to the end user.
Abstract:
In 5G-Advanced, and especially 6G, message faulting is expected to be a major impediment due to phase noise and increased pathloss attenuation, as well as network crowding. Therefore, new procedures are disclosed enabling the receiver to identify and correct message faults without a retransmission and without using bulky FEC (forward error correction) bits. For example, the receiver can measure the “distance” of each received message element from the nearest modulation state, and thereby quantify the modulation quality, or suspiciousness, of each message element. To correct the message, the worst-modulated ones can be altered first, generally selecting the next-closest states since small distortions are more likely than large distortions. The result: rapid message recovery, internal to the receiver processor, without adding to the message size or the latency.
Abstract:
In 5G-Advanced and especially 6G, a primary concern is the increase in message faulting due to higher pathloss and phase noise at FR2 frequencies. Current methods for dealing with faults include packing the message with bulky error-correction (FEC) bits which are often ineffective, or automatically requesting a costly retransmission. As a substantially better alternative, the receiver may identify the specific fault locations and attempt an immediate repair by testing the modulation quality of each message element. For example, for a QAM-modulated message, the receiver can measure the I and Q branch deviations relative to predetermined levels, and the message element(s) with largest deviations is/are likely faulted. Alternatively, if the message is advantageously modulated according to the waveform amplitude and phase, the receiver can determine the amplitude and phase deviations relative to predetermined values. An AI model can greatly assist in the fault localization and in finding the corrected values.
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:
Corrupted messages in 5G and 6G are usually discarded, leading to a retransmission with its added costs, delays, and background generation. Therefore, disclosed herein are methods for a wireless receiver to determine which message elements are faulted, and in many cases to correct them, based on parameters of the waveform signal in each message element. Multiple parameters may be combined for better sensitivity to the fault condition. For example, the indicator parameters may be the modulation deviation of each message element, its amplitude or phase noise level, characteristic interference patterns between symbol-times, a polarization anomaly, a frequency offset, or combinations of these. After localizing the likely faulted message elements, the receiver may be able to recover the message by correcting the waveform signal or the demodulation value, thereby saving time and energy at near zero cost.