System for adjusting a reference constellation for demodulating an optical signal include a coherent electro-optical receiver configured to convert a received optical signal to a plurality of electrical signals, an array of analog-to-digital convertors configured to digitize the plurality of electrical signals, and processor logic. The processor logic is configured to process the digitized plurality of electrical signals using a reference constellation to yield a plurality of decoded signals and a signal quality measurement. The reference constellation includes an inphase component equal to an ideal inphase component plus an inphase offset and a quadrature component equal to an ideal quadrature component plus a quadrature offset. The processor logic is configured to determine an optimal inphase offset and optimal quadrature offset. The processor logic is configured to update the reference constellation using the optimal inphase offset and the optimal quadrature offset.

A communications device configured to receive data transmitted as encoded data packets from an infrastructure equipment of a wireless communications network. Each of the encoded data packets are transmitted as a control signal component and a data signal component. The control signal component carries control information for detecting and decoding the data signal component in which the encoded data carried by the encoded data packet is transmitted. As part of the ARQ-type protocol, at least the control signal component may be re-transmitted. By including with the control information carried by the retransmitted control signals an indication of at least a temporal location of the data signal component, which has already been transmitted and received in a buffer of a receiver, an improvement in a use of communications resource can be provided and also in some embodiments an improvement in a likelihood of correctly detecting and decoding an encoded data packet.

A bandwidth allocation and monitoring method may divide available bandwidth on a shared communication medium into a plurality of discrete tones that can be individually allocated to modems on an as-needed basis. The effective modulation rate that a particular modem can use for each discrete tone can be monitored over time using a schedule of pilot tones transmitted from the modems on different tones at different times. The schedule may define representative pilot tones, in which case effective modulation rates for neighboring tones may be inferred from a determined effective modulation rate of a pilot tone.

This invention presents methods for estimating the uplink SINR and channel estimation error level in MU-MIMO wireless communication systems comprising the BS obtaining the channel coefficients between each receiving antenna of a BS and a transmitting antenna of a UE in the uplink; for the BS estimating the SU-MIMO SINR of a UE using the channel coefficients between a UE and the BS; for the BS estimating the channel estimation error level of a UE using the channel coefficients between a UE and the BS.

Different solutions for an apparatus comprising a predictor predicting decodability of received symbols are disclosed. Decoding is performed based on the prediction.

The present disclosure provides a method for transmitting and receiving in a wireless communication system and an apparatus therefore. Specifically, in a wireless communication system according to an embodiment of the present disclosure, there is provided a method for transmitting and receiving a signal by a receiving apparatus, the method includes receiving, from a transmitting apparatus, signals modulated based on a differential phase shift keying (DPSK) method through a plurality of reception paths, calculating a differential value in each reception path of the plurality of reception paths based on the received signals, and calculating reliability for the received signals, in which the reliability is proportional to a real value of a sum of the differential values in each reception path of the plurality of reception paths.

Message faults are caused by network crowding and signal fading at high frequencies of 5G and 6G. Current error-detection and correction algorithms are computationally demanding, especially for new low-cost reduced-capability IoT devices. Disclosed are methods for (a) determining whether a message is faulted using a compact error-detection code, (b) localizing the most likely faulted message element(s) according to the waveform signal, and (c) determining the likely corrected version by back-calculating from the error-detection code. Other versions include testing various modulation substitutions for the most suspicious message elements, having the worst signal quality. The waveform parameters may include a deviation from an average amplitude, phase, frequency, or polarization, as well as an amount of amplitude variation and phase variation within the message element. Identification of the most likely faulted message elements may enable recovery of the message without a costly retransmission.

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.

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.

Certain aspects of the present disclosure provide techniques for dynamic configuration of demodulation reference signals (DMRSs). A method that may be performed by a base station (BS) includes receiving one or more uplink signals from at least one user equipment (UE); estimating a Doppler shift associated with the one or more uplink signals; determining a density of reference signals (RSs) within a slot for the at least one UE based, at least in part, on the estimated Doppler shift associated with the one or more uplink signals; and transmitting information to the at least one UE indicating an allocation of RS resources for the UE, wherein the allocation of the RS resources is based on the density of the RSs for the at least one UE.