A sequence estimation device includes: a soft decision processing unit, generating a plurality of input signals including soft information according to a plurality of first equalized signals, an equalizer weight and a plurality of estimation signals corresponding to the equalizer weight; and a decoding unit, coupled to the soft decision processing unit, decoding the plurality of input signals including the soft information according to a decoding rule to generate a plurality of output signals.

An apparatus and method for optimizing the performance of satellite communication system receivers by using the Soft-Input Soft-Output (SISO) BCJR (Bahl, Cocke, Jelinek and Raviv) algorithm to detect a transmitted information sequence is disclosed. A Sliding Window technique is used with a plurality of reduced state sequence estimation (RSSE) equalizers to execute the BCJR algorithm in parallel. A serial data stream is converted into a plurality of data blocks using a serial-to-parallel converter. After processing in parallel by the equalizers, the output blocks are converted back to a serial data stream by a parallel-to-serial converter. A path history is determined using maximum likelihood (ML) path history calculation.

Circuits for producing signals representative of mean and variance estimations for quadrature amplitude modulation (QAM) are provided where the circuits comprise: sequentially repeated first circuit modules and sequentially repeated second circuit modules configured for producing updates in the corresponding estimation iterations. In one embodiment, a closest negative integer power of 2 is used as a substitute multiplicand when multiplying together two or more outputs of hyperbolic function generating units where the substituted for output is less than one. Size and complexity of the corresponding multiplier can then be reduced.

A system, method and device for wireless communication is provided. The method includes receiving, by a receiver, data from a transmitter, storing the data in the receiver, and determining, by the receiver, a probability of a bit stored in the data and a probability of a symbol based on the probability of the bit, wherein determining the probability of the bit includes moving a decision boundary associated with a constellation diagram.

A communication unit for performing soft-decision demodulation comprises a receiver that receives a transmitted signal conveying a first set of bits comprising k bits selected from a set of 2.sup.k possible signals. A demodulator comprises a bank of 2.sup.k correlators that detects a transmission of each possible transmitted signal, and outputs 2.sup.k magnitudes of correlator outputs, based on the detected possible transmitted signals, as a first set of inputs. A-de-mapper circuit receives the first set of inputs and determines derived from a plurality of aggregated correlator output magnitude distributions of the first set of inputs, wherein the plurality of aggregated correlator output magnitude distributions is fewer than 2.sup.2k; and calculates therefrom a first set of aposteriori soft bits comprising k soft bits. In this manner, high quality soft-decisions can be obtained in a robust and practical manner.

A receiver for receiving a combination signal having two separate signal portions whose pulses are shifted relative to each other and/or whose carrier waves have a phase difference is configured to obtain a first series of samples using a first sampling and to obtain a second series of samples using a second sampling. The first sampling is adjusted to a symbol phase of the first signal portion, the second sampling is adjusted to a symbol phase of the second signal portion. The receiver is configured to obtain probabilities of transmission symbols of the first signal portion and probabilities of transmission symbols of the second signal portion for a plurality of sampling times based on the first and second series of samples, and to determine probabilities for transmission symbols of the first signal portion based on samples of the first sampling and estimated or calculated probabilities for transmission symbols of the second signal portion without taking into account inter-symbol interference between transmission symbols of the first signal portion in the samples of the first sampling, and determines probabilities for symbols of the second signal portion correspondingly. A corresponding method and computer program are described.

An apparatus for optimization of signal shaping for a multi user multiple input multiple output, MU-MIMO, communication system, including circuitry configured for receiving a bit vector; and for determining a constellation vector, wherein the circuitry for determining the constellation vector includes a Geometric Shaping and Labeling Block, GSLB, for modulating the bit vector, wherein the GSLB is configured to implement an algorithm with one or more trainable parameters.

A receiver and a method for receiving a radio communication is disclosed. The method includes receiving a burst encoded with a robust modulation coding scheme (MCS) as RX signals; generating, for each of the RX signals, a burst SNR, soft decision symbols and a packet; weighing, each of soft decision symbols with a respective burst SNR, to calculate soft combined symbols that are used to generate a Maximal-Ratio Combining (MRC) packet; and selecting, from the packets and the MRC packet, a CRC passed packet as an output. An adaptive dual burst transmitter is disclosed.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment may transmit a request, for an uplink transmission or a downlink transmission, for data aided phase tracking reference signals (PT-RSs) on multiple layers of a communication link; and communicate the uplink transmission or the downlink transmission based at least in part on the request. Numerous other aspects are provided.

A Viterbi Equalizer having a limited number of stages is disclosed. In some embodiments, the Viterbi Equalizer may have only four stages. The Viterbi Equalizer produces soft decisions, which comprise a final decision and reliability information related to that final decision. The Viterbi Equalizer is able to provide reliability information even if all paths do not converge on the final decision at the last stage. The reliability information is calculated based on if and when the paths in the trellis converge on a final decision. This reliability information can be used downstream, such as by another Viterbi Algorithm block to perform forward error correction. The use of soft decision provides gains of up to several dB in performance. Additionally, the Viterbi Equalizer is low cost and readily implemented in hardware or software.