Disclosed are a signal receiving apparatus based on FTN and a signal decoding method thereof, and the apparatus includes: an equalizer calculating, when a signal sampled by Fast to Nyquist (FTN) is received on a communication channel, a posterior probability of information bits and calculating a log likelihood ratio by using the calculated posterior probability; a deinterleaver deinterleaving bit data output from the equalizer; a decoder correcting of signal interference of the data bits deinterleaved by the deinterleaver by using the LLR and decoding the corrected signal interference; and an interleaver interleaving data output from the decoder to provide the interleaved data to the equalizer.

Disclosed is a reception apparatus that has solved a problem that fluctuations cannot be followed immediately after a commencement of turbo equalization in a high-speed fading environment. A reception apparatus includes a soft interference canceller, an MMSE equalizer, a likelihood calculator, a de-interleaver, an SISO decoder, an information bit hard decision unit, a subtracter, an interleaver, a soft estimation value calculator, a zero storage unit, a known signal memory unit, a transmission path estimator, and a plurality of switches. At the time of equalization, the transmission path estimator uses, as a reference signal, a known signal stored in the known signal memory unit or an output of the MMSE equalizer. Meanwhile, at the time of a first equalization, the soft interference canceller is given a 0 value from the zero storage unit as a reference signal.

Provided is a receiver for receiving a signal including a symbol, the receiver including processing circuitry configured to generate a first log likelihood ratio corresponding to a bit included in the symbol based on a first log likelihood ratio calculation method, the first log likelihood ratio calculation method being a linear calculation method, generate a second log likelihood ratio corresponding to the bit based on a second log likelihood ratio calculation method, the second log likelihood ratio calculation method being a nonlinear calculation method, generate comparison data based on a result of comparing the first log likelihood ratio with the second log likelihood ratio, and generate a final log likelihood ratio corresponding to at least one of the first log likelihood ratio or the second log likelihood ratio based on the comparison data.

Systems and methods for symbol detection. The methods comprising: receiving, by a receiver, a signal that was transmitted in a single carrier transmission system; detecting, by a processor of the receiver, a plurality of first symbols in the received signal that are to be detected and a plurality of second symbols in the received signal that are to be considered interfering symbols; cancelling, by the processor, interference from the received signal using the plurality of second symbols to obtain a modified received signal; obtaining, by the processor, soft values using a stochastic detection algorithm that considers each of the plurality of first symbols as being transmitted from respective virtual transmitters and received by respective virtual receivers; and using the soft values to recover symbols from the received signal.

The present disclosure provides a system and a method for implementing rate recovery in the PUSCH and PDCH bit rate processing chain of network. The system packs log likelihood ratios (LLRs) data in such a way that for each equalized in phase and quadrature (IQ) symbols, a predetermined number of LLRs equal to the modulation order are packed. The system de-interleaves the packed LLRs by reading the most significant bit (MSB) LLRs row wise for the number of columns equal to the modulation order. The system uses a single buffer for de-interleaving, bit-deselection, and filler bit addition stages, thereby reducing memory requirement of the system. The system processes only a predetermined number of LLRs to a HARQ combining stage to optimize memory and reduce latency.

A communication unit for performing soft-decision demodulation comprises a receiver that receives a transmitted signal having a first set of bits comprising k bits, selected from a set of 2.sup.k possible signals according to values of the k bits, and a second set of bits comprising Q.sub.m bits based on a phase rotation of the transmitted signal selected from a set of 2.sup.Qm possible rotations. The receiver comprises: a demodulator comprising a bank of 2.sup.k correlators and is configured to: detect a transmission of each possible transmitted signal, and output 2.sup.k phases of the correlator outputs as a third set of inputs. A de-mapper circuit receives the third set of inputs: determines statistics derived from a number of aggregated correlator output phase distributions of the third set of inputs; and calculates and outputs a second set of aposteriori soft bits comprising Q.sub.m soft bits.

Systems, apparatus, and methods for channel estimation and data detection. In one exemplary embodiment, the data is obtained in a two-phase transmission structure that alternates known data with unknown data according to a regular or otherwise pre-determined time interval. Then, the receiver iteratively updates a postulated channel, and provides a predicted channel to the next time slot. Conceptually, the exemplary techniques iteratively improve its postulates for channel condition and data over multiple time slots. More directly, instead of linear detection and decoding of a pilot for channel estimation in each time slot, the exemplary techniques described herein use postulated channel conditions to attempt data detection and use the recovered data from data detection (unknown data) to re-postulate the channel conditions, etc. until channel conditions are stable and/or the next time slot is ready for processing.

A method of detecting signals in a multiple-input multiple-output (MIMO) communication system is provided. The method includes: receiving a signal vector and a channel matrix associated with transmissions from a plurality of antennas; initializing symbol information for the signal vector; applying a minimum mean square error (MMSE) detection process to the signal vector to generate updated symbol information; repeating the MMSE detection process for a plurality of iterations, each iteration including further updating the symbol information based on outputs of a previous iteration, wherein the MMSE detection process is performed using a real-valued system model of the signal vector; and outputting final symbol information from the MMSE detection process as detected symbols.

Provided in the present disclosure are a detection circuit, a detection method and a detection apparatus for a maximum likelihood sequence, and an electronic device. The detection circuit for detecting a maximum likelihood sequence includes an equalization processing module, configured to perform equalization processing on an output signal from an analog-to-digital converter (ADC) and output a soft value based on the output signal from the ADC; a state selection module, connected to the equalization processing module and configured to determine a target signal state based on the soft value; and a detection module, connected to the state selection module and configured to perform maximum likelihood sequence detection based on the target signal state and output a detection result after decoding.

An operating method of a modem chip includes receiving a first Euclidean distance (ED) set including an ED of first symbol vector candidates, comparing magnitudes of the EDs of the first ED set, calculating each of a first minimum ED corresponding to a bit value of a first bit being 1 and a second minimum ED corresponding to the bit value of the first bit being 0, the first bit being from among a plurality of bits of a plurality of layers of the transmission symbol, based on first index information including results of the comparing the magnitudes of the EDs of the first ED set, updating the first minimum ED and the second minimum ED with a smallest first minimum ED and a smallest second minimum ED, respectively, and detecting the transmission symbol based on the updated first minimum ED and the updated second minimum ED.