The present invention is directed to data communication systems and techniques thereof. More specifically, embodiments of the present invention provide an FEC encoder that processes an interleaved data stream and generates parity symbols that are embedded into FEC blocks. An FEC decoder determines whether to perform error correction based on the parity symbols. When performing error correction, the decoder selects a worst symbol from a segment of symbols, and the worst symbol is corrected. There are other embodiments as well.

Methods, systems, and devices for wireless communication are described. A wireless communication device may receive multiple data streams from one or more users, associate the multiple data streams with different user groups, and identify modulation symbols for the users after reducing signal contribution from modulation symbols associated with different user groups. For example, the device may receive a signal including multiple spatial streams, partition the data streams into different user groups, and determine a set of sequences from channel characteristics associated with the respective user groups. The wireless communication device may then apply the sequences to the received signal and to values associated with the channel characteristics. Subsets of values may be selected following the application of the sequences, and from the subsets of values, the wireless communication device may identify the sets of modulation symbols associated with one or more of the user groups.

The present invention discloses an ML (Maximum Likelihood) detector. An embodiment of the ML detector comprises a search value selecting circuit and an ML detecting circuit. The search value selecting circuit is configured to select a first-layer search value. The ML detecting circuit is configured to carry out the following steps: selecting first-layer candidate values according to the first-layer search value, one of a reception signal and a derivative thereof, and one of a channel estimation signal and a derivative thereof, and adding one or more first-layer candidate value(s), if necessary; calculating second-layer candidate values according to all the above-mentioned first-layer candidate values, and adding one or more second-layer candidate value(s) and its/their corresponding first-layer candidate value(s), if necessary; and calculating log likelihood ratios according to the whole first-layer and second-layer candidate values.

The present invention discloses an ML (Maximum Likelihood) detector comprising: a search value selecting circuit selecting a first-layer search value; and an ML detecting circuit. The ML detecting circuit executes the following steps: selecting K first-layer candidate values according to the first-layer search value, one of a reception signal and a derivative thereof, and one of a channel estimation signal and a derivative thereof; calculating K second-layer candidate values according to the K first-layer candidate values; determining whether to add P second-layer supplemental candidate value(s) and generating a decision; when the decision is affirmative, adding the P second-layer supplemental candidate values, generating P first-layer supplemental candidate values according to the P second-layer supplemental candidate values, and calculating log likelihood ratios (LLRs) according to the (K+P) first-layer and (K+P) second-layer candidate values; and when the decision is negative, calculating LLRs according to the K first-layer and K second-layer candidate values.

The present disclosure includes an ML (Maximum Likelihood) detector. An embodiment of the ML detector comprises a search value selecting circuit and an ML detecting circuit. The search value selecting circuit is configured to select a search value according to a communication index and a modulation type or determine the search value according to a predetermined value, in which the communication index is related to a reception signal or a derivative thereof, the search value is associated with a search range, and a number of candidate signal value(s) in the search range is not greater than a number of all candidate signal values of the modulation type. The ML detecting circuit is configured to execute an ML calculation according to the search value and one of the reception signal and the derivative thereof, so as to calculate a log likelihood ratio of every candidate signal value in the search range.

A method (200) for channel estimation includes receiving (201) a receive symbol (206) comprising: a plurality of interfering transmissions from: a first transmit symbol (202), the first transmit symbol (202) comprising a plurality of unknown modulated symbols interleaved with a plurality of known modulated symbols and a second transmit symbol (204), the second transmit symbol (204) comprising a plurality of unknown modulated symbols interleaved with a plurality of known modulated symbols, wherein the plurality of transmissions from the first transmit symbol (202) and the second transmit symbol (204) are a plurality of transmissions of different time instances; and estimating (203) a channel based on the receive symbol (206) and a plurality of estimates of the first transmit symbol (202) and the second transmit symbol (204).

All data symbols used in data transmission of a modulated signal are precoded by switching between precoding matrices so that the precoding matrix used to precode each data symbol and the precoding matrices used to precode data symbols that are adjacent to the data symbol along the frequency axis and the time axis all differ. A modulated signal with such data symbols arranged therein is transmitted.

A method, a computer-readable medium, and an apparatus are provided. The apparatus communicates with a second apparatus, including transmitting or receiving a first transmission. The apparatus receives information about the second UE from a sensor at the first UE and/or from a BSM. The apparatus determines whether the first apparatus and the second apparatus are in a LOS condition based on a correlation of the information with one or more of a channel estimation, PMI feedback, or RI feedback. The apparatus may adapt a transmission parameter for a second transmission based on a predicted location of the first apparatus or the second apparatus. The transmission parameter may include at least one of a modulation, a code rate, a DMRS density, a precoder, a CSI-RS transmission periodicity or a feedback rate.

A technique for assessing the reliability of bits received by a modulation symbol on a channel is provided. A providing circuit provides an input dataset including a plurality of input values. The input values correspond to different transmit hypotheses according to a modulation alphabet used for encoding the bits in the symbol. A computing circuit performs a first computing step and a second computing step. In the first computing step, a first intermediary dataset is computed by combining the input values of the input dataset according to a first combination scheme. In the second computing step, a second intermediary dataset is computed by combining the input values of the input dataset according to a second combination scheme. The second combination scheme is different from the first combination scheme. An assessing circuit assesses the reliability of the bits based on the first intermediary dataset and the second intermediary dataset.

A signal receiver with adaptive software information adjustment of a communication system is provided. The signal receiver receives a modulated signal comprising a plurality of packets, and includes: a demodulating circuit, configured to demodulate the modulated signal to generate a plurality of sets of soft information corresponding to each packet; a software information adjusting circuit, coupled to the demodulating circuit, configured to adjust the sets of soft information according to a distribution of the sets of soft information corresponding to each packet; a quantizer, coupled to the soft information adjusting circuit, configured to quantize the adjusted sets of soft information to generate a plurality of sets of data; and a decoder, coupled to the quantizer, configured to decode the data.