Patent classifications
H03M13/3905
Parallelizable reduced state sequence estimation via BCJR algorithm
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.
DECODING PATH SELECTION DEVICE AND METHOD
The present invention discloses a decoding path selection device for decoding codewords generated by convolutional codes or turbo codes encoders in error correction codes, the decoding path selection device comprising: a branch metrics calculation unit for receiving incoming signals and calculating branch metrics values; a programmable generalized trellis router for generating a decoding path control signal according to the turbo code or convolutional code specification employed by one of communications standards; a multiplexer for receiving the branch metrics values from the branch metrics calculation unit and the decoding path control signal from the programmable generalized trellis router and selecting a corresponding branch metrics value; a recursive calculation unit, connected after the multiplexer and for receiving the corresponding branch metrics value from the multiplexer; and an a-posteriori probability calculation unit, connected after the recursive calculation unit and for calculating a final decoding result.
Reception apparatus
When a channel between a transmission apparatus and a reception apparatus is distorted by multipath fading or other reasons, linear interpolation between pilot subcarriers produces a large estimation error, resulting in an increase in an equalization error and a decrease in reception performance. The present invention allows feedback of a signal that undergoes error correction, reduction in the channel estimation error through repeated channel estimation, and improvement in the reception performance.
RECEPTION APPARATUS
When a channel between a transmission apparatus and a reception apparatus is distorted by multipath fading or other reasons, linear interpolation between pilot subcarriers produces a large estimation error, resulting in an increase in an equalization error and a decrease in reception performance. The present invention allows feedback of a signal that undergoes error correction, reduction in the channel estimation error through repeated channel estimation, and improvement in the reception performance.
CYCLE SLIP RESILIENT CODED MODULATION FOR FIBER-OPTIC COMMUNICATIONS
Disclosed is a method for decoding an optical data signal. Said optical data signal is phase and amplitude modulated according to a constellation diagram with at least eight constellation points representing non-binary symbols. Said decoding method comprises the following steps: carrying out a carrier phase recovery of a received signal ignoring the possible occurrence of phase slips, decoding said signal after phase recovery, wherein in said decoding, possible cycle slips occurring during phase recovery are modelled as virtual input to an equivalent encoder assumed by the decoding scheme. Further disclosed are a related encoding method as well as a receiver and a transmitter.
FIXED POINT CONVERSION OF LLR VALUES BASED ON CORRELATION
An apparatus includes a memory and a controller. The memory may be configured to store data. The memory generally comprises a plurality of memory units each having a size less than a total size of the memory. The controller may be configured to generate a set of converted log likelihood ratios by scaling a set of original log likelihood ratios using a selected scalar value, wherein the controller determines the selected scalar value by generating a plurality of sets of scaled log likelihood ratios by scaling the set of original log likelihood ratios with a plurality of corresponding scalar values, calculating a plurality of respective correlation coefficients each measuring a similarity of a respective set of scaled log likelihood ratios to the set of original log likelihood ratios, and selecting the scalar value corresponding to the set of scaled log likelihood ratios whose respective correlation coefficient is highest as the selected scalar value.
Methods for recovering RFID data based upon probability using an RFID receiver
RFID data signals from RFID tags may be recovered by determining the probabilities of transitions between data states between a series of a pairs of signal samples using a set of predetermined probabilities related to data, timing, baud rate and/or phase variables affecting the received signal and processing those determined probabilities to determine the sequence of such transitions that has the highest probability of occurrence. A second set of predetermined probabilities related to transitions in the opposite direction may be used to sequence in a reverse direction. The determination of the sequence representing the RFID tag data may be iterated in both directions until further iterations do not change the determined probabilities.
Fixed point conversion of LLR values based on correlation
An apparatus comprising a memory and a controller. The memory may be configured to process a plurality of read/write operations. The memory comprises a plurality of memory units each having a size less than a total size of the memory. The controller may be configured to perform error correction code decoding on the memory units. The controller may be configured to generate a plurality of original log likelihood ratios each comprising a real value. The controller may be configured to convert each of the original log likelihood ratios to a converted log likelihood ratio comprising a fixed point value. The conversion comprises (a) scaling down a magnitude of each of the original log likelihood ratios, and (b) rounding each of the original log likelihood ratios having a scaled down magnitude to the fixed point value.