Abstract:
An achievable sum data rate with respect to each of available candidate transmission/reception modes may be calculated to select a transmission/reception mode of transmission/reception pairs repeatedly using radio resources. A transmission/reception mode to be applied may be selected from the candidate transmission/reception modes based on the calculated sum data rate. Information associated with the selected transmission/reception mode may be shared by the transmission/reception pairs.
Abstract:
An iterative decoding system for intersymbol interference (ISI) channels has a module for extracting bit reliabilities from a partial response (PR) channel, an iterative decoder, and a module for updating the bit reliabilities. A transmitter parses a data sequence into blocks that are encoded to generate a sequence of codewords. By encoding, a correlation among the bits of each codeword output to the PR channel is created. A maximum likelihood sequence detector (MLSD) in the receiver produces estimates of transmitted bits from samples of the output from the PR channel. The MLSD detector has a priori knowledge of typical error events that can occur during transmission through the channel. Along with the bit estimates, at each time instant the MLSD detector generates set of error event likelihoods. These error event likelihoods are then converted into bit reliabilities that, together with estimates for the transmitted bits, are used to recalculate the bit reliabilities using the knowledge of the relation between bits within a codeword. The iterative decoder uses this soft input information (bit reliabilities and bit estimates) for each iteration of decoding to improve i) the estimate of the bit reliabilities, ii) the decisions of what bit has been transmitted, and iii) calculations for the error event likelihoods for the next iteration. These error event likelihoods are then converted into bit reliabilities that, together with estimates for the transmitted bits, are used by the iterative decoder to recalculate the bit reliabilities using the knowledge of correlation among bits within the codeword. The error event likelihoods may be updated using the updated bit reliabilities, and the updated error event likelihoods are then converted to new bit reliabilities for the next iteration. In an iterative manner, increasing those bit reliabilities that tend to show increasing confidence for corresponding decoded bits (i.e., corresponding Viterbi decisions) between iterations, while decreasing those reliabilities that tend to show decreasing confidence for corresponding decoded bits, tends to drive the iterative decoding scheme to fewer iterations while maintaining a predetermined probability of error.
Abstract:
A data recording system employs parallel iterative decoding of soft output samples representing encoded data read from a storage medium. The iterative decoder reads packets of data from a sector of the medium, each packet containing soft output samples representing data encoded with a concatenated code formed from N component codes, N a positive integer. The iterative decoder employs I decoding iterations, I a positive integer. Each packet has a length substantially equal to the sector length divided by N. For an exemplary magnetic recording system, encoded data read from a sector of a magnetic medium is partitioned into N packets of length 4096/N. The first packet is passed to the first component code decoder of a parallel iterative decoder. When the second packet is ready to be passed to the first component code decoder, the decoded output values of the first packet in the first decoder are passed to the second component code decoder. The second packet is then applied to the first component code decoder. This operation is repeated until the last (Nth) packet is input to the first component code decoder. When the last (Nth) packet is input to the first component code decoder, all data in a sector is stored within the parallel iterative decoder and servo mode of the magnetic recording system is enabled. During servo mode, the iterative process of the iterative decoder begins. The decoded output of the first packet in the last (Nth) component code decoder is now input to the first component code decoder and the second iteration starts. Each packet in the corresponding component code decoder is then circularly shifted to the next component code decoder. After repeating the decode and shift operation for I iterations, each successive packet output from the last (Nth) component code decoder is provided as the decoded user data.
Abstract:
Methods and apparatus for spatial multiplexing in a closed-loop Multi Input Multi Output (MIMO) system are provided. In a method of operating a receiver in an MIMO system, a signal transmitted by a transmitter is received. Blockwise-Orthogonalized Spatial Multiplexing (B-OSM) is performed on the received signal. Feedback information determined by performing the B-OSM on the received signal is fed back to the transmitter.
Abstract:
Disclosed is a relay. The relay includes: a reception unit configured to receive signals from a transmitter; a processor configured to estimate a channel with respect to the transmitter based on a pilot signal of the transmitter among receiving signals, remove the pilot signal from among the received signals, amplify the signals without the pilot signal according to the estimated channel, and insert a pilot signal of the relay into the amplified signals; and a transmitter transmitting the signals including the pilot signal of the relay under the control of the processor.
Abstract:
A maximum a posteriori (MAP) detector/decoder employs an algorithm that computes log-likelihood value with an a posteriori probability (APP) value employing a number N of previous state sequences greater than or equal to two (N≧2). By defining the APP with more previous state sequences, the set of &agr; values may be calculated for a current state and then reduced. After generating the reduced set of &agr; values, the full set of &bgr; values may be generated for calculation of log-likelihood values. By calculating a set of &agr; values that may be decimated by, for example, N, the amount of memory required to store the &agr; values used in subsequent computations is reduced.
Abstract:
An iterative decoder employs detection and post-processing of channel output samples to generate soft output vales for encoded data provided to the decoder for one or more iterations of decoding. The channel output samples account for user data encoded with concatenated codes. For one or more other iterations, the reliability values of the soft values of the prior iteration are updated, generating soft output data for the decoder for the current iteration of decoding. A detector may use a soft-output Viterbi algorithm (SOVA) to detect encoded data from channel output samples, and the SOVA algorithm may be implemented by a Viterbi algorithm generating hard decisions from the output channel samples followed by post-processing to generate and update reliability values for the soft-output values based on the hard decisions and output channel samples. In one implementation, generating soft-output values from output channel samples by a detector employs the full soft-output Viterbi algorithm (SOVA) during the first iteration. For subsequent iterations, the post-processor of the full SOVA algorithm is used without a Viterbi detector.
Abstract:
A data transmission system employs an iterative decoder that applies decision feedback equalization (DFE) to channel output samples of a packet of data. The iterative decoder receives a stream of channel output samples as packets that may, for example, be read from a sector of a recording medium. Each packet may represent user data encoded, for example, with a concatenated code formed from N component codes, N a positive integer. The iterative decoder employs I decoding iterations, I a positive integer. DFE employs two filters: a feedforward filter and a feedback filter. The feedforward filter, which may be a whitened-matched filter used for detection, shifts dispersed channel output energy into the current sample. The feedback filter cancels energy of trailing inter-symbol interference from previous symbols. In each iteration by the iterative decoder, the DFE is applied to channel output samples of a packet by filtering with the feedforward filter, and then filtering with the feedback filter to cancel interference energy in the current sample from previous samples. The feedback filter uses soft information corresponding to tentative decisions for decoded data of the packet. During the first iteration, the soft information for applying DFE to the current sample is derived from the slicer output directly, and during the second and subsequent iterations the soft data of the decoder is provided to the feedback filter of the equalizer as soft information.
Abstract:
An iterative decoder arranges calculation of updated reliability values for a current iteration of an iterative decoder so as to reduce the number of comparison operations. The variables for the magnitude and sign of the updated reliability value are initialized. A search of the previous reliability values generates first and second minimum magnitude values for each row (if the iterative decoder is decoding in the horizontal direction) or column (if the iterative decoder is decoding in the vertical direction). A test determines whether the magnitude of the previous reliability value is greater than the first minimum magnitude value m1. If so, the magnitude of the updated reliability value is set as the value m1. Otherwise, the magnitude of the updated reliability value is set as the second minimum magnitude value m2. The sign of the updated reliability value is tracked and assigned once the updated reliability value is set.