Qualcomm Incorporated

Bjorn Bjerke

John Wendell Ketchum

Steven J Howard

Jay Rodney Walton

Jay Rod Walton

Mark S Wallace

Nagabhushana T Sindhushayana

Irina Medvedev

Methods and apparatus for enhancing estimations of channel response in a wireless communication system are discussed. As an example, a method can comprise: selecting a selected channel from among one or more channels in the communication system; determining, for the selected channel, an initial channel estimate comprising a sequence of frequency-domain samples; determining a phase slope of the initial channel estimate; generating a flat-phase channel estimate by removing the phase slope from the initial channel estimate; and generating an enhanced channel estimate for the selected channel by applying a smoothing function to the flat-phase channel estimate. Other aspects, embodiments, and features are also claimed and described.

Systems and methods for enhanced channel estimation in wireless communication systems

Techniques for performing detection and decoding at a receiver are described. In one scheme, the receiver obtains R received symbol streams for M data streams transmitted by a transmitter, performs receiver spatial processing on the received symbols to obtain detected symbols, performs log-likelihood ratio (LLR) computation independently for each of D best data streams, and performs LLR computation jointly for the M&#x2212;D remaining data streams, where M&#x3e;D&#x2267;1 and M&#x3e;1. The D best data streams may be selected based on SNR and/or other criteria. In another scheme, the receiver performs LLR computation independently for each of the D best data streams, performs LLR computation jointly for the M&#x2212;D remaining data streams, and reduces the number of hypotheses to consider for the joint LLR computation by performing a search for candidate hypotheses using list sphere detection, Markov chain Monte Carlo, or some other search technique.

Reduced complexity detection and decoding for a receiver in a communication system

Disclosed herein are methods and apparatus for enhancing the estimation of channel response in a wireless communication system. An apparatus (and associated method) for optimizing channel estimation in a communication system includes a receiving antenna; a receiver adapted to receive a signal from the receiving antenna; an initial channel estimator module adapted to select a selected channel from among one or more channels in the communication system and to determine, for the selected channel, an initial channel estimate based upon the received signal; a transformation module adapted to transform the initial channel estimate into an initial impulse response estimate comprising a sequence of samples; a filtering module adapted to select a sub-sequence of samples from the sequence of samples and generate a truncated initial impulse response estimate by setting to zero the samples in the initial impulse response estimate that are not in the selected sub-sequence of samples; and a maximum likelihood channel estimating module adapted to compute a time domain weighted impulse response estimate using the truncated time domain impulse response estimate for the selected channel and to compute a maximum likelihood channel estimate for the selected channel by transforming the time domain weighted impulse response estimate into the frequency domain.

Method and apparatus for generating codewords with variable length and redundancy from a single Low-Density Parity-Check (LDPC) code with variable length input words. A mother code for encoding data words is generated based on a parity-check matrix, wherein the mother code is adjusted to reflect the size of the data word to be encoded. A generator matrix applies the mother code to data words to produce codewords for transmission. In one embodiment, a reduction criteria is determined and the size of the generator matrix reduced in response. The corresponding parity-check matrix is applied at the receiver for decoding the received codeword.

Rate-compatible LDPC codes

Techniques to iteratively detect and decode data transmitted in a wireless (e.g., MIMO-OFDM) communication system. The iterative detection and decoding is performed by iteratively passing soft (multi-bit) 'a priori' information between a detector and a decoder. The detector receives modulation symbols, performs a detection function that is complementary to the symbol mapping performed at the transmitter, and provides soft-decision symbols for transmitted coded bits. 'Extrinsic information' in the soft-decision symbols is then decoded by the decoder to provide its extrinsic information, which comprises the a priori information used by the detector in the detection process. The detection and decoding may be iterated a number of times. The soft-decision symbols and the a priori information may be represented using log-likelihood ratios (LLRs). Techniques are provided to reduce the computational complexity associated with deriving the LLRs, including interference nulling to isolate each transmitted signal and &#x201c;dual-maxima&#x201d; approximation.

Iterative detection and decoding for a MIMO-OFDM system

Techniques for preceding data for a multipath channel in a MIMO system. In one method, data is coded in accordance with one or more coding schemes to provide coded data, which is further modulated (i.e., symbol mapped) in accordance with one or more modulation schemes to provide modulation symbols. An estimated response of the MIMO channel is obtained (e.g., provided by a receiver), and an equivalent channel response is derived based on the estimated MIMO channel response and a response of a feed-forward filter of a decision feedback equalizer. The modulation symbols are then precoded based on the equivalent channel response to provide precoded symbols, which are further preconditioned based on the estimated MIMO channel response (e.g., using spatio-temporal pulse-shaping) to provide preconditioned symbols for transmission over the MIMO channel. The feed-forward filter may be adapted based on a minimum mean square error (MMSE) criterion.

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Bjorn Bjerke