Method for multiple-input-multiple-output system demodulation
AssigneeNEC Laboratories America, Inc.
InventorsNarayan Prasad, Xiaodong Wang, Mohammad Madihian
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Abstract
A MMSE-based deterministic sequential Monte Carlo (SMC) method for MIMO demodulation exhibiting square root complexity in terms of constellation size. Further extensions to the method reduce the search space resulting in significant reduction in computational requirements while minimally impacting performance. As a hard decision algorithm, the methods achieve sphere decoder performance while imposing a much smaller computational load.
Claims7
A low complexity Minimum Mean Square Error (MMSE) based sequential Monte Carlo method for Multiple-Input Multiple-Output (MIMO) demodulation, said method comprising the steps of:
- receiving a plurality of signals at an array of receive antennas;
- estimating a channel matrix;
- determining a channel dependent order of demodulation that is responsive to the estimated channel matrix;
- processing the received signal vector through the use of MMSE techniques;
- modeling the processed received signal vector as being equal to the sum of a linear transformation of the transmitted symbols by a triangular matrix having positive diagonal elements and a vector representing a realization of a plurality of un-correlated Gaussian random variables;
- and
- demodulating the said transmitted symbols using deterministic sequential Monte Carlo techniques on the processed received signal and the said model.
A method for communicating data from a transmitter to a receiver in a Multiple-Input Multiple-Output (MIMO) wireless system, comprising:
- encoding a data stream to obtain spherical lattice codewords;
- transmitting the said codewords using a plurality of transmit antennas and time intervals;
- receiving a plurality of signals at an array of receive antennas and collecting the received signals over a plurality of time intervals;
- processing the collected received signals through the use of MMSE techniques;
- modeling the processed received signal vector as being equal to the sum of a linear transformation of the transmitted codeword and a vector representing a realization of a plurality of un-correlated Gaussian random variables;
- and
- decoding that said transmitted codeword using deterministic sequential Monte Carlo techniques on the processed received signal and the said model, said deterministic
- sequential Monte Carlo technique incorporating a spherical boundary constraint.
Dependencies are inferred from the claim text.