Co-channel interference cancellation with multiple receive antennas for BICM
Apparatus and methods are provided for computing soft information at a receiver having a plurality of receive antennas. The receiver may be a mobile station or a base station, and can receive a signal vector that includes an intended signal from a first source as well as interfering signals from one or more other, interfering sources. The receiver can determine modulation information, such as the modulation scheme, used by each of the interfering sources. The mobile station can also estimate channel information, such as channel gain information, associated with each interfering source. Using the modulation and channel information, the receiver can compute soft information, such as a log-likelihood ratio. In some embodiments, the receiver can adaptively determine which interference sources and which receive antennas to use when computing the soft information.
1. A method of computing soft information for use in estimating digital information from an intended source, the method comprising:
receiving, at a receiver, a plurality of data signals with a plurality of different antennas, wherein each of the plurality of data signals includes an intended signal corresponding to the digital information from the intended source and an interference signal from at least one interfering source comprising a plurality of interference sources
for each respective data signal of the plurality of data signals, comparing, at the receiver, a strength of the intended signal to a strength of the interference signal within the respective data signal;
selecting, at the receiver, a subset of the plurality of data signals based on the comparisons; computing the soft information corresponding to the digital information using the subset of data signals; selecting a subset of the interference sources; and wherein computing the soft information comprises calculating the soft information using only interference signals received from the subset of the interference sources.
2. The method of claim 1 , wherein comparing the strength of the intended signal to the strength of the interference signal within the respective data signal comprises computing a signal-to-interference plus noise ratio (SINR) for the respective data signal.
3. The method of claim 2 , wherein selecting a subset of the plurality of data signals comprises selecting each data signal of the plurality of data signals having a SINR of at least a predetermined value.
4. The method of claim 2 , wherein selecting a subset of the plurality of data signals comprises selecting a predetermined number of the plurality of data signals having the highest SINR values.
5. The method of claim 1 further comprising:
computing a receive signal vector and a channel response matrix from the plurality of data signals;
multiplying the receive signal vector and the channel response matrix by a modifying matrix having dimensions N r ×M to produce a modified receive signal vector and a modified channel response matrix respectively, where N r is a number of different antennas used to receive the plurality of data signals, and M is a number of data signals within the subset of data signals.
6. The method of claim 5 further comprising calculating a distance metric based on the modified receive signal vector and the modified channel response matrix.
7. The method of claim 1 , wherein each of the plurality of interference sources is associated with a transmit dimension of a channel matrix, and wherein selecting a subset of the interference sources comprises:
calculating a norm of each transmit dimension of the channel matrix;
identifying each of the transmit dimensions of the channel matrix that has a norm of at least a predetermined value; and
selecting each of the plurality of interference sources associated with an identified transmit dimension.
8. The method of claim 1 , wherein each of the plurality of interference sources is associated with a transmit dimension of a channel matrix, and wherein selecting a subset of the interference sources comprises:
calculating a norm of each transmit dimension of the channel matrix;
identifying the transmit dimensions of the channel matrix that have the highest norms; and
selecting a predetermined number of the plurality of interference sources associated with the identified transmit dimensions.
9. The method of claim 1 , wherein each of the plurality of interference sources is associated with a column of a channel matrix, the method further comprising:
reordering the columns of the channel matrix with the columns corresponding to the subset of the interference sources at a first position in the channel matrix; and
performing QR decomposition on the reordered channel matrix.
10. A system for computing soft information to estimate digital information from an intended source, the system comprising:
a plurality of receive antennas at a receiver operable to:
receive a plurality of data signals, wherein each of the plurality of data signals includes an intended signal corresponding to the digital information from the intended source and an interference signal from at least one interfering source comprising a plurality of interference sources
computational logic at the receiver configured to:
compare, for each respective data signal of the plurality of data signals, a strength of the intended signal to a strength of the interference signal within the respective data signal; and
select a subset of the plurality of data signals based on the comparisons; wherein the computational logic is further configured to select a subset of the interference sources; and
a soft bit-metric calculator configured to:
compute the soft information corresponding to the digital information using the subset of data signals; and wherein the soft bit-metric calculator is further configured to calculate the soft information using only interference signals received from the subset of the interference sources.
11. The system of claim 10 , wherein the computational logic is further configured to compute a signal-to-interference plus noise ratio (SINR) for the respective data signal.
12. The system of claim 11 , wherein the computational logic is configured to select a subset of the plurality of data signals by selecting each data signal of the plurality of data signals having a SINR of at least a predetermined value.
13. The system of claim 11 , wherein the computational logic is configured to select a subset of the plurality of data signals by selecting a predetermined number of the plurality of data signals having the highest SINR values.
14. The system of claim 10 , wherein the computational logic is further configured to:
compute a receive signal vector and a channel response matrix from the plurality of data signals;
multiply the receive signal vector and the channel response matrix by a modifying matrix having dimensions N r ×M to produce a modified receive signal vector and a modified channel response matrix respectively, where N r is a number of different antennas used to receive the plurality of data signals, and M is a number of data signals within the subset of data signals.
15. The system of claim 14 , wherein the soft bit-metric calculator is further configured to calculate a distance metric based on the modified receive signal vector and the modified channel response matrix.
16. The system of claim 10 , wherein each of the plurality of interference sources is associated with a transmit dimension of a channel matrix, and wherein the computational logic is configured to select a subset of the interference sources by:
calculating a norm of each transmit dimension of the channel matrix;
identifying each of the transmit dimensions of the channel matrix that has a norm of at least a predetermined value; and
selecting each of the plurality of interference sources associated with an identified transmit dimension.
17. The system of claim 10 , wherein each of the plurality of interference sources is associated with a transmit dimension of a channel matrix, and wherein the computational logic is configured to select a subset of the interference sources by:
calculating a norm of each transmit dimension of the channel matrix;
identifying the transmit dimensions of the channel matrix that have the highest norms; and
selecting a predetermined number of the plurality of interference sources associated with the identified transmit dimensions.
18. The system of claim 10 , wherein each of the plurality of interference sources is associated with a column of a channel matrix, the computational logic further configured to:
reorder the columns of the channel matrix with the columns corresponding to the subset of the interference sources at a first position in the channel matrix; and
perform QR decomposition on the reordered channel matrix.