Link performance abstraction for ML receivers based on RBIR metrics
A PHY abstraction mapping between the link level and system level performance is presented based on mapping between the mean RBIR (Received Bit Information Rate) of the transmitted symbols and their received LLR values after symbol-level ML detection in SISO/MIMO wireless systems, such as WiMAX. In MIMO antenna configuration, the mapping is presented for both vertical and horizontal encoding. An embodiment of this invention provides the PER/BLER prediction in the actual system, enabling the system to use more aggressive methods to improve the system performance.
1. A method for link performance abstraction under maximum likelihood receivers, said method comprising:
determining at a receiver a symbol-level log-likelihood-ratio distribution based on a channel matrix and a signal-to-noise ratio, for a symbol of multiple symbols and a subcarrier of one or more subcarriers received by the receiver;
determining at the receiver a received bit information rate for said subcarrier based on said symbol-level log-likelihood-ratio distribution;
calculating at the receiver a mean received bit information rate over said multiple symbols and said one or more subcarriers, and storing said mean received bit information rate in a memory location; and
determining at the receiver a block error rate based on said mean received bit information rate and a code rate.
2. A method as recited in claim 1 , wherein said determining said block error rate comprises:
determining at the receiver an effective signal-to-noise-ratio based on said mean received bit information rate; and
determining at the receiver said block error rate based on said effective signal-to-noise-ratio and said code rate.
3. A method as recited in claim 2 , wherein said determining said effective signal-to-noise-ratio comprises using a lookup table.
4. A method as recited in claim 2 , wherein said determining said block error rate based on said effective signal-to-noise-ratio and said code rate comprises using a lookup table or using an approximate expression for said block error rate based on an additive-white-Gaussian-noise signal-to-noise-ratio.
5. A method as recited in claim 1 , wherein said determining said symbol-level log-likelihood-ratio distribution uses a zero mean noise distribution model with a noise level variance based on said signal-to-noise ratio.
6. A method as recited in claim 1 , wherein said determining said symbol-level log-likelihood-ratio distribution approximates said symbol-level log-likelihood-ratio distribution by using constellation points having dominant Euclidean distance relative to said symbol.
7. A method as recited in claim 1 , wherein said determining said symbol-level log-likelihood-ratio distribution approximates said symbol-level log-likelihood-ratio distribution by a normal distribution for a sender antenna stream.
8. A method as recited in claim 7 , wherein parameters of said normal distribution are determined by numerical approximation or by using a lookup table.
9. A method as recited in claim 7 , wherein one or more parameters of said normal distribution is adjusted by an adjustment factor.
10. A method as recited in claim 9 , wherein said adjustment factor is determined based on said channel matrix, said signal-to-noise-ratio, and a modulation coding scheme.
11. A method as recited in claim 10 , wherein eigenvalues of said channel matrix are used in said determining adjustment factor.
12. A method as recited in claim 10 , wherein said adjustment factor is determined by using a lookup table.
13. A method as recited in claim 1 , wherein in case of having multiple sending antennas, said determining said symbol-level log-likelihood-ratio distribution comprises combining sending-antenna-stream symbol-level log-likelihood-ratio distributions corresponding to said multiple sending antennas.
14. A method as recited in claim 13 , wherein in case of having vertical encoding across said multiple sending antennas, said combining sending-antenna-stream symbol-level log-likelihood-ratio distributions uses stream weights corresponding to said multiple sending antennas.
15. A method as recited in claim 1 , wherein said determining said received bit information rate uses one or more of the following techniques: numerical approximation, using a lookup table, or using a simplified approximate form.
16. A method as recited in claim 1 , wherein a coded block comprises mixed modulation symbols; and
wherein said calculating said mean received bit information rate uses a mean number of bits per symbol within said coded block.
17. A method for link performance abstraction under maximum likelihood receivers, said method comprising:
determining at a receiver a symbol-level log-likelihood-ratio distribution based on a channel matrix and a signal-to-noise ratio, for a symbol of multiple symbols and a subcarrier of one or more subcarriers received by the receiver, and based on an approximation of said symbol-level log-likelihood-ratio distribution with a normal distribution for a sender antenna stream;
determining at the receiver a received bit information rate for said subcarrier based on said symbol-level log-likelihood-ratio distribution by using one or more of the following techniques: numerical approximation, using a lookup table, or using a simplified approximate form;
calculating at the receiver a mean received bit information rate over said multiple symbols and said one or more subcarriers, and storing said mean received bit information rate in a memory location; and
determining at the receiver a block error rate based on said mean received bit information rate and a code rate.
18. A method as recited in claim 17 , said method further comprising:
providing a channel quality indicator feedback to a transmitter, based on said block error rate.
19. A method as recited in claim 17 , said method further comprising:
in case of having multiple sending antennas, said determining said symbol-level log-likelihood-ratio distribution comprises combining sending-antenna-stream symbol-level log-likelihood-ratio distributions corresponding to said multiple sending antennas.
20. A method as recited in claim 19 , said method further comprising:
in case of having vertical encoding across said multiple sending antennas, said combining sending-antenna-stream symbol-level log-likelihood-ratio distributions uses stream weights corresponding to said multiple sending antennas.