Efficient peak-to-average-power reduction for OFDM and MIMO-OFDM
Low-complexity computational processing provides a set of selective mapping weights for reducing peak-to-average-power ratio (PAPR) in transmitted Multiple Input, Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) signals. A MIMO precoder and invertible transform generates a base discrete-time MIMO-OFDM signal from a set of data symbols and MIMO precoding weights. A matrix multiplier multiplies the set of data symbols with a sparse update weight matrix, and the resulting product is MIMO-precoded and modulated onto an OFDM signal to produce a discrete-time update signal. A linear combiner sums the discrete-time update signal and the base discrete-time MIMO-OFDM signal to produce an updated discrete-time MIMO-OFDM signal from which the PAPR can be measured.
1. A method, comprising:
generating a base discrete-time Orthogonal Frequency Division Multiplexing (OFDM) signal from a set of data symbols;
generating a sparse update weight matrix;
multiplying the set of data symbols with the sparse update weight matrix to produce an update signal;
performing an inverse discrete Fourier transform (IDFT) on the update signal to generate a discrete-time update signal;
summing the discrete-time update signal with a previously generated base discrete-time OFDM signal to produce an updated discrete-time OFDM signal; and
designating the updated discrete-time OFDM signal to be used as the base discrete-time OFDM signal in a subsequent iteration.
2. The method of claim 1 , further comprising measuring a peak-to-average-power ratio (PAPR) of the updated discrete-time OFDM signal; comparing the PAPR to at least one PAPR measurement corresponding to at least one other discrete-time OFDM signal; and selecting a discrete-time OFDM signal corresponding to the lowest PAPR.
3. The method of claim 1 , wherein the IDFT is an inverse fast Fourier transform.
4. The method of claim 1 , wherein the sparse update weight matrix comprises at least one of a selective mapping matrix, a matrix configured to insert at least one dummy data symbol in the set of data symbols, a matrix configured to change mapping of at least one data symbol in the set of data symbols, and a matrix configured to change at least one symbol value in the set of data symbols.
5. The method of claim 1 , wherein generating the sparse update weight matrix employs at least one of a data-independent updating schedule and a data-dependent updating schedule.
6. The method of claim 1 , further comprising storing the updated discrete-time OFDM signal.
7. The method of claim 1 , wherein the set of data symbols comprises at least one of transform-precoded data symbols, spread data symbols, and Multiple Input, Multiple Output (MIMO) precoded data symbols.
8. The method of claim 1 , wherein the sparse update weight matrix is a square matrix or a vector.
9. The method of claim 1 , wherein the sparse update weight matrix corresponds to a weight set in a codebook.
10. The method of claim 1 , wherein the steps of generating the sparse update weight matrix, multiplying, performing, and summing are performed a predetermined number of times, the method further comprising transmitting at least one of a peak-to-average-power ratio (PAPR) for each updated discrete-time OFDM signal and a codebook index for a weight set corresponding to the sparse update weight matrix.
11. An apparatus, comprising:
a memory; and
one or more processors operatively coupled to the memory, the one or more processors configured for:
generating a base discrete-time Multiple Input, Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) signal from a set of data symbols and MIMO precoding weights;
generating a sparse update weight matrix;
multiplying the set of data symbols with the sparse update weight matrix to produce an update signal;
multiplying the update signal with the MIMO precoding weights to produce a precoded update signal;
performing an inverse discrete Fourier transform (IDFT) on the precoded update signal to generate a discrete-time update signal; and
summing the discrete-time update signal with a previously generated base discrete-time MIMO-OFDM signal to produce an updated discrete-time MIMO-OFDM signal.
12. The apparatus of claim 11 , further comprising measuring a peak-to-average-power ratio (PAPR) of the updated discrete-time MIMO-OFDM signal; comparing the PAPR to at least one PAPR measurement corresponding to at least one other discrete-time MIMO-OFDM signal; and selecting a discrete-time MIMO-OFDM signal corresponding to the lowest PAPR.
13. The apparatus of claim 11 , wherein the IDFT is an inverse fast Fourier transform.
14. The apparatus of claim 11 , wherein the sparse update weight matrix comprises at least one of a selective mapping matrix, a matrix configured to insert at least one dummy data symbol in the set of data symbols, a matrix configured to change mapping of at least one data symbol in the set of data symbols, and a matrix configured to change at least one symbol value in the set of data symbols.
15. The apparatus of claim 11 , wherein generating the sparse update weight matrix employs at least one of a data-independent updating schedule and a data-dependent updating schedule.
16. The apparatus of claim 11 , further comprising storing the updated discrete-time MIMO-OFDM signal.
17. The apparatus of claim 11 , further comprising designating the updated discrete-time MIMO-OFDM signal to be used as the base discrete-time MIMO-OFDM signal in a subsequent iteration.
18. The apparatus of claim 11 , wherein the MIMO precoding weights further comprise at least one of transform-precoding values and spreading values.
19. The apparatus of claim 11 , wherein the sparse update weight matrix is a square matrix or a vector.
20. The apparatus of claim 11 , wherein the sparse update weight matrix corresponds to a weight set in a codebook.
21. The apparatus of claim 11 , wherein the steps of generating the sparse update weight matrix, multiplying the set of data symbols, multiplying the update signal, performing, and summing are performed a predetermined number of times, the method further comprising transmitting at least one of a peak-to-average-power ratio (PAPR) for each updated discrete-time OFDM signal and a codebook index for a weight set corresponding to the sparse update weight matrix.
22. An apparatus, comprising:
a memory; and
one or more processors operatively coupled to the memory, the one or more processors configured to:
precode a set of data symbols with Multiple Input, Multiple Output (MIMO) precoding weights to produce a MIMO-precoded signal;
transform the MIMO-precoded signal into an Orthogonal Frequency Division Multiplexing (OFDM) signal to produce a base discrete-time MIMO-OFDM signal;
multiply the set of data symbols with a sparse update weight matrix to produce an update signal; and
sum the base discrete-time MIMO-OFDM signal with a discrete-time update signal to produce an updated discrete-time MIMO-OFDM signal, wherein the discrete-time update signal is produced by an invertible transform operating on an update MIMO-precoded signal, and the update MIMO-precoded signal is produced by performing MIMO precoding on the update signal.
23. The apparatus of claim 22 , further configured to compute a peak-to-average-power ratio (PAPR) of the updated discrete-time MIMO-OFDM signal.
24. The apparatus of claim 23 , further configured to communicate at least one of a set of PAPRs and a set of weight codebook indices to a central processor.
25. The apparatus of claim 23 , further configured to compare the PAPR to at least one PAPR corresponding to at least one other discrete-time MIMO-OFDM signal.
26. The apparatus of claim 23 , further configured to collect a plurality of PAPRs.
27. The apparatus of claim 23 , further configured to scale at least one PAPR with at least one of an antenna-specific weight and a node-specific weight.
28. The apparatus of claim 23 , further configured to select a weight set corresponding to at least one of a lowest PAPR and a lowest scaled PAPR.