# Block Floating-Point FFT Functions¶

bfp_complex_s32_t *bfp_fft_forward_mono(bfp_s32_t *x)

Performs a forward real Discrete Fourier Transform on a real 32-bit sequence.

Performs an $$N$$-point forward real DFT on the real 32-bit BFP vector x, where $$N$$ is x->length. The operation is performed in-place, resulting in an $$N/2$$-element complex 32-bit BFP vector.

The operation performed is:

$\begin{split} X[f] = \sum_{n=0}^{N-1} \left( x[n]\cdot e^{-j2\pi fn/N} \right) \\ \text{ for } 0 \le f \le N/2 \end{split}$
where $$x[n]$$ is the BFP vector initially represented by x, and $$X[f]$$ is the DFT of $$x[n]$$ represented by the returned pointer.

The exponent, headroom, length and data contents of x are all updated by this function, though x->data will continue to point to the same address.

x->length must be a power of 2, and must be no larger than (1<<MAX_DIT_FFT_LOG2).

This function returns a bfp_complex_s32_t pointer. This points to the same address as . This is intended as a convenience for user code.

Upon completion, the spectrum data is encoded in x->data as specified for real DFTs in Spectrum Packing. That is, x->data[f] for 1 <= f < (x->length) represent $$X[f]$$ for $$1 \le f \lt (N/2)$$ and x->data[0] represents $$X[0] + j X[N/2]$$.

Example

// Initialize time domain data with samples.
int32_t buffer[N] = { ... };
bfp_s32_t samples;
bfp_s32_init(&samples, buffer, 0, N, 1);
// Perform the forward DFT
{
bfp_complex_s32_t* spectrum = bfp_fft_forward_mono(&samples);
// samples should no longer be used.
// Operate on frequency domain data using spectrum
...
// Perform the inverse DFT to go back to time domain
bfp_fft_inverse_mono(spectrum); // returns (bfp_s32_t*) which is the address of samples
}
// Use samples again to use new time domain data.
...


Parameters

x[inout] The BFP vector $$x[n]$$ to be DFTed.

Returns

Address of input BFP vector x, cast as bfp_complex_s32_t*.

bfp_s32_t *bfp_fft_inverse_mono(bfp_complex_s32_t *x)

Performs an inverse real Discrete Fourier Transform on a complex 32-bit sequence.

Performs an $$N$$-point inverse real DFT on the real 32-bit BFP vector x, where $$N$$ is 2*x->length. The operation is performed in-place, resulting in an $$N$$-element real 32-bit BFP vector.

The operation performed is:

$\begin{split} x[n] = \sum_{f=0}^{N/2} \left( X[f]\cdot e^{j2\pi fn/N} \right) \\ \text{ for } 0 \le n \lt N \end{split}$
where $$X[f]$$ is the BFP vector initially represented by x, and $$x[n]$$ is the IDFT of $$X[f]$$ represented by the returned pointer.

The exponent, headroom, length and data contents of x are all updated by this function, though x->data will continue to point to the same address.

x->length must be a power of 2, and must be no larger than (1<<(MAX_DIT_FFT_LOG2-1)).

This function returns a bfp_s32_t pointer. This points to the same address as . This is intended as a convenience for user code.

When calling, the spectrum data must be encoded in x->data as specified for real DFTs in Spectrum Packing. That is, x->data[f] for 1 <= f < (x->length) represent $$X[f]$$ for $$1 \le f \lt N/2$$, and x->data[0] represents $$X[0] + j X[N/2]$$.

Example

// Initialize time domain data with samples.
int32_t buffer[N] = { ... };
bfp_s32_t samples;
bfp_s32_init(&samples, buffer, 0, N, 1);
// Perform the forward DFT
{
bfp_complex_s32_t* spectrum = bfp_fft_forward_mono(&samples);
// samples should no longer be used.
// Operate on frequency domain data using spectrum
...
// Perform the inverse DFT to go back to time domain
bfp_fft_inverse_mono(spectrum); // returns (bfp_s32_t*) which is the address of samples
}
// Use samples again to use new time domain data.
...


Parameters

x[inout] The BFP vector $$X[f]$$ to be IDFTed.

Returns

Address of input BFP vector x, cast as bfp_s32_t*.

void bfp_fft_forward_complex(bfp_complex_s32_t *x)

Performs a forward complex Discrete Fourier Transform on a complex 32-bit sequence.

Performs an $$N$$-point forward complex DFT on the complex 32-bit BFP vector x, where $$N$$ is x->length. The operation is performed in-place.

The operation performed is:

$\begin{split} X[f] = \sum_{n=0}^{N-1} \left( x[n]\cdot e^{-j2\pi fn/N} \right) \\ \text{ for } 0 \le f \lt N \end{split}$
where $$x[n]$$ is the BFP vector initially represented by x, and $$X[f]$$ is the DFT of $$x[n]$$, also represented by x upon completion.

The exponent, headroom and data contents of x are updated by this function. x->data will continue to point to the same address.

x->length ( $$N$$) must be a power of 2, and must be no larger than (1<<MAX_DIT_FFT_LOG2).

Upon completion, the spectrum data is encoded in x as specified in Spectrum Packing. That is, x->data[f] for 0 <= f < (x->length) represent $$X[f]$$ for $$0 \le f \lt N$$.

Example

// Initialize complex time domain data with samples.
complex_s32_t buffer[N] = { ... };
bfp_complex_s32_t vector;
bfp_complex_s32_init(&vector, buffer, 0, N, 1);
// Perform the forward DFT
bfp_fft_forward_mono(&vector);
// Operate on frequency domain data
...
// Perform the inverse DFT to go back to time domain
bfp_fft_inverse_mono(&vector);
// vector contains (complex) time-domain data again
...


Parameters

x[inout] The BFP vector $$x[n]$$ to be DFTed.

void bfp_fft_inverse_complex(bfp_complex_s32_t *x)

Performs an inverse complex Discrete Fourier Transform on a complex 32-bit sequence.

Performs an $$N$$-point inverse complex DFT on the complex 32-bit BFP vector x, where $$N$$ is x->length. The operation is performed in-place.

The operation performed is:

$\begin{split} x[n] = \sum_{f=0}^{N-1} \left( X[f]\cdot e^{j2\pi fn/N} \right) \\ \text{ for } 0 \le f \lt N \end{split}$
where $$X[f]$$ is the BFP vector initially represented by x, and $$x[n]$$ is the DFT of $$X[f]$$, also represented by x upon completion.

The exponent, headroom and data contents of x are updated by this function. x->data will continue to point to the same address.

x->length must be a power of 2, and must be no larger than (1<<MAX_DIT_FFT_LOG2).

The data initially encoded in x are interpreted as specified in Spectrum Packing. That is, x->data[f] for 0 <= f < (x->length) represent $$X[f]$$ for $$0 \le f \lt N$$.

Example

// Initialize complex time domain data with samples.
complex_s32_t buffer[N] = { ... };
bfp_complex_s32_t vector;
bfp_complex_s32_init(&vector, buffer, 0, N, 1);
// Perform the forward DFT
bfp_fft_forward_mono(&vector);
// Operate on frequency domain data
...
// Perform the inverse DFT to go back to time domain
bfp_fft_inverse_mono(&vector);
// vector contains (complex) time-domain data again
...


Parameters

x[inout] The BFP vector $$x[n]$$ to be IDFTed.

void bfp_fft_forward_stereo(bfp_s32_t *a, bfp_s32_t *b, complex_s32_t scratch[])

Performs a forward real Discrete Fourier Transform on a pair of real 32-bit sequences.

Performs an $$N$$-point forward real DFT on the real 32-bit BFP vectors $$\bar a$$ and $$\bar b$$, where $$N$$ is a->length (which must equal b->length). The resulting spectra, $$\bar A$$ and $$\bar B$$, are placed in a and b. Each spectrum is a $$N/2$$-element complex 32-bit BFP vectors. To access the spectrum, the pointers a and b should be cast to bfp_complex_s32_t* following a call to this function.

The operation performed is:

$\begin{split} A[f] = \sum_{n=0}^{N-1} \left( a[n]\cdot e^{-j2\pi fn/N} \right) \text{ for } 0 \le f \le N/2 \\ B[f] = \sum_{n=0}^{N-1} \left( b[n]\cdot e^{-j2\pi fn/N} \right) \text{ for } 0 \le f \le N/2 \end{split}$
where $$a[n]$$ and $$b[n]$$ are the two time-domain sequences represented by input BFP vectors a and b, and $$A[f]$$ and $$B[f]$$ are the DFT of $$a[n]$$ and $$b[n]$$ respectively.

a->length ( $$N$$) must be equal to b->length, must be a power of 2, and must be no larger than(1<<MAX_DIT_FFT_LOG2).

The parameters and are used as both inputs and outputs. To access the result of the FFT, a and b should be cast to bfp_complex_s32_t*. The structs’ metadata (e.g. exp, hr, length) are updated by this function to reflect this change of interpretation. The bfp_s32_t references should be considered corrupted after this call (at least until bfp_fft_inverse_stereo() is called).

The spectrum data is encoded in a->data and b->data as specified for real DFTs in Spectrum Packing. That is, a->data[f] for 1 <= f < (a->length) represent $$A[f]$$ for $$1 \le f \lt (N/2)$$ and a->data[0] represents $$A[0] + j A[N/2]$$. Likewise for the encoding of b->data.

This function requires a scratch buffer large enough to contain $$N$$ complex_s32_t elements.

Deprecated:
Example

// Initialize time domain data with samples.
int32_t bufferA[N] = { ... };
int32_t bufferB[N] = { ... };
complex_s32_t scratch[N]; // scratch buffer -- contents don't matter
bfp_s32_t channel_A, channel_B;
bfp_s32_init(&channel_A, buffer, 0, N, 1);
bfp_s32_init(&channel_B, buffer, 0, N, 1);

// Perform the forward DFT
bfp_fft_forward_stereo(&channel_A, &channel_B, scratch);

// channel_A and channel_B should now be considered clobbered as the structs are now
// effectively bfp_complex_s32_t
bfp_complex_s32_t* chanA = (bfp_complex_s32_t*) &channel_A;
bfp_complex_s32_t* chanB = (bfp_complex_s32_t*) &channel_B;

// Operate on frequency domain data using chanA and chanB
...
// Perform the inverse DFT to go back to time domain
bfp_fft_inverse_stereo(&chanA, &chanB, scratch);

// Use channel_A and channel_B again to use new time domain data.
...


// Suppress this from generated documentation for the time being //

Note

Use of this function is not currently recommended. It functions correctly, but a recent change in this library’s API (namely, dropping support for channel-pair vectors) means this function is no more computationally efficient than calling bfp_fft_forward_mono() on each input vector separately. Additionally, this function currently requires a scratch buffer, whereas the mono FFT does not.

Parameters
• a[inout] [Input] Time-domain BFP vector $$\bar a$$. [Output] Frequency domain BFP vector $$\bar A$$

• b[inout] [Input] Time-domain BFP vector $$\bar b$$. [Output] Frequency domain BFP vector $$\bar B$$

• scratch – Scratch buffer of at least a->length complex_s32_t elements

void bfp_fft_inverse_stereo(bfp_complex_s32_t *A_fft, bfp_complex_s32_t *B_fft, complex_s32_t scratch[])

Performs an inverse real Discrete Fourier Transform on a pair of complex 32-bit sequences.

Performs an $$N$$-point inverse real DFT on the 32-bit complex BFP vectors $$\bar A$$ and $$\bar B$$ (A_fft and B_fft respectively), where $$N$$ is A_fft->length . The resulting real signals, $$\bar a$$ and $$\bar b$$, are placed in A_fft and B_fft. Each time-domain result is a $$N/2$$-element real 32-bit BFP vectors. To access the spectrum, the pointers A_fft and B_fft should be cast to bfp_s32_t* following a call to this function.

The operation performed is:

$\begin{split} a[n] = \sum_{f=0}^{N/2-1} \left( A[f]\cdot e^{j2\pi fn/N} \right) \text{ for } 0 \le n \lt N \\ b[n] = \sum_{f=0}^{N/2-1} \left( B[f]\cdot e^{j2\pi fn/N} \right) \text{ for } 0 \le n \lt N \end{split}$
where $$A[f]$$ and $$B[f]$$ are the frequency spectra represented by BFP vectors A_fft and B_fft, and $$a[n]$$ and $$b[n]$$ are the IDFT of $$A[f]$$ and $$B[f]$$.

A_fft->length ( $$N$$) must be a power of 2, and must be no larger than (1<<(MAX_DIT_FFT_LOG2-1)).

The parameters and are used as both inputs and outputs. To access the result of the IFFT, A_fft and B_fft should be cast to bfp_s32_t*. The structs’ metadata (e.g. exp, hr, length) are updated by this function to reflect this change of interpretation. The bfp_complex_s32_t references should be considered corrupted after this call.

The spectrum data encoded in A_fft->data and A_fft->data are interpreted as specified for real DFTs in Spectrum Packing. That is, A_fft->data[f] for 1 <= f < (a->length) represent $$A[f]$$ for $$1 \le f \lt (N/2)$$ and A_fft->data[0] represents $$A[0] + j A[N/2]$$. Likewise for the encoding of B_fft->data.

This function requires a scratch buffer large enough to contain $$2N$$ complex_s32_t elements.

Deprecated:
Example

// Initialize time domain data with samples.
int32_t bufferA[N] = { ... };
int32_t bufferB[N] = { ... };
complex_s32_t scratch[N]; // scratch buffer -- contents don't matter
bfp_s32_t channel_A, channel_B;
bfp_s32_init(&channel_A, buffer, 0, N, 1);
bfp_s32_init(&channel_B, buffer, 0, N, 1);

// Perform the forward DFT
bfp_fft_forward_stereo(&channel_A, &channel_B, scratch);

// channel_A and channel_B should now be considered clobbered as the structs are now
// effectively bfp_complex_s32_t
bfp_complex_s32_t* chanA = (bfp_complex_s32_t*) &channel_A;
bfp_complex_s32_t* chanB = (bfp_complex_s32_t*) &channel_B;

// Operate on frequency domain data using chanA and chanB
...
// Perform the inverse DFT to go back to time domain
bfp_fft_inverse_stereo(&chanA, &chanB, scratch);

// Use channel_A and channel_B again to use new time domain data.
...


// Suppress this from generated documentation for the time being //

Note

Use of this function is not currently recommended. It functions correctly, but a recent change in this library’s API (namely, dropping support for channel-pair vectors) means this function is no more computationally efficient than calling bfp_fft_forward_mono() on each input vector separately. Additionally, this function currently requires a scratch buffer, whereas the mono FFT does not.

Parameters
• A_fft[inout] [Input] Freq-domain BFP vector $$\bar A$$. [Output] Time domain BFP vector $$\bar b$$

• B_fft[inout] [Input] Freq-domain BFP vector $$\bar b$$. [Output] Time domain BFP vector $$\bar b$$

• scratch – Scratch buffer of at least 2*A_fft->length complex_s32_t elements

void bfp_fft_unpack_mono(bfp_complex_s32_t *x)

Unpack the spectrum resulting from bfp_fft_forward_mono().

The DFT of a real signal is periodic with period FFT_N (the FFT length) and has a complex conjugate symmetry about index 0. These two properties guarantee that the imaginary part of both the DC component (index 0) and the Nyquist component (index FFT_N/2) of the spectrum are zero. To compute the forward FFT in-place, bfp_fft_forward_mono() packs the real part of the Nyquist rate component of the output spectrum into the imaginary part of the DC component.

This may be undesirable when operating on the signal’s complex spectrum. Use this function to unpack the Nyquist component. This function will also adjust the BFP vector’s length to reflect this unpacking.

NOTE: If you intend to unpack the spectrum using this function, the buffer for the time-domain BFP vector must have length FFT_N+2, rather than FFT_N (int32_t elements), but these should NOT be reflected in the time-domain BFP vector’s length` field.

\begin{split}\begin{align*} & Re\{x_{N/2}\} && \leftarrow Im\{x_0\} \\ & Im\{x_0\} && \leftarrow 0 \\ & Im\{x_{N/2}\} && \leftarrow 0 \\ & x.length && \leftarrow x.length + 1 \end{align*}\end{split}

NOTE: Before bfp_fft_inverse_mono() may be applied, bfp_fft_pack_mono() must be called, as the inverse FFT expects the data to be packed.

Parameters

x[inout] The spectrum to be unpacked

void bfp_fft_pack_mono(bfp_complex_s32_t *x)

Pack the spectrum resulting from bfp_fft_unpack_mono().

This function applies the reverse process of bfp_fft_unpack_mono(), to prepare it for an inverse FFT using bfp_fft_inverse_mono().