Method for computing a fast fourier transform and associated...

Electrical computers: arithmetic processing and calculating – Electrical digital calculating computer – Particular function performed

Reexamination Certificate

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Reexamination Certificate

active

06629117

ABSTRACT:

BACKGROUND OF INVENTION
1. Field of the Invention
The present invention generally relates to digital signal processors, and more particularly to novel method for computing a fast Fourier transform (FFT) in a digital signal processor, and an associated addressing circuit for addressing a data memory within a FFT processing circuit.
2. Discussion of the Related Art
As is known, digital signal processors (DSPs) are used in a wide variety of practical applications. Although circuit architectures may vary from chip to chip, DSPs are generally characterized by a multiplier component. As is known, multipliers perform the multiplication operation at an extremely high rate of speed (often within a single clock cycle). In comparison, a typically microprocessor architecture, which contains shifters adders and accumulators, performs a number of shift, add, and accumulate operations to carry out a multiplication operation. This manner of performing a single multiplication operation requires a relatively large number of clock cycles. As a result, arithmetic computations requiring many multiplication operations are preferably performed with a DSP.
As merely one example, DSP chips are used in electronic communications, and virtually all modems include an on-board DSP chip. As is known by those skilled in the communications art, the coding, filtering, error-correction, and other processes associated with electronic communications all demand relatively extensive mathematical computation. In order to achieve the desired speed for communications—and the faster, the better—DSP chips are used to perform this processing.
The FFTs are based on the discrete Fourier transforms. The algorithms are fast because they reuse the same roots of unity many times and thus minimize the number of multiplications. This reuse of the roots of unity reduces the complexity of the operation to N log N. Typical FFT algorithms achieve the decrease in complexity over the discrete Fourier transform algorithm by using these roots of unity and storing the intermediate values in global memory. The stored values are retrieved rather than explicitly using a multiplication to calculate them.
In this regard, the FFT processor may generally be characterized as a digital processor which repetitively performs the basic computations:
AW+B; AW−B,
where A and B are complex digital words, each initially associated with a different one of N digital samples, generally of the radar video signal the frequency spectrum of which is to be analyzed, and W is a complex digital word which serves as a weighting coefficient (also known as a twiddle factor). The above computations would be performed by processing such digital words in parallel form, as mentioned above, using a complex multiplier to perform the AW portion of the calculation, a storage means for storing such portion of the calculation, and a complex parallel adder and subtractor for adding and subtracting the stored portion of the calculation to and from, respectively, the B portion of the calculation.
Unfortunately, such algorithms often do not work well for low energy consumption implementations due to the global nature of the shared memory required for storage and lookup of the intermediate results. Current technology employs two approaches for architecting FFTs for high performance or low energy consumption. A complex switching network, called a butterfly network, is employed to forward results between parallel functional units in a pipelined manner. One obstacle to low energy consumption and higher performance relates to the memory architectures used to store and forward intermediate results. Global memories are notoriously slow and heavily loaded due to their shared nature. More significantly, however, the large number of intermediate reads and writes that are made to memory devices leads to increased power consumption.
Accordingly, there is a desire to provide an improved architecture for computing FFTs that overcomes these and other related shortcomings of the prior art.
SUMMARY OF INVENTION
Certain objects, advantages and novel features of the invention will be set forth in part in the description that follows and in part will become apparent to those skilled in the art upon examination of the following or may be learned with the practice of the invention. The objects and advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the appended claims.
To achieve the advantages and novel features, the present invention is generally directed to a novel method of computing a fast Fourier transform (FFT), and an associated circuit that controls the addressing of a data memory of the FFT processing circuit. Thus, in accordance with one aspect of the present invention, a method is provided for computing a fast Fourier transform of a series of data values. The novel method operates by computing all complex butterfly operations in a given stage of computations, before computing any of the complex butterfly operations in a subsequent stage. Further, and within any given computation stage, the method performs by computing all other complex butterfly operations in a given stage of computations having a twiddle factor equal to the first twiddle value of that stage, before computing any other complex butterfly operations in the given stage of computations. Thereafter, subsequent computations are performed in the same way. More particularly, after computing a first set of complex butterfly operations (each having the same twiddle value) in a given computation stage, a first complex butterfly operation (having a different twiddle value) of a second set of complex butterfly operations, is computed in that stage. Thereafter, all remaining complex butterfly operations (having the same value) in that stage will be computed. This methodology will be repeated until all butterfly operations are calculated in each stage.
In accordance with a related aspect of the present invention, a novel method is provided for computing a FFT of a series of data values comprising the steps of computing all complex butterfly operations in a first stage of computation, and computing a first complex butterfly operation in a next stage of computation, wherein the first complex butterfly operation includes a twiddle factor having a first value. Thereafter, the method computes all remaining complex butterfly operations in the said next stage of computation having twiddle factors equal to the first value, skipping intervening butterfly computations having values different than the first value. The method then computes a previously uncomputed next complex butterfly operation in the said next state of computation, wherein the said next complex butterfly operation includes a twiddle factor having a second value, said second value being different than the first value. Finally, the method computes all remaining complex butterfly operations in the said next stage of computation having twiddle factors equal to the second value, skipping intervening butterfly computations having values different than the second value.
In accordance with another aspect of the present invention, a circuit is provided for addressing a data memory in a system for computing a fast Fourier transform, the system having a data memory for storing data values and a coefficient memory for storing coefficient values. The addressing circuit includes a multiplexer having an output for addressing the data memory, a first input of the multiplexer defining a data memory read address and a second input of the multiplexer defining a data memory write address. The circuit also includes a write FIFO disposed in communication with the second input of the multiplexer, the write FIFO having an input that is connected to the first input of the multiplexer.
In one embodiment, the write FIFO is a four-deep FIFO, configured to store four addresses, before delivering the first stored address to the second input of the multiplexer. In addition, the addressing circuit further includes a

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