Efficient digital ITU-compliant zero-buffering DTMF...

Details Efficient digital ITU-compliant zero-buffering DTMF... Efficient digital ITU-compliant zero-buffering DTMF...

2001-12-07

2003-08-19

Eng, George (Department: 2643)

Telephonic communications

Supervisory or control line signaling

Signal receiver

C379S283000

Reexamination Certificate

active

06608896

ABSTRACT:

TECHNICAL FIELD
The present invention relates to methods and apparatus for the detection of DTMF symbols.
BACKGROUND OF THE INVENTION
Dual-tone multiple frequency (DTMF) signaling is used in telephone dialing, voice mail, and electronic banking systems. A DTMF signal corresponds to one of sixteen touchtone symbols (0-9,A-D, #, *) as shown in FIG.
1
. Each symbol is represented by one of four frequencies in a low frequency band and one of four frequencies in a higher frequency band. In
FIG. 1
the symbols are shown in a matrix format. Each symbol is represented by a frequency representing the column in which the symbol appears and by a frequency representing the row in which the symbol appears. The columns are represented by frequencies in a band between 1 kHz (kilo-Hertz) and 2 kHz, and the rows are represented by frequencies in a band between 500 Hz and 1 kHz. The first three columns of symbols form the telephone keypad layout familiar to consumers of voice telephone services. The last column of symbols are available for more particularized applications. Whenever a key of a touch-tone keypad is depressed, the high frequency and the low frequency corresponding to the symbol assigned to that key is generated and transmitted to a receiving device. The device that receives this dual tone signal must detect which one of the four low frequencies and which one of the four high frequencies have been received in order to determine which symbol has been transmitted.
The problem of DTMF signal detection is non-trivial for several reasons. The eight frequencies used to encode the symbols are within the spectrum of frequencies generated by voice-data. Therefore, when voice data is transmitted, symbol simulation, (also called digit simulation), may occur. A DTMF detector must be able to discriminate against these voice-simulated symbols. Also, the DTMF signal is attenuated by the transmission medium through which it is transmitted. Typical transmission media attenuate high frequencies more than low frequencies. Thus, the higher frequency in the dual tone pair may have significantly less power at the receiver than the low frequency in the pair. Conversely, devices do not typically generate all DTMF frequencies at the same power level. It is therefore possible for the lower frequency to be received at a lower power level than the high frequency. This disparity in power between the low and high frequency is called “twist”. Further, both tones must be detected in the presence of noise power which may be a significant fraction of the signal power of the received DTMF signal. An additional problem is that not all devices will generate the exact dual tone frequencies shown in
FIG. 1
because of poor design or system degradation. The DTMF receiver must be able to detect the DTMF signals at frequencies slightly offset from the nominal values while rejecting frequencies outside a given tolerance band. Because the nominal DTMF frequencies are closely spaced, the tolerance band must be very narrow. The problem of signal detection within narrow frequency bands is complicated by the fact that each signal is transmitted only for a short time duration of uncertain length with an uncertain delay time between transmission of successive symbols.
To standardize the performance of devices for DTMF signal generation and reception, the International Telecommunications Union (ITU) has developed a set of performance standards to which these devices should comply. These standards have achieved virtually worldwide acceptance, and refine the standards previously developed by Bell Communications Research, Inc. (“Bellcore”). The ITU standards are summarized in Table 1. Voice-simulated tones must be rejected as invalid tones. Signal frequencies that are within +/−1.5% of the nominal frequencies listed should be detected as valid DTMF tones. A signal frequency outside the band of +/−3.5% of a nominal frequency must be rejected as an invalid tone. Two twist parameters are also specified. The twist, which is the ratio of the low frequency power to the high frequency power in deci-Bels (dB), is specified to be greater than −4 dB and less than 8 dB. A positive twist value is a forward twist condition, which is the case when the low frequency signal power exceeds the high frequency power. A negative twist value is a reverse twist condition which exists when the high frequency signal power exceeds the low frequency signal power. When the twist is within the range of −4 dB to +8 db, the signal must be accepted as valid. Also, according to Bellcore standards, a valid DTMF signal must be detected if the signal-to-noise ratio (SNR) is at least 15 dB. In addition to frequency and power tolerances, temporal constraints are also imposed. A DTMF signal of duration at least 40 msec (milli-seconds) must be detected. A signal of duration 23 msec or less must be rejected. Also, if the time between the end of one DTMF signal and the beginning of the next successive DTMF signal, the interdigit time, at least than 40 msec, the signals must be distinguished as two distinct symbols. Conversely, a signal interruption of 10 msec or less must not cause detection of two separate tones.
Within the telephone network, DTMF signals are typically transmitted digitally at a sampling rate of about 8 kHz (8000 samples per second), to give sample durations of approximately 0.125 msec. One way to detect the presence of a valid DTMF signal is by digital-to-analog conversion followed by a bank of analog filters centered at the nominal DTMF frequencies. This method is not efficient because of the required conversion process and the size and complexity of analog filter implementation. It is more desirable to achieve DTMF signal detection using digital methods which can be implemented by an integrated circuit digital signal processor.
The most common digital methods for DTMF detection involve repetitively or iteratively computing the frequency content of the received signal over a finite duration of time referred to as a frame. For each frame, the power at each frequency of interest is determined. Once the power at each desired frequency is detected, a decision process, in the form of a series of tests, is usually employed to determine whether a valid DTMF signal has been detected. For example, voice-simulated DTMF signal tones can be discriminated by computing the signal power at the first harmonic of the fundamental DTMF signal tones listed in Table 1. A DTMF signal that is not voice-simulated will have little or no signal power at these harmonics, whereas the spectrum of a voice signal usually does generate these harmonics at significant power levels. To discriminate against voice-simulated tones, the power level at harmonic frequencies of the fundamental DTMF frequencies can be compared to specified threshold values. If the power in any of the harmonics exceeds the given threshold for that harmonic, a decision is made that an invalid detection has occurred. To determine if a valid tone has been detected, the DTMF frequency in the high band at which the power is greatest is determined. Similarly, the DTMF frequency in the low band at which the power is greatest is also determined. Each of these signals must exceed a certain threshold power or a decision is made that no valid DTMF signal has been detected within the current frame. For static thresholding, the threshold is a fixed, predetermined amount. For dynamic thresholding, the threshold is the minimum amount by which the power in the strongest tone in the band must exceed the power of the signals at the other three DTMF frequencies in the band. Further, the power of the strongest tone in the high band is compared to the power of the strongest tone in the low band to determine if the twist is within the range of −4 dB to 8 dB.
One approach to analyzing the frequency content of the received signal is by use of a Fast Fourier Transform (FFT) algorithm. The FFT would produce a sampled frequency spectrum with equally spaced samples. To obtain the frequency r

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