This invention relates to the field of electrical signal treatment.
Digital-to-Analog Converters are widely used in the field of electrical signal treatment. In many devices, such as Compact Disk players, MP3-audio players or mobile phones, signals are treated in the digital domain. For this purpose, the signal is represented by a stream of digital words (each word containing a number of digital bits). At some point in the signal chain, the signal is converted from a digital representation to a “normal” analog representation by a Digital-to-Analog Converter.
Such a Digital-to-Analog Converter shows some inidealities that degrade the signal quality. Due to the finite number of bits in the digital words representing the signal, noise is added to the signal. This noise is known by the skilled professional as “Quantisation Noise”. Increasing the number of bits in the digital words allows reducing the Quantisation Noise. In general, increasing the number of bits by one reduces the quantisation noise by 6 dB.
However, there is a limit to this trade-off between wordlength and Quantisation Noise. In general, the relation, between number of bits in the digital words representing the signal, and the Quantisation Noise, is as depicted in
Due to this effect, it is difficult to create Digital-to-Analog Converters with a very low Quantisation Noise. Lowering the Quantisation Noise of Digital-to-Analog Converters is a continuing process, and the state-of-the-art is advancing gradually year after year.
The asymptotic lower limit of the Quantisation Noise is determined by non-idealities inside the Digital-to-Analog Converter, well-known by the skilled professional as “Integral Nonlinearity” (INL) and/or “Differential Nonlinearity” (DNL). These are generally due to fabrication tolerances on electrical components inside the Digital-to-Analog Converter and are generally different for each fabricated Digital-to-Analog Converter sample (in other words, two identically fabricated Digital-to-Analog Converters show different errors due to INL or DNL).
In many situations, it is sufficient to lower the quantisation noise spectrum in a given frequency band of interest. Especially for some frequency bands outside the signal frequency band, the requirements for low-noise can be difficult to reach. For example, a GSM phone uses different radio frequency bands for transmitting signals and for receiving signals. When transmitting a GSM signal (in the frequency band designated for signal transmissions), there is a very stringent specification on the maximum amount of noise that can be transmitted in the frequency band designated for signal receptions. When this transmitted signal is converted from digital representation to analog representation by a Digital-to-Analog Converter, the Quantisation Noise of the Digital-to-Analog Converter can contribute to the noise produced in the frequency band designated for signal receptions, and hence must be very low.
In such situation, it could be advantageous, instead of using a Digital-to-Analog Converter with very low Quantisation Noise, to relax the specifications on the Quantisation Noise and to use a signal filter. Such a filter can attenuate the unwanted noise in the frequency band with stringent noise requirements while not significantly attenuating the wanted signal in its frequency band of interest.
Filtering an electrical signal is a well-known technique and numerous applications exist. The higher the signal frequency, the more difficult, and hence more expensive, it becomes to create accurate filters for analog signals. This explains why recent architectures for transmitting radio-frequency signals tend to reduce the requirements for radio-frequency filters.
It is possible to filter signals in the digital domain. A well-known type of digital signal filter is known by the skilled professional as a “Finite Impulse Response” filter (FIR). In such a filter, the last “N” digital words representing the signal (N being some integer number) are stored in N digital memories, (3) and a weighted sum is calculated:
where at a given time instant “k”, y[k] is the digital output word of the FIR filter and x[k−N] to x[k−1] are the N digital words at the filter input that are immediately preceding time instant It “k”. By properly choosing the coefficients (2) α1 to αN, a filter characteristic can be realised that attenuates signals in a chosen frequency band. A possible realisation of such a FIR filter with subsequent Digital-to-Analog Conversion (1) is depicted in
However, because the filtering takes place before the Digital-to-Analog Conversion, the Quantisation Noise inherent to the Digital-to-Analog Converter is not filtered out.
An alternative approach is depicted in
However, in general, the noise due to INL or DNL differs from Digital-to-Analog Converter to Digital-to-Analog Converter and hence, this noise is NOT filtered. As a result, Quantisation Noise can be attenuated by the circuit of
The presented invention aims at solving this last issue.
Recently, a class of Digital-to-Analog Converters, generally denoted as “Direct Digital RF modulators” (DDRM) or ‘All-Digital Transmitters” emerged. Such a Digital-to-Analog Converter aims at generating a Radio-Frequency (RF) signal by combining the functions of Digital-to-Analog Converter and RF frequency Upconverter (also known as “mixer”). The Quantisation Noise principles and filtering techniques described above hold for this class of Digital-to-Analog Converters.
A DDRM incorporating a quantisation noise filter as depicted in
The present invention aims at solving this last issue, also for Direct Digital RF modulators.
The present invented aims at filtering the quantisation noise of an Digital-to-Analog Converter, including the noise due to INL and DNL.
An embodiment is described, where the invention is applied to a Direct Digital RF modulator, e.g. to be used in a GSM phone. The Quantisation Noise (including noise due to INL and DNL) transmitted in the frequency band intended for receiving signals is attenuated.
The invention is mainly based on the following principles as shown in
Let us start with the case where all coefficients α1 to αN (2) in expr. 1 are all equal to unity. During each conversion cycle, the N digital signal samples of a FIR filter, as stored in digital memories (3), are applied rapidly, one after the other, to the same Digital-to-Analog Converter (1). This can be accomplished, for example, by means of a digital multiplexer (4). When the conversion Speed of the Digital-to-Analog Converter is fast enough, an output signal is created in this way with an average value corresponding to:
This is identical to the result of expr. 1, except for a scaling factor.
In comparison with the circuit of
In this way, each input signal sample is used N times: It is applied N times to the same Digital-to-Analog Converter, once as first term of expr. 2, once as second term of expr. 2, etc. But because each time, the same Digital-to-Analog Converter is used to convert this input signal to an analog representation, the conversion suffers each time from an identical error due to INL or DNL. Hence, this error exhibits an attenuation due to the FIR filtering characteristic, identical to the attenuation of the signal. It is therefore possible to attenuate the noise due to INL and/or DNL in a given frequency band with stringent noise requirements.
More in general, it is also possible to apply each of the N input signal samples, as stored in the digital memories (3) of
In the case where all weighting coefficients α1 to αN in expr. 2 are positive numbers with rational ratios (the word “rational” indicates that the ratios can be expressed as a division p/q, where p and q are positive integer numbers), these coefficients can be implemented by applying each input signal in expr. 2 a number of times to the Digital-to-Analog Converter of
Negative values for the weighting coefficients coefficients α1 to αN in expr. 2 can also be handled: during each conversion cycle, each input signal in expr. 2 is applied a number of times to the Digital-to-Analog Converter of
These principles can be easily implemented in a Direct Digital RF modulator, because such modulator contains already clock signals with frequencies that are substantially larger than the baseband input signal frequencies.
Important timing characteristics are shown in
For further clarification, in
For further clarification,
The resulting filter frequency characteristic is drawn in
For further clarification, in
The principles of the invention described above can be successfully applied to a Direct Digital RF modulator (DDRM) e.g. for GSM applications. Such a DDRM is essentially a Digital-to-Analog Converter, as shown in
This principle is well-described in the literature and the skilled professional can understand that this circuit performs the functions of Digital-to-Analog Converter and RF upconversion mixer.
The circuit of
The timings of the different signals is detailed in
In order to further clarify the circuit operation, in
It is obvious to the skilled professional that the FIR filter shows an impulse response (9) as depicted in
The last factor in expr. 3 is due to the hold-function embedded in any Digital-to-Analog Converter.
This filter characteristic is depicted in
In order to further clarify the circuit operation:
Because the filtered signal is mixed with the Local Oscillator in a Dual-Sideband mixer, the resulting output current shows a filtered spectrum that is symmetrical around the Local Oscillator frequency:
Let us now further consider the example where the Local Oscillator frequency corresponds to a frequency in the band [890 MHz-915 MHz]. This is the GSM transmit band. From
It should be well understood that the drawings and embodiments presented in this document are given for explanatory purposes, and that other embodiments of the principles of the invention may exist.
It should also b understood that, although the embodiment described in this document is a DDRM, the principles can generally be applied to any Digital-to-Analog Converter.
Also, the principle of the time-interleaved FIR-filter of
Number | Date | Country | Kind |
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11447022 | Sep 2011 | EP | regional |
Filing Document | Filing Date | Country | Kind | 371c Date |
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PCT/BE2012/000043 | 9/11/2012 | WO | 00 | 3/18/2014 |