Front End - Revision history

Claudia.Prajanu at 19:45, 2 September 2018

2018-09-02T19:45:50Z

← Older revision		Revision as of 19:45, 2 September 2018
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	*'''Filtering and amplification''': these stages are necessary to ensure low noise and out-of-band rejection in the received signals, as well as amplification stages to compensate for transmission losses.		*'''Filtering and amplification''': these stages are necessary to ensure low noise and out-of-band rejection in the received signals, as well as amplification stages to compensate for transmission losses.

	*'''Down-conversion''': The front end is responsible for down-converting the signal, whether using ''direct conversion''<ref>http://www.gpsworld.com~~/gnss-system/galileo/pulling-wideband-7053~~</ref> techniques, to convert the RF spectrum directly to baseband, or ''heterodyning''<ref>[[wikipedia:Heterodyne receiver]]</ref> approaches, where typically a multi-stage approach is used to shift the spectrum to intermediate frequencies (IF), with the appropriate band filtering, ultimately converting the IF signals to baseband<ref>[[wikipedia:Digital down converter]]</ref>.		*'''Down-conversion''': The front end is responsible for down-converting the signal, whether using ''direct conversion''<ref>http://www.gpsworld.com</ref> techniques, to convert the RF spectrum directly to baseband, or ''heterodyning''<ref>[[wikipedia:Heterodyne receiver]]</ref> approaches, where typically a multi-stage approach is used to shift the spectrum to intermediate frequencies (IF), with the appropriate band filtering, ultimately converting the IF signals to baseband<ref>[[wikipedia:Digital down converter]]</ref>.

	*'''Quantization''': The incoming signals are digitized through ''analog to digital converters''<ref>[[wikipedia:Analog-to-digital converter]]</ref> (ADC), ensuring that quantization errors and dynamic ranges are appropriate to accommodate the signal's characteristics.		*'''Quantization''': The incoming signals are digitized through ''analog to digital converters''<ref>[[wikipedia:Analog-to-digital converter]]</ref> (ADC), ensuring that quantization errors and dynamic ranges are appropriate to accommodate the signal's characteristics.

Filipe.Pelica: Included editor logo.

2014-09-18T16:37:23Z

Included editor logo.

← Older revision		Revision as of 16:37, 18 September 2014
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	\|Level=Advanced		\|Level=Advanced
	\|YearOfPublication=2011		\|YearOfPublication=2011
			\|Logo=GMV
	\|Title={{PAGENAME}}		\|Title={{PAGENAME}}
	}}		}}

James.Curran: /* Signal Bandwidth */

2012-11-12T23:53:39Z

Signal Bandwidth

← Older revision		Revision as of 23:53, 12 November 2012
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	Latest works on the effect of bandwidth and quantization on the correlation losses of the receiver can be found in <ref>"Analytical Model for GNSS Receiver Implementation Losses", Hegarty, Journal of Navigation 2011, ~~J.Curran, D.Borio, C.C.Murphy~~</ref>, <ref>"Front-End Filtering and Quantization Effects on GNSS Signal Processing," IEEE Wireless VITAE, Aalborg, Denmark, May 2009</ref>.		Latest works on the effect of bandwidth and quantization on the correlation losses of the receiver can be found in <ref>"Analytical Model for GNSS Receiver Implementation Losses", Hegarty, Journal of Navigation 2011, </ref>, <ref>"Front-End Filtering and Quantization Effects on GNSS Signal Processing," J.Curran, D.Borio, C.C.Murphy, IEEE Wireless VITAE, Aalborg, Denmark, May 2009</ref>.

	==From RF to Baseband==		==From RF to Baseband==

Carlos.Lopez at 11:01, 23 February 2012

2012-02-23T11:01:06Z

← Older revision		Revision as of 11:01, 23 February 2012
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	{{Article Infobox2		{{Article Infobox2
	\|Category=Receivers		\|Category=Receivers
	\|Editors=GMV ~~A.D.~~		\|Editors=GMV
	\|Level=Advanced		\|Level=Advanced
	\|YearOfPublication=2011		\|YearOfPublication=2011

Carlos.Lopez at 10:34, 23 February 2012

2012-02-23T10:34:31Z

← Older revision		Revision as of 10:34, 23 February 2012
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	{{Article Infobox2		{{Article Infobox2
	\|Category=Receivers		\|Category=Receivers
	\|~~Title={{PAGENAME}}~~		\|Editors=GMV A.D.
	~~\|Authors~~=GMV
	\|Level=Advanced		\|Level=Advanced
	\|YearOfPublication=2011		\|YearOfPublication=2011
	\|~~Logo~~=~~GMV~~		\|Title={{PAGENAME}}
	}}		}}
	A GNSS signal is captured through the receiver's [[Antennas\|antenna]], and is fed to the front end section. The front end is then responsible for "preparing" the received signals for [[Digital Signal Processing\|signal processing]] tasks, and many different implementations can achieve the desired results. As always, some requirement and trade-off analysis is needed when designing a front-end for GNSS receivers, depending on the application at hand. Figure 1 illustrates a typical front end structure in GNSS receivers.		A GNSS signal is captured through the receiver's [[Antennas\|antenna]], and is fed to the front end section. The front end is then responsible for "preparing" the received signals for [[Digital Signal Processing\|signal processing]] tasks, and many different implementations can achieve the desired results. As always, some requirement and trade-off analysis is needed when designing a front-end for GNSS receivers, depending on the application at hand. Figure 1 illustrates a typical front end structure in GNSS receivers.

Teresa.Ferreira: /* Quantization and Sampling */

2011-11-21T11:41:10Z

Quantization and Sampling

← Older revision		Revision as of 11:41, 21 November 2011
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	The choice of the quantization method and range depends on the noise characteristics. In GNSS receivers, the power levels of the input signals are low, so the ADC quantization sees only noise-like signals at the input.		The choice of the quantization method and range depends on the noise characteristics. In GNSS receivers, the power levels of the input signals are low, so the ADC quantization sees only noise-like signals at the input.
	[[File:nyquist_and_aliasing.png\|left\|thumb\|220px\|'''''Figure 4:''''' Illustration of Nyquist theorem: Original signal (top), fs respects Nyyquist Theorem (middle) and aliasing effects when Nyquist theorem is not respected (bottom).]]		[[File:nyquist_and_aliasing.png\|left\|thumb\|220px\|'''''Figure 4:''''' Illustration of Nyquist theorem: Original signal (top), fs respects Nyyquist Theorem (middle) and aliasing effects when Nyquist theorem is not respected (bottom).]]
	~~A uniform~~ quantization ~~with~~ <math>k\,</math> ~~bits has~~ <~~math~~>~~2k-1\~~,</~~math~~> ~~edges~~, ~~and these quantization edges~~ (~~thresholds~~) ~~must be optimized in terms of the noise standard deviation <math>\sigma\~~,</~~math~~> ~~and the maximum quantization threshold L, given by~~:		There is an optimal ratio between the maximum quantization threshold L, and the noise standard deviation <math>\sigma\,</math>, that minimizes SNR degradation at correlator output,<ref name="Bastide">F. Bastide, D. Akos, C. Macabiau, B. Roturier, <i>“Automatic Gain Control (AGC) as an Interference Assessment Tool”</i>, Proceedings of the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS/GNSS 2003), September 9 - 12, 2003, Portland, OR, Page(s): 2042 – 2053.</ref>:


	<math>k_{opt} = \frac{L}{\sigma}\,</math>		<math>k_{opt} = \frac{L}{\sigma}\,</math>


	Regarding the number of bits to use, the signal degradation is about 1.5 dB when using 2-bit quantization, increasing to 3.5 dB when using 1-bit quantization<ref name="Bastide">F. Bastide, D. Akos, C. Macabiau, B. Roturier, <i>“Automatic Gain Control (AGC) as an Interference Assessment Tool”</i>, Proceedings of the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS/GNSS 2003), September 9 - 12, 2003, Portland, OR, Page(s): 2042 – 2053.</ref>. For GNSS signals and receivers, however, these are quite affordable losses for decreasing the number of quantization bits. Although using 1-bit data also discards the need for an AGC (therefore simplifying the hardware), enabling gain control through an AGC system may still help in interference mitigation.		Regarding the number of bits to use, the signal degradation is about 1.5 dB when using 2-bit quantization, increasing to 3.5 dB when using 1-bit quantization<ref name="Bastide"></ref>. For GNSS signals and receivers, however, these are quite affordable losses for decreasing the number of quantization bits. Although using 1-bit data also discards the need for an AGC (therefore simplifying the hardware), enabling gain control through an AGC system may still help in interference mitigation.

	When the ADC samples the input signal (typically at a lower IF frequency after down-conversion), the ''sampling frequency'' <math>f_s,</math> should be carefully chosen. In fact, for GNSS signals,<math>f_s,</math> should not be a multiple of 1.023 MHz. As stated by the Nyquist–Shannon sampling theorem<ref>[[wikipedia:Nyquist–Shannon sampling theorem]]</ref>, the sampling frequency <math>f_s\,</math>, needed to represent and reproduce the signal, is related to the one-sided baseband bandwidth <math>B,</math> by:		When the ADC samples the input signal (typically at a lower IF frequency after down-conversion), the ''sampling frequency'' <math>f_s,</math> should be carefully chosen. In fact, for GNSS signals,<math>f_s,</math> should not be a multiple of 1.023 MHz. As stated by the Nyquist–Shannon sampling theorem<ref>[[wikipedia:Nyquist–Shannon sampling theorem]]</ref>, the sampling frequency <math>f_s\,</math>, needed to represent and reproduce the signal, is related to the one-sided baseband bandwidth <math>B,</math> by:

Teresa.Ferreira: /* Quantization and Sampling */

2011-11-21T11:23:17Z

Quantization and Sampling

← Older revision		Revision as of 11:23, 21 November 2011
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	The choice of the quantization method and range depends on the noise characteristics. In GNSS receivers, the power levels of the input signals are low, so the ADC quantization sees only noise-like signals at the input.		The choice of the quantization method and range depends on the noise characteristics. In GNSS receivers, the power levels of the input signals are low, so the ADC quantization sees only noise-like signals at the input.
	[[File:nyquist_and_aliasing.png\|left\|thumb\|220px\|'''''Figure 4:''''' Illustration of Nyquist theorem: Original signal (top), fs respects Nyyquist Theorem (middle) and aliasing effects when Nyquist theorem is not respected (bottom).]]		[[File:nyquist_and_aliasing.png\|left\|thumb\|220px\|'''''Figure 4:''''' Illustration of Nyquist theorem: Original signal (top), fs respects Nyyquist Theorem (middle) and aliasing effects when Nyquist theorem is not respected (bottom).]]
	A uniform quantization with <math>k\,</math> bits has <math>2k-1\,</math> edges, and these quantization edges (thresholds) must be optimized in terms of the noise standard deviation <math>\sigma\,</math>, given by:		A uniform quantization with <math>k\,</math> bits has <math>2k-1\,</math> edges, and these quantization edges (thresholds) must be optimized in terms of the noise standard deviation <math>\sigma\,</math> and the maximum quantization threshold L, given by:


	<math>k = \frac{L}{\sigma}\,</math>		<math>k_{opt} = \frac{L}{\sigma}\,</math>

Teresa.Ferreira: /* Signal Bandwidth */

2011-11-21T11:07:25Z

Signal Bandwidth

← Older revision		Revision as of 11:07, 21 November 2011
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	Latest works on the effect of BW and quantization on the correlation losses of the receiver/ Analytical Model for GNSS Receiver Implementation Losses ~~can be found here: <ref>~~Hegarty, Journal of Navigation 2011, J.Curran, D.Borio, C.C.Murphy</ref>, <ref>"Front-End Filtering and Quantization Effects on GNSS Signal Processing," IEEE Wireless VITAE, Aalborg, Denmark, May 2009</ref>.		Latest works on the effect of bandwidth and quantization on the correlation losses of the receiver can be found in <ref>"Analytical Model for GNSS Receiver Implementation Losses", Hegarty, Journal of Navigation 2011, J.Curran, D.Borio, C.C.Murphy</ref>, <ref>"Front-End Filtering and Quantization Effects on GNSS Signal Processing," IEEE Wireless VITAE, Aalborg, Denmark, May 2009</ref>.

	==From RF to Baseband==		==From RF to Baseband==

Teresa.Ferreira: /* Signal Bandwidth */

2011-11-21T11:06:00Z

Signal Bandwidth

← Older revision		Revision as of 11:06, 21 November 2011
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	Dual-frequency receivers used dual-band antennas, and their front end bandwidth is dimensioned to the envisaged application, needed accuracy, and available technology. For example, a survey receiver will need larger bandwidths to achieve accurate results, whereas a low-cost receiver may only have an antenna/front end bandwidth of around 2 MHz, but still receive enough signal power to determine position with an accuracy within meters. Although the receiver’s antenna/front-end bandwidth is directly proportional to the accuracy required for the application, it is also directly proportional to the processing load and power consumption for portable solutions.		Dual-frequency receivers used dual-band antennas, and their front end bandwidth is dimensioned to the envisaged application, needed accuracy, and available technology. For example, a survey receiver will need larger bandwidths to achieve accurate results, whereas a low-cost receiver may only have an antenna/front end bandwidth of around 2 MHz, but still receive enough signal power to determine position with an accuracy within meters. Although the receiver’s antenna/front-end bandwidth is directly proportional to the accuracy required for the application, it is also directly proportional to the processing load and power consumption for portable solutions.

	Latest works on the effect of BW and quantization on the correlation losses of the receiver/ Analytical Model for GNSS Receiver Implementation Losses can be found here: <ref>Hegarty, Journal of Navigation 2011, J.Curran, D.Borio, C.C.Murphy</ref>, <ref>"Front-End Filtering and Quantization Effects on GNSS Signal Processing," IEEE Wireless VITAE, Aalborg, Denmark, May 2009</ref>
			Latest works on the effect of BW and quantization on the correlation losses of the receiver/ Analytical Model for GNSS Receiver Implementation Losses can be found here: <ref>Hegarty, Journal of Navigation 2011, J.Curran, D.Borio, C.C.Murphy</ref>, <ref>"Front-End Filtering and Quantization Effects on GNSS Signal Processing," IEEE Wireless VITAE, Aalborg, Denmark, May 2009</ref>.

	==From RF to Baseband==		==From RF to Baseband==

Teresa.Ferreira: /* Signal Bandwidth */

2011-11-21T11:05:30Z

Signal Bandwidth

← Older revision		Revision as of 11:05, 21 November 2011
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	Dual-frequency receivers used dual-band antennas, and their front end bandwidth is dimensioned to the envisaged application, needed accuracy, and available technology. For example, a survey receiver will need larger bandwidths to achieve accurate results, whereas a low-cost receiver may only have an antenna/front end bandwidth of around 2 MHz, but still receive enough signal power to determine position with an accuracy within meters. Although the receiver’s antenna/front-end bandwidth is directly proportional to the accuracy required for the application, it is also directly proportional to the processing load and power consumption for portable solutions.		Dual-frequency receivers used dual-band antennas, and their front end bandwidth is dimensioned to the envisaged application, needed accuracy, and available technology. For example, a survey receiver will need larger bandwidths to achieve accurate results, whereas a low-cost receiver may only have an antenna/front end bandwidth of around 2 MHz, but still receive enough signal power to determine position with an accuracy within meters. Although the receiver’s antenna/front-end bandwidth is directly proportional to the accuracy required for the application, it is also directly proportional to the processing load and power consumption for portable solutions.

			Latest works on the effect of BW and quantization on the correlation losses of the receiver/ Analytical Model for GNSS Receiver Implementation Losses can be found here: <ref>Hegarty, Journal of Navigation 2011, J.Curran, D.Borio, C.C.Murphy</ref>, <ref>"Front-End Filtering and Quantization Effects on GNSS Signal Processing," IEEE Wireless VITAE, Aalborg, Denmark, May 2009</ref>

	==From RF to Baseband==		==From RF to Baseband==