Pseudorandom signal sampler for relaxed design of multistandard radio receiver

Rebai, Chiheb; Ben-Romdhane, Manel; Desgreys, Patricia; Loumeau, Patrick; Ghazel, Adel

doi:10.1016/j.mejo.2009.01.010

Cited by 12 publications

(11 citation statements)

References 16 publications

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“…Based on the signal spectrum characteristics, both MC and DSB samplers start sampling at f mc =f dsb =145MHz with p mc =p dsb =31, see Figs. [6][7]. Note that f mc and f dsb represent the average sampling frequencies for MC and DSB samplers, respectively.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Since in practice, it is impossible to design a random sampler, the sampler proposed in [7], [8] are, thus, pseudo-random samplers. In this paper, we propose to use a pseudo-random sampler in conjunction with MC sampling.…”

Section: A Non-uniform Sampler Blockmentioning

confidence: 99%

“…Thus, unlike the p branches in the usual MC sampler shown in Fig.1, the input of the DSB-NUS is composed of a single branch non-uniform sampler. The input of our mono-branch DSB sampler is designed as an Additive Pseudo-Random Sampler (APRS) [7].…”

Section: A Non-uniform Sampler Blockmentioning

confidence: 99%

“…Thus, for a given L, the non-uniform sampler operating at an optimal average rate depends only on the number of active band. As a result, (7) can be rewritten as…”

Section: Optimal Average Sampling Rate Search Blockmentioning

confidence: 99%

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Dynamic Single Branch Non-Uniform Sampler

Traore

Aziz

Guennec

2013

2013 18th International Conference on Digital Signal Processing (DSP)

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We consider the problem of designing an effective sampling scheme for sparse multi-band signals. Based on previous results on periodic non-uniform sampling (Multi-coset) and recent advances in Compressive Sensing (CS), we propose a new sampling scheme, the Dynamic Single Branch Non-uniform Sampler (DSB-NUS). Our scheme estimates the spectral support using non-uniform spectrum sensing technique to minimize the average sampling rate, thereby reducing the number of samples as well as energy consumption. In this paper, we show through simulation results that compared to existing multi-coset based samplers, our proposed sampler provides superior performance, both in terms of sampling rate and energy consumption. Moreover, we show that our proposed sampler is not constrained by the inflexibility of harware circuitry and is easily reconfigurable.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: A Non-uniform Sampler Blockmentioning

confidence: 99%

Section: A Non-uniform Sampler Blockmentioning

confidence: 99%

“…Thus, for a given L, the non-uniform sampler operating at an optimal average rate depends only on the number of active band. As a result, (7) can be rewritten as…”

Section: Optimal Average Sampling Rate Search Blockmentioning

confidence: 99%

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Dynamic Single Branch Non-Uniform Sampler

Traore

Aziz

Guennec

2013

2013 18th International Conference on Digital Signal Processing (DSP)

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“…All of these are corrected digitally in DSP as explained in [1][2]. We propose in previous work to non-uniformly control the Analog-to-Digital Converter in multistandard receiver architecture [3].…”

Section: Nus-based Multistandard Homodyne Receivermentioning

confidence: 99%

Flexible baseband analog front-end for NUS based multistandard receiver

Ben-Romdhane

Rebai²,

Desgreys

et al. 2009

2009 Joint IEEE North-East Workshop on Circuits and Systems and TAISA Conference

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Non-uniform sampling (NUS) controlling baseband analog front-end in a Software Defined Radio multistandard receiver was previously proposed in our works. Non-uniform sampling offers the alias-free sampling feature. Non-uniform sampling based multistandard receiver relaxes Anti-Aliasing Filter (AAF), relaxes automatic gain control circuit and reduces power consumption of the analog-to-digital converter. In this paper, for a finite number of samples, we adopt Bilinskis's theoretical results to multistandard radio signals. The obtained NUS attenuations are relevant to design a flexible AAF. Some comparative AAF orders are presented to figure out NUS advantages in spite of finite number of samples.

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