Efficient reconfigurable scheme for the recovery of sub-Nyquist sampled sparse multi-band signals

Pillai, Anu Kalidas Muralidharan; Johansson, Håkan

doi:10.1109/globalsip.2013.6737146

Cited by 3 publications

(8 citation statements)

References 7 publications

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“…Submitted to the IEEE Transactions on Signal Processing, 2015. This is an extension of a conference publication [90].…”

Section: Included Papersmentioning

confidence: 91%

Signal Reconstruction Algorithms for Time-Interleaved ADCs

Pillai¹

2015

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An analog-to-digital converter (ADC) is a key component in many electronic systems. It is used to convert analog signals to the equivalent digital form. The conversion involves sampling which is the process of converting a continuous-time signal to a sequence of discrete-time samples, and quantization in which each sampled value is represented using a finite number of bits. The sampling rate and the effective resolution (number of bits) are two key ADC performance metrics. Today, ADCs form a major bottleneck in many applications like communication systems since it is difficult to simultaneously achieve high sampling rate and high resolution. Among the various ADC architectures, the time-interleaved analog-to-digital converter (TI-ADC) has emerged as a popular choice for achieving very high sampling rates and resolutions. At the principle level, by interleaving the outputs of M identical channel ADCs, a TI-ADC could achieve the same resolution as that of a channel ADC but with M times higher bandwidth. However, in practice, mismatches between the channel ADCs result in a nonuniformly sampled signal at the output of a TI-ADC which reduces the achievable resolution. Often, in TI-ADC implementations, digital reconstructors are used to recover the uniform-grid samples from the nonuniformly sampled signal at the output of the TI-ADC. Since such reconstructors operate at the TI-ADC output rate, reducing the number of computations required per corrected output sample helps to reduce the power consumed by the TI-ADC. Also, as the mismatch parameters change occasionally, the reconstructor should support online reconfiguration with minimal or no redesign. Further, it is advantageous to have reconstruction schemes that require fewer coefficient updates during reconfiguration. In this thesis, we focus on reducing the design and implementation complexities of nonrecursive finite-length impulse response (FIR) reconstructors. We propose efficient reconstruction schemes for three classes of nonuniformly sampled signals that can occur at the output of TI-ADCs.iii Firstly, we consider a class of nonuniformly sampled signals that occur as a result of static timing mismatch errors or due to channel mismatches in TI-ADCs. For this type of nonuniformly sampled signals, we propose three reconstructors which utilize a two-rate approach to derive the corresponding single-rate structure. The two-rate based reconstructors move part of the complexity to a symmetric filter and also simplifies the reconstruction problem. The complexity reduction stems from the fact that half of the impulse response coefficients of the symmetric filter are equal to zero and that, compared to the original reconstruction problem, the simplified problem requires only a simpler reconstructor.Next, we consider the class of nonuniformly sampled signals that occur when a TI-ADC is used for sub-Nyquist cyclic nonuniform sampling (CNUS) of sparse multi-band signals. Sub-Nyquist sampling utilizes the sparsities in the analog signal to sample the signal at a lowe...

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“…Submitted to the IEEE Transactions on Signal Processing, 2015. This is an extension of a conference publication [90].…”

Section: Included Papersmentioning

confidence: 91%

Signal Reconstruction Algorithms for Time-Interleaved ADCs

Pillai¹

2015

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“…We have observed that the problem of reconstructing missing samples is similar to that of the reconstruction problem in sub-Nyquist sampled sparse multi-band signals considered in [8]. Assume that the whole Nyquist band is divided into N sub-bands of equal width π/N.…”

Section: Proposed Reconstructormentioning

confidence: 99%

A sub-band based reconstructor for M-channel time-interleaved ADCS with missing samples

Pillai

Johansson

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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This paper proposes a scheme for the recovery of a uniformly sampled sequence from the output of a time-interleaved analog-to-digital converter (TI-ADC) with static time-skew errors and missing samples. Nonuniform sampling occurs due to timing mismatches between the individual channel ADCs and also due to missing input samples as some of the sampling instants are reserved for estimating the mismatches in the TI-ADC. In addition to using a non-recursive structure, the proposed reconstruction scheme supports online reconfigurability and reduces the computational complexity of the reconstructor as compared to a previous solution.

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“…Parts of this work have been presented at a conference [18] where only the basic concept was outlined without giving any proofs. However, in order to get further insight and understanding of the efficient reconfigurable scheme, in Section IV we show that the reconstruction problem can be expressed in terms of the proposed analysis and synthesis FBs.…”

Section: A Contributions and Outline Of The Papermentioning

confidence: 99%

“…Based on this, we introduce a reconfigurable reconstruction scheme in Section V. Using complexity expressions for the proposed reconstructor and the polyphase implementation of the straightforward scheme in [7], we show that order-ofmagnitude reduction of the complexity is achievable using the proposed reconstructor. Furthermore, in [18], the filters in the analysis FB were designed using numerical optimization which can be time-consuming especially for higher filter orders and/or larger K. In Section VI of this paper, we propose a least-squares approach for designing these filters so that their filter coefficients can be obtained via a closed-form solution. In addition to reducing the design effort, the closedform solution enables us to redetermine the filter coefficients online, if required.…”

Section: A Contributions and Outline Of The Papermentioning

confidence: 99%

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Efficient Recovery of Sub-Nyquist Sampled Sparse Multi-Band Signals Using Reconfigurable Multi-Channel Analysis and Modulated Synthesis Filter Banks

Pillai

Johansson

2015

IEEE Trans. Signal Process.

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Abstract-Sub-Nyquist cyclic nonuniform sampling (CNUS) of a sparse multi-band signal generates a nonuniformly sampled signal. Assuming that the corresponding uniformly sampled signal satisfies the Nyquist sampling criterion, the sequence obtained via CNUS can be passed through a reconstructor to recover the missing uniform-grid samples. At present, these reconstructors have very high design and implementation complexity that offsets the gains obtained due to sub-Nyquist sampling. In this paper, we propose a scheme that reduces the design and implementation complexity of the reconstructor. In contrast to the existing reconstructors which use only a multi-channel synthesis filter bank (FB), the proposed reconstructor utilizes both analysis and synthesis FBs which makes it feasible to achieve an orderof-magnitude reduction of the complexity. The analysis filters are implemented using polyphase networks whose branches are allpass filters with distinct fractional delays and phase shifts. In order to reduce both the design and the implementation complexity of the synthesis FB, the synthesis filters are implemented using a cosine-modulated FB. In addition to the reduced complexity of the reconstructor, the proposed multi-channel recovery scheme also supports online reconfigurability which is required in flexible (multi-mode) systems where the user subband locations vary with time.Index Terms-Sub-Nyquist sampling, sparse multi-band signals, reconstruction, nonuniform sampling, time-interleaved analog-to-digital converters, filter banks.

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Efficient reconfigurable scheme for the recovery of sub-Nyquist sampled sparse multi-band signals

Cited by 3 publications

References 7 publications

Signal Reconstruction Algorithms for Time-Interleaved ADCs

Signal Reconstruction Algorithms for Time-Interleaved ADCs

A sub-band based reconstructor for M-channel time-interleaved ADCS with missing samples

Efficient Recovery of Sub-Nyquist Sampled Sparse Multi-Band Signals Using Reconfigurable Multi-Channel Analysis and Modulated Synthesis Filter Banks

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