Efficient Implementation of Complex Modulated Filter Banks Using Cosine and Sine Modulated Filter Banks

Viholainen, A.; Alhava, J.; Renfors, Markku

doi:10.1155/asp/2006/58564

Cited by 33 publications

(23 citation statements)

References 18 publications

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“…1.7 can be reduced by using a fast-transform algorithm [36,37] whereas for the prototype filter, only N/M multiplications per input/output sample are required. …”

Section: Cosine-modulated Filter Banksmentioning

confidence: 99%

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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“…1.7 can be reduced by using a fast-transform algorithm [36,37] whereas for the prototype filter, only N/M multiplications per input/output sample are required. …”

Section: Cosine-modulated Filter Banksmentioning

confidence: 99%

Signal Reconstruction Algorithms for Time-Interleaved ADCs

Pillai¹

2015

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“…In a PR cosine modulated filter bank (CMFB), N = 2KM− 1whereK is an integer overlapping factor as defined in Viholainen et al (2006). For complex modulated FBs,…”

Section: Modulated Fbsmentioning

confidence: 99%

Reconfigurable Multirate Systems in Cognitive Radios

Eghbali¹,

Johansson²

2012

Foundation of Cognitive Radio Systems

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“…To process a block of M complex-valued input samples and with an overlapping factor K, the M -channel MDFT FB requires M (4K + log 2 M − 3) + 4 real multiplications and M (4K + 3 log 2 M − 1) − 4 real additions [12]. Thus, the total per-sample arithmetic complexity is 8K + 4 log 2 M − 4.…”

Section: Implementation Cost and System Parametersmentioning

confidence: 99%

Reconfigurable nonuniform transmultiplexers based on uniform filter banks

Eghbali

Johansson

Lowenborg

2010

Proceedings of 2010 IEEE International Symposium on Circuits and Systems

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This paper introduces reconfigurable nonuniform transmultiplexers (TMUXs) based on uniform modulated filter banks (FBs). Polyphase components, of any user, are processed by a number of synthesis FB and analysis FB branches of a uniform TMUX. One branch, of the TMUX, represents one granularity band and any user occupies integer multiples of a granularity band. By adjusting the number of branches, assigned to each user, a nonuniform TMUX is obtained. This only requires adjustable commutators which add no extra arithmetic complexity. The application of both cosine modulated and modified discrete Fourier transform FBs are considered and the formulations related to the appropriate choice of parameters are outlined. Examples are provided for illustration.

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Efficient Implementation of Complex Modulated Filter Banks Using Cosine and Sine Modulated Filter Banks

Cited by 33 publications

References 18 publications

Signal Reconstruction Algorithms for Time-Interleaved ADCs

Signal Reconstruction Algorithms for Time-Interleaved ADCs

Reconfigurable Multirate Systems in Cognitive Radios

Reconfigurable nonuniform transmultiplexers based on uniform filter banks

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