Blind zero forcing equalization of multichannel nonlinear CDMA systems

Redfern, A.J.; Zhou, Guoyun

doi:10.1109/78.950791

Cited by 14 publications

(12 citation statements)

References 14 publications

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“…That is particularly interesting as Volterra systems are generally characterized by a large number Q of parameters. Indeed, working in the underdetermined case may impose a strong constraint on the number of antennas to be used, as it is the case in many previous works [5], [6], [7], [18], [9]. The flexibility on the choice of Rand P provided by the Kruskal condition is one of the main advantages of using a tensor-based approach.…”

Section: B Als With Direct Decision and Block Initialization (Als-ddmentioning

confidence: 95%

“…As a consequence, some nonlinear terms degenerate in terms of smaller order, leading to a smaller value of Q. Moreover, we have at = 0 or/and {3t = 0, for all t = 1, ... , T in (6). For instance, for T = 2 users and K = 1 (linear-cubic system), we have Q = 8 when Quadrature amplitude modulation (QAM) is used, and Q = 4 for PSK modulation.…”

Section: The Multiuser Nonlinear Rof Channel Modelmentioning

confidence: 97%

“…channel and transmitted signals, using only one known pilot symbol. Another advantage of this approach is that it allows working with weak uniqueness conditions compared with existing methods [5], [6], [7], [8], [9], which require that the number of channel outputs be greater than the number of nonlinear terms. That provides a great flexibility on the number of antennas and spreading factor, which is particularly suitable when identifying Volterra systems with a high number of parameters.…”

Section: Introductionmentioning

confidence: 97%

See 2 more Smart Citations

Tensor based receivers for nonlinear Radio Over Fiber uplinks in multiuser CDMA systems

Fernandes¹,

Favier²,

Mota³

2008

2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications

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International audienceTwo semi-blind tensor based receivers for uplink radio over fiber (ROF) nonlinear instantaneous channels in a multiuser code division multiple access (CDMA) environment are proposed in this paper. These receivers are based on the PARAFAC decomposition of a tensor (three-way array) composed of received signals with space, time and code diversities. A great advantage of the tensor approach is that it allows joint blind estimation of the channel and transmitted signals under weak uniqueness conditions compared with existing methods, which is particularly suitable when identifying nonlinear systems. Two estimation algorithms are proposed and illustrated by means of computer simulations

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Section: B Als With Direct Decision and Block Initialization (Als-ddmentioning

confidence: 95%

Section: The Multiuser Nonlinear Rof Channel Modelmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 97%

See 1 more Smart Citation

Tensor based receivers for nonlinear Radio Over Fiber uplinks in multiuser CDMA systems

Fernandes¹,

Favier²,

Mota³

2008

2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications

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“…In this section we consider the design of a blind zero forcing equalizer for the CDMA system with nonlinear channels modeled by (9). We follow a similar strategy as in [5], however we consider time-invariant codes and nonlinear channels.…”

Section: Blind Equalization Y$)(n) = X:(n)h$)mentioning

confidence: 99%

“…The scale ambiguity is not a concern, as it can be resolved using differential encoding and a knowledge of the signal constellation. See [8], [9] for the proof details.…”

Section: Y (~) (~P )mentioning

confidence: 99%

Blind equalization of CDMA systems with nonlinear channels

Redfern

Zhou²

Conference Record of the Thirty-Third Asilomar Conference on Signals, Systems, and Computers (Cat. No.CH37020)

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Code division multiple access (CDMA) has emerged as a popular format for many multiuser communication systems. However; the error pe~ormance of CDMA systems deteriorates as a result of intersymbol interJerence and nonlinearities. In this paper we propose a blind equalizer for chip synchronous CDMA systems with Volterra (nonlinear) channels. The equalizer requires multiple observations at the receive< obtained through oversampling or multiple antennas, and a knowledge of the code for the desired user. Zero forcing equalization is possible in the noisefree case. Simulations demonstrate the pegonnance of the equalizer on a number of different channel and user conjigurations.

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Sparse Nonlinear MIMO Filtering and Identification

Mileounis

Kalouptsidis

2013

Compressed Sensing &Amp; Sparse Filtering

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In this chapter system identification algorithms for sparse nonlinear multi input multi output (MIMO) systems are developed. These algorithms are potentially useful in a variety of application areas including digital transmission systems incorporating power amplifier(s) along with multiple antennas, cognitive processing, adaptive control of nonlinear multivariable systems, and multivariable biological systems. Sparsity is a key constraint imposed on the model. The presence of sparsity is often dictated by physical considerations as in wireless fading channelestimation. In other cases it appears as a pragmatic modelling approach that seeks to cope with the curse of dimensionality, particularly acute in nonlinear systems like Volterra type series.Three identification approaches are discussed: conventional identification based on both input and output samples, semi-blind identification placing emphasis on minimal input resources and blind identification whereby only output samples are available plus a-priori information on input characteristics. Based on this taxonomy a variety of algorithms, existing and new, are studied and evaluated by simulations.

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Blind zero forcing equalization of multichannel nonlinear CDMA systems

Cited by 14 publications

References 14 publications

Tensor based receivers for nonlinear Radio Over Fiber uplinks in multiuser CDMA systems

Tensor based receivers for nonlinear Radio Over Fiber uplinks in multiuser CDMA systems

Blind equalization of CDMA systems with nonlinear channels

Sparse Nonlinear MIMO Filtering and Identification

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