On Function Computation via Wireless Sensor Multiple-Access Channels

Goldenbaum, Mario; Stańczak, Sławomir; Kaliszan, Michał

doi:10.1109/wcnc.2009.4917843

Cited by 39 publications

(55 citation statements)

References 6 publications

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“…Although practical computation schemes suffer from limitations such as power constraints, fading, receiver noise, synchronization issues, we consider in this paper computations over an ideal MAC only to focus on the core of the computation problem and the related questions. The extension to realistic MACs (2) follows along similar lines such as in [4], [6].…”

Section: System Modelmentioning

confidence: 99%

“…To allow the computation of some nonlinear functions by means of the wireless MAC as well, the authors of [4] proposed a novel analog (i.e., non-digital/uncoded) computation scheme that employs appropriate pre-processing functions, operating on real sensor readings prior to transmissions, and a post-processing function, operating on the real superimposed signal received by a fusion center, to match the resulting overall channel to the nonlinear function of interest.…”

Section: Introductionmentioning

confidence: 99%

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Analog computation via wireless multiple-access channels: Universality and robustness

Goldenbaum

Boche

Stańczak

2012

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Recently, it has been shown that the superposition property of wireless multiple-access channels can be exploited to compute functions in sensor networks much more efficiently. By using appropriate pre-and post-processing functions operating on real sensor readings and the superimposed signal received by a fusion center, every function of the measurements is in principle computable by means of the wireless channel in which the pre-processing functions, and therefore the transmitting nodes, do not depend on the function of interest. In this paper we extend these general considerations by examining how robust this kind of universality is against variations in network topology due to nodes that drop out of the network or due to new nodes that connect to the network. Index Terms-Computation over multiple-access channels, representation of functions, wireless sensor networks

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Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analog computation via wireless multiple-access channels: Universality and robustness

Goldenbaum

Boche

Stańczak

2012

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…Equation (2) reveals that the natural mathematical characteristic of the wireless MAC is simply summation which can immediately be used to compute some linear desired functions in an efficient way. To enable the computation of certain nonlinear desired functions by means of the wireless MAC as well, we introduce the notions of pre-and post-processing functions [4], [5].…”

Section: A Computationmentioning

confidence: 99%

“…Motivated by this abstraction of the wireless channel as a computer, the authors of [4], [5] proposed a novel analog (i.e., non-digital/uncoded) computation scheme that outperforms TDMA in many relevant wireless sensor network scenarios of interest. The scheme employs appropriate pre-processing functions, operating on real sensor readings prior to transmissions, and a post-processing function, operating on the real superimposed signal received by the fusion center, to match the resulting overall channel to a nonlinear desired function.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the space of functions analog-computable via wireless multiple-access channels

Goldenbaum

Boche

Stańczak

2011

2011 8th International Symposium on Wireless Communication Systems

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To efficiently compute linear functions of the measurements in sensor networks, it was recently shown that the superposition property of the wireless multiple-access channel can profitably be exploited. Using suitable pre - and postprocessing functions operating on real sensor readings and on the superimposed signal received by a fusion center, respectively, the natural computation property of the wireless channel can be adapted such that a much larger class of functions is efficiently computable as well. In this paper, we analyze the corresponding space of functions which are in principle computable, or at least approximable, in an analog fashion via a wireless multiple-access channel and show to what extend this impacts the communication pattern and the complexity of nodes. Finally, we change the transmission scenario to a sequence of successively received multiple-access channel output-signals and observe that the resulting questions on the computability of functions are related to the famous 13th Hilbert problem

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“…Goldenbaum and others overcome this limitation by exploiting the signal strength of a received superimposition of signals [2], [7], [8]. They show how the arithmetic mean, the geometric mean, polynomials and other functions can be calculated at the time of transmission on the wireless channel.…”

Section: Introductionmentioning

confidence: 99%

Utilising convolutions of random functions to realise function calculation via a physical channel

Sigg¹,

Jakimovski²,

Ji³

et al. 2013

2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

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We discuss the utilisation of an algebra of random functions for the calculation of mathematical operations on a physical communication channel for actual implementation with resource restricted nodes. In particular, we present a transmission scheme for the computation of functions on the wireless channel and discuss various properties from combinations of random functions as well as requirements and restrictions of resource restricted hardware.

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On Function Computation via Wireless Sensor Multiple-Access Channels

Cited by 39 publications

References 6 publications

Analog computation via wireless multiple-access channels: Universality and robustness

Analog computation via wireless multiple-access channels: Universality and robustness

Analyzing the space of functions analog-computable via wireless multiple-access channels

Utilising convolutions of random functions to realise function calculation via a physical channel

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