A testbed based verification of joint communication and computation systems

Altun, Ufuk; Basaran, Semiha Tedik; Alakoca, Hakan; Kurt, Güneş Karabulut

doi:10.1109/telfor.2017.8249293

Cited by 9 publications

(9 citation statements)

References 10 publications

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“…Average error Sigg et al [166] 2012 Mean error Kortke et al [163] 2014 Relative error Abari et al [167] 2015 CFO Altun et al [164] 2017 MSE mization problem that minimizes the mean square error of the computed function output at the receiver. Their results show that a semidefinite relaxation is necessary to solve the problem and successive convex approximation can further increase the accuracy of the solution.…”

Section: Function Ratementioning

confidence: 99%

“…A network with 11 nodes and an FC is implemented to compute the arithmetic and geometric mean of the sensor readings of the nodes. In another implementation study [164], the summation of sensor readings over the channel is tested via SDR modules. The network that includes three transmitters and an FC is used to analyze the effect of distance and signal power level.…”

Section: Function Ratementioning

confidence: 99%

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The Magic of Superposition: A Survey on Simultaneous Transmission Based Wireless Systems

Altun,

Kurt,

Ozdemir

2021

Preprint

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In conventional communication systems, any interference between two communicating points is regarded as unwanted noise since it distorts the received signals. On the other hand, allowing simultaneous transmission and intentionally accepting the interference of signals and even benefiting from it have been considered for a range of wireless applications. As prominent examples, non-orthogonal multiple access (NOMA), joint source-channel coding, and the computation codes are designed to exploit this scenario. They also inspired many other fundamental works from network coding to consensus algorithms. Especially, federated learning is an emerging technology that can be applied to distributed machine learning networks by allowing simultaneous transmission. Although various simultaneous transmission applications exist independently in the literature, their main contributions are all based on the same principle; the superposition property. In this survey, we aim to emphasize the connections between these studies and provide a guide for the readers on the wireless communication techniques that benefit from the superposition of signals. We classify the existing literature depending on their purpose and application area and present their contributions. The survey shows that simultaneous transmission can bring scalability, security, low-latency, lowcomplexity and energy efficiency for certain distributed wireless scenarios which are inevitable with the emerging Internet of things (IoT) applications.

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Section: Function Ratementioning

confidence: 99%

Section: Function Ratementioning

confidence: 99%

The Magic of Superposition: A Survey on Simultaneous Transmission Based Wireless Systems

Altun,

Kurt,

Ozdemir

2021

Preprint

Self Cite

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“…Existing works on the OTA technique all suppose perfect superposition of the analog waveforms coming from different sensors since a similar idea has already been verified and applied for modulation-free remote state estimations [28]- [32] and the over-the-air fusion of sensor measurements [33]- [35]. In the existing prototype validation works [36], [37], a time-domain waveform design is adopted, and the waveform misalignment is the key issue since the sensors experience different multi-path propagations and also suffer different frame timing offsets (TOs). The misaligned waveforms not only cause superposition distortion but also result in inter-symbol interference.…”

Section: Introductionmentioning

confidence: 99%

“…The misaligned waveforms not only cause superposition distortion but also result in inter-symbol interference. In order to alleviate this issue, the direct-sequence spread spectrum (DSSS) technique is utilized in [36], [37], which multiplies each analog data symbol by a pseudo-random sequence with good correlation characteristics. By setting a long pseudo-random sequence (N ), a high-quality waveform superposition can be achieved, but the transmission efficiency is reduced to 1/N .…”

Section: Introductionmentioning

confidence: 99%

“…We propose an effective waveform superposition solution with prototype validation for the OTA-FL by utilizing the N -point orthogonal frequency-division multiplexing (OFDM) transmission. In contrast to [36], [37], the waveforms from different sensors can be aligned automatically in the frequencydomain sub-carriers, while the time-domain misalignment issue is addressed by the L-length cyclic prefixes. Therefore, the transmission efficiency is improved to (N − L)/N (while N ≫ L).…”

Section: Introductionmentioning

confidence: 99%

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Over-the-Air Aggregation for Federated Learning: Waveform Superposition and Prototype Validation

Guo¹,

Zhu²,

Ma³

et al. 2021

Preprint

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In this paper, we develop an orthogonal-frequencydivision-multiplexing (OFDM)-based over-the-air (OTA) aggregation solution for wireless federated learning (FL). In particular, the local gradients in massive IoT devices are modulated by an analog waveform and are then transmitted using the same wireless resources. To this end, achieving perfect waveform superposition is the key challenge, which is difficult due to the existence of frame timing offset (TO) and carrier frequency offset (CFO). In order to address these issues, we propose a two-stage waveform pre-equalization technique with a customized multiple access protocol that can estimate and then mitigate the TO and CFO for the OTA aggregation. Based on the proposed solution, we develop a hardware transceiver and application software to train a real-world FL task, which learns a deep neural network to predict the received signal strength with global positioning system information. Experiments verify that the proposed OTA aggregation solution can achieve comparable performance to offline learning procedures with high prediction accuracy.

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The Magic of Superposition: A Survey on Simultaneous Transmission Based Wireless Systems

2022

Self Cite

View full text Add to dashboard Cite

In conventional communication systems, any interference between two communicating points is regarded as unwanted noise since it distorts the received signals. On the other hand, allowing simultaneous transmission and intentionally accepting the superposition of signals and even benefiting from it have been considered for a range of wireless applications. As prominent examples, NOMA, joint sourcechannel coding, and the computation codes are designed to exploit this scenario. They also inspired many other fundamental works from network coding to consensus algorithms. Especially, federated learning is an emerging technology that can be applied to distributed machine learning networks by allowing simultaneous transmission. Although various simultaneous transmission applications exist independently in the literature, their main contributions are all based on the same principle; the superposition property. In this survey, we aim to emphasize the connections between these studies and provide a guide for the readers on the wireless communication techniques that benefit from the superposition of signals. We classify the existing literature depending on their purpose and application area and present their contributions. The survey shows that simultaneous transmission can bring scalability, security, low-latency, low-complexity and energy efficiency for certain distributed wireless scenarios which are inevitable with the emerging wireless technologies.

show abstract

A testbed based verification of joint communication and computation systems

Cited by 9 publications

References 10 publications

The Magic of Superposition: A Survey on Simultaneous Transmission Based Wireless Systems

The Magic of Superposition: A Survey on Simultaneous Transmission Based Wireless Systems

Over-the-Air Aggregation for Federated Learning: Waveform Superposition and Prototype Validation

The Magic of Superposition: A Survey on Simultaneous Transmission Based Wireless Systems

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