arXiv subjects

Alphan Sahin

Publications and source records attributed to Alphan Sahin.

At least 19 recordsLinked to original sources

arXiv2026

A Generic Multi-dimensional Symbol Construction for Digital Over-the-Air Computation and Practical Aspects

In this paper, we propose a general-purpose multi-dimensional symbol construction for computing an arbitrary symmetric function with digital over-the-air computation (OAC) and discuss the practical aspects of coherent aggregation. For our first contribution, we discuss the categorical representation of a symmetric function. By using this representation and leveraging the sufficiency of the histogram to evaluate a symmetric function, i.e., inspired by type-based multiple access (TBMA), we introduce a general approach to design a single set of OAC symbols to compute any digital function. For our second contribution, we use a comprehensive platform based on low-cost nodes that maintain synchronization in time, frequency, phase, and amplitude via a trigger mechanism, enabling coherent OAC experiments without Global Positioning System (GPS) or cable-based synchronization. Using measurements from the platform, we characterize the phase and amplitude statistics of the composite channel to derive a realistic impairment model for coherent OAC. Through a comprehensive analysis, we demonstrate the effectiveness of the proposed scheme under impairments captured by the proposed model

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arXiv2026

Jutted BMOCZ for Non-Coherent OFDM

In this work, we propose a zero constellation for binary modulation on conjugate-reciprocal zeros (BMOCZ), called jutted BMOCZ (J-BMOCZ), and study its application to non-coherent orthogonal frequency division multiplexing (OFDM). With J-BMOCZ, we introduce asymmetry to the zero constellation for Huffman BMOCZ, which removes ambiguity at the receiver under a uniform rotation of the zeros. The asymmetry is controlled by the magnitude of "jutted" zeros and enables the receiver to estimate zero rotation using a simple cross-correlation. The proposed method, however, leads to a natural trade-off between asymmetry and zero stability. Accordingly, we introduce a reliability metric to measure the stability of a polynomial's zeros under an additive perturbation of the coefficients, and we apply the metric to optimize the J-BMOCZ zero constellation parameters. We then combine the advantages of J-BMOCZ and Huffman BMOCZ to design a hybrid waveform for OFDM with BMOCZ (OFDM-BMOCZ). The pilot-free waveform enables blind synchronization/detection and has a fixed peak-to-average power ratio that is independent of the message. Finally, we assess the proposed scheme through simulation and demonstrate non-coherent OFDM-BMOCZ using low-cost software-defined radios.

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arXiv2026

KAN-AE with Non-Linearity Score and Symbolic Regression for Energy-Efficient Channel Coding

In this paper, we investigate Kolmogorov-Arnold network-based autoencoders (KAN-AEs) with symbolic regression (SR) for energy-efficient channel coding. By using SR, we convert KAN-AEs into symbolic expressions, which enables low-complexity implementation and improved energy efficiency at the radios. To further enhance the efficiency, we introduce a new non-linearity score term in the SR process to help select lower-complexity equations when possible. Through numerical simulations, we demonstrate that KAN-AEs achieve competitive BLER performance while improving energy efficiency when paired with SR. We score the energy efficiency of a KAN-AE implementation using the proposed non-linearity metric and compare it to a multi-layer perceptron-based autoencoder (MLP-AE). Our experiment shows that the KAN-AE paired with SR uses 1.38 times less energy than the MLP-AE, supporting that KAN-AEs are a promising choice for energy-efficient deep learning-based channel coding.

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arXiv2025

Learning Zero Constellations for Binary MOCZ in Fading Channels

In this work, we propose two methods to design zero constellations for binary modulation on conjugate-reciprocal zeros (BMOCZ). In the first approach, we treat constellation design as a multi-label binary classification problem and learn the zero locations for a direct zero-testing (DiZeT) decoder. In the second approach, we introduce a neural network (NN)-based decoder and jointly learn the decoder and zero constellation parameters. We show that the NN-based decoder can directly generalize to flat-fading channels, despite being trained under additive white Gaussian noise. Furthermore, the results of numerical simulations demonstrate that learned zero constellations outperform the canonical, Huffman BMOCZ constellation, with the proposed NN-based decoder achieving large performance gain at the expense of increased computational complexity.

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arXiv2025

On the Feasibility of Distributed Phase Synchronization for Coherent Signal Superposition

In this study, we analyze the feasibility of distributed phase synchronization for coherent signal superposition, a fundamental enabler for paradigms such as coherent over-the-air computation (OAC), distributed beamforming, and interference alignment, under mobility and hardware impairments. With the focus on coherent OAC, we introduce phase-coded pilots (PCPs), a strategy where the radios communicate with each other to eliminate the round-trip phase change in the uplink (UL) and downlink (DL) to align the phase of the received symbol at a desired angle. In this study, considering a carrier frequency offset (CFO)-resilient multi-user procedure, we derive the statistics of the phase deviations to assess how fast the phase coherency degrades. Our results show that residual CFO is a major factor determining the duration of phase coherency, in addition to the non-negligible effects of mobility and the number of nodes in the network. We also provide a proof-of-concept demonstration for coherent signal superposition by using off-the-shelf radios to demonstrate the feasibility of PCPs in practice.

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arXiv2025

A Smooshed BMOCZ Zero Constellation for CFO Estimation Without Channel Coding

In this study, we propose a new binary modulation on conjugate-reciprocal zeros (BMOCZ) zero constellation, which we call smooshed binary modulation on conjugate-reciprocal zeros (SBMOCZ), to address carrier frequency offset (CFO)-induced zero rotation without depending on channel coding. In our approach, we modify the phase mapping of Huffman BMOCZ by shrinking the angle between adjacent zeros, except for the first and last, to introduce a gap in the zero constellation. By discerning the gap location in the received polynomial, the receiver can estimate and correct the phase rotation. We demonstrate the error rate performance of SBMOCZ relative to Huffman BMOCZ, showing that SBMOCZ addresses a CFO-induced rotation at the cost of a modest performance reduction compared to Huffman BMOCZ in the absence of a CFO. Finally, we compare SBMOCZ to Huffman BMOCZ using a cyclically permutable code (CPC), showing a 4 dB bit error rate (BER) improvement in a fading channel, while demonstrating comparable performance across other simulations.

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arXiv2025

Fourier-Domain CFO Estimation Using Jutted Binary Modulation on Conjugate-Reciprocal Zeros

In this work, we propose jutted binary modulation on conjugate-reciprocal zeros (J-BMOCZ) for non-coherent communication under a carrier frequency offset (CFO). By introducing asymmetry to the Huffman BMOCZ zero constellation, we exploit the identical aperiodic auto-correlation function of BMOCZ sequences to derive a Fourier-domain metric for CFO estimation. Unlike the existing methods for Huffman BMOCZ, which require a cyclically permutable code (CPC) for pilot-free CFO correction, J-BMOCZ enables the estimation of a CFO without the use of pilots or channel coding. Through numerical simulations in additive white Gaussian noise and fading channels, we show that the bit error rate (BER) loss of J-BMOCZ under a CFO is just 1 dB over Huffman BMOCZ without a CFO. Furthermore, the results show that coded J-BMOCZ achieves better BER performance than Huffman BMOCZ with a CPC.

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arXiv2024

A mmWave Software-Defined Array Platform for Wireless Experimentation at 24-29.5 GHz

Advanced millimeter-wave software-defined array (SDA) platforms, or testbeds at affordable costs and high performance are essential for the wireless community. In this paper, we present a low-cost, portable, and programmable SDA that allows for accessible research and experimentation in real time. The proposed platform is based on a 16-element phased-array transceiver operating across 24-29.5 GHz, integrated with a radio-frequency system-on-chip board that provides data conversion and baseband signal-processing capabilities. All radio-communication parameters and phased-array beam configurations are controlled through a high-level application program interface. We present measurements evaluating the beamforming and communication link performance. Our experimental results validate that the SDA has a beam scan range of -45 to +45 degrees (azimuth), a 3 dB beamwidth of 20 degrees, and support up to a throughput of 1.613 Gb/s using 64-QAM. The signal-to-noise ratio is as high as 30 dB at short-range distances when the transmit and receive beams are aligned.

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arXiv2024

On the Optimal Radius and Subcarrier Mapping for Binary Modulation on Conjugate-Reciprocal Zeros

In this work, we investigate the radius maximizing reliability for binary modulation on conjugate-reciprocal zeros (BMOCZ) implemented with both maximum likelihood (ML) and direct zero-testing (DiZeT) decoders. We first show that the optimal radius for BMOCZ is a function of the employed decoder and that the radius maximizing the minimum distance between polynomial zeros does not maximize the minimum distance of the final code. While maximizing zero separation offers an almost optimal solution with the DiZeT decoder, simulations show that the ML decoder outperforms the DiZeT decoder in both additive white Gaussian noise (AWGN) and fading channels when the radius is chosen to maximize codeword separation. Finally, we analyze different sequence-to-subcarrier mappings for BMOCZ-based orthogonal frequency division multiplexing (OFDM). We highlight a flexible time-frequency OFDM waveform that avoids distortion introduced by a frequency-selective channel at the expense of a higher peak-to-average power ratio (PAPR).

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arXiv2024

Over-the-Air Majority Vote Computation with Modulation on Conjugate-Reciprocal Zeros

In this study, we propose a new approach to compute the majority vote (MV) function based on modulation on conjugate-reciprocal zeros (MOCZ) and introduce three different methods. In these methods, each transmitter maps the votes to the zeros of a Huffman polynomial, and the corresponding polynomial coefficients are transmitted. The receiver evaluates the polynomial constructed by the elements of the superposed sequence at conjugate-reciprocal zero pairs and detects the MV with a direct zero-testing (DiZeT) decoder. With differential and index-based encoders, we eliminate the need for power-delay information at the receiver while improving the computation error rate (CER) performance. The proposed methods do not use instantaneous channel state information at the transmitters and receiver. Thus, they provide robustness against phase and time synchronization errors. We theoretically analyze the CERs of the proposed methods. Finally, we demonstrate their efficacy in a distributed median computation scenario.

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arXiv2023

Reliable Majority Vote Computation with Complementary Sequences for UAV Waypoint Flight Control

In this study, we propose a non-coherent over-the-air computation scheme to calculate the majority vote (MV) reliably in fading channels. The proposed approach relies on modulating the amplitude of the elements of complementary sequences based on the sign of the parameters to be aggregated. Since it does not use channel state information at the nodes, it is compatible with time-varying channels. To demonstrate the efficacy of our method, we employ it in a scenario where an unmanned aerial vehicle is guided by distributed sensors, relying on the MV computed using our proposed scheme. We show that the proposed scheme notably reduces the computation error rate with a longer sequence length in fading channels while maintaining the peak-to-mean-envelope power ratio of the transmitted orthogonal frequency division multiplexing signals to be less than or equal to 3 dB.

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arXiv2023

Wireless Federated $k$-Means Clustering with Non-coherent Over-the-Air Computation

In this study, we propose using an over-the-air computation (OAC) scheme for the federated k-means clustering algorithm to reduce the per-round communication latency when it is implemented over a wireless network. The OAC scheme relies on an encoder exploiting the representation of a number in a balanced number system and computes the sum of the updates for the federated k-means via signal superposition property of wireless multiple-access channels non-coherently to eliminate the need for precise phase and time synchronization. Also, a reinitialization method for ineffectively used centroids is proposed to improve the performance of the proposed method for heterogeneous data distribution. For a customer-location clustering scenario, we demonstrate the performance of the proposed algorithm and compare it with the standard k-means clustering. Our results show that the proposed approach performs similarly to the standard k-means while reducing communication latency.

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arXiv2023

Majority Vote Computation With Complementary Sequences for Distributed UAV Guidance

This study introduces a novel non-coherent over-the-air computation (OAC) scheme aimed at achieving reliable majority vote (MV) calculations in fading channels. The proposed approach relies on modulating the amplitude of the elements of complementary sequences (CSs) based on the sign of the parameters to be aggregated. Notably, our method eliminates the reliance on channel state information at the nodes, rendering it compatible with time-varying channels. To demonstrate the efficacy of our approach, we employ it in a scenario where an unmanned aerial vehicle (UAV) is guided by distributed sensors, relying on the MV computed using our proposed scheme. The experimental results confirm the superiority of our approach, as evidenced by a significant reduction in computation error rates in fading channels, particularly with longer sequence lengths. Meanwhile, we ensure that the peak-to-mean-envelope power ratio of the transmitted orthogonal frequency division multiplexing signals remains within or below 3 dB.

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arXiv2022

A Survey on Over-the-Air Computation

Communication and computation are often viewed as separate tasks. This approach is very effective from the perspective of engineering as isolated optimizations can be performed. However, for many computation-oriented applications, the main interest is a function of the local information at the devices, rather than the local information itself. In such scenarios, information theoretical results show that harnessing the interference in a multiple access channel for computation, i.e., over-the-air computation (OAC), can provide a significantly higher achievable computation rate than separating communication and computation tasks. Moreover, the gap between OAC and separation in terms of computation rate increases with more participating nodes. Given this motivation, in this study, we provide a comprehensive survey on practical OAC methods. After outlining fundamentals related to OAC, we discuss the available OAC schemes with their pros and cons. We provide an overview of the enabling mechanisms for achieving reliable computation in the wireless channel. Finally, we summarize the potential applications of OAC and point out some future directions.

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arXiv2022

Over-the-Air Computation Based on Balanced Number Systems for Federated Edge Learning

In this study, we propose a digital over-the-air computation (OAC) scheme for achieving continuous-valued (analog) aggregation for federated edge learning (FEEL). We show that the average of a set of real-valued parameters can be calculated approximately by using the average of the corresponding numerals, where the numerals are obtained based on a balanced number system. By exploiting this key property, the proposed scheme encodes the local stochastic gradients into a set of numerals. Next, it determines the positions of the activated orthogonal frequency division multiplexing (OFDM) subcarriers by using the values of the numerals. To eliminate the need for precise sample-level time synchronization, channel estimation overhead, and channel inversion, the proposed scheme also uses a non-coherent receiver at the edge server (ES) and does not utilize a pre-equalization at the edge devices (EDs). We theoretically analyze the MSE performance of the proposed scheme and the convergence rate for a non-convex loss function. To improve the test accuracy of FEEL with the proposed scheme, we introduce the concept of adaptive absolute maximum (AAM). Our numerical results show that when the proposed scheme is used with AAM for FEEL, the test accuracy can reach up to 98% for heterogeneous data distribution.

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arXiv2022

Over-the-Air Computation over Balanced Numerals

In this study, a digital over-the-air computation (OAC) scheme for achieving continuous-valued gradient aggregation is proposed. It is shown that the average of a set of real-valued parameters can be calculated approximately by using the average of the corresponding numerals, where the numerals are obtained based on a balanced number system. By using this property, the proposed scheme encodes the local gradients into a set of numerals. It then determines the positions of the activated orthogonal frequency division multiplexing (OFDM) subcarriers by using the values of the numerals. To eliminate the need for a precise sample-level time synchronization, channel estimation overhead, and power instabilities due to the channel inversion, the proposed scheme also uses a non-coherent receiver at the edge server (ES) and does not utilize a pre-equalization at the edge devices (EDs). Finally, the theoretical mean squared error (MSE) performance of the proposed scheme is derived and its performance for federated edge learning (FEEL) is demonstrated.

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arXiv2022

A Demonstration of Over-the-Air Computation for Federated Edge Learning

In this study, we propose a general-purpose synchronization method that allows a set of software-defined radios (SDRs) to transmit or receive any in-phase/quadrature data with precise timings while maintaining the baseband processing in the corresponding companion computers. The proposed method relies on the detection of a synchronization waveform in both receive and transmit directions and controlling the direct memory access blocks jointly with the processing system. By implementing this synchronization method on a set of low-cost SDRs, we demonstrate the performance of frequency-shift keying (FSK)-based majority vote (MV), i.e., an over-the-air computation scheme for federated edge learning, and introduce the corresponding procedures. Our experiment shows that the test accuracy can reach more than 95% for homogeneous and heterogeneous data distributions without using channel state information at the edge devices.

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arXiv2022

Distributed Learning over a Wireless Network with Non-coherent Majority Vote Computation

In this study, we propose an over-the-air computation (OAC) scheme to calculate the majority vote (MV) for federated edge learning (FEEL). With the proposed approach, edge devices (EDs) transmit the signs of local stochastic gradients, i.e., votes, by activating one of two orthogonal resources. The MVs at the edge server (ES) are obtained with non-coherent detectors by exploiting the accumulations on the resources. Hence, the proposed scheme eliminates the need for channel state information (CSI) at the EDs and ES. In this study, we analyze various gradient-encoding strategies through the weight functions and waveform configurations over orthogonal frequency division multiplexing (OFDM). We show that specific weight functions that enable absentee EDs (i.e., hard-coded participation with absentees (HPA)) or weighted votes (i.e., soft-coded participation (SP)) can substantially reduce the probability of detecting the incorrect MV. By taking path loss, power control, cell size, and fading channel into account, we prove the convergence of the distributed learning for a non-convex function for HPA. Through simulations, we show that the proposed scheme with HPA and SP can provide high test accuracy even when the time-synchronization and the power control are not ideal under heterogeneous data distribution scenarios.

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