17 citations · 65 across the 51 of their papers we have counts for
70 papers
Fast Tuning of Pinching Antenna-Assisted ISAC Systems via User Clustering
Ruizhi Niu, Ali Bereyhi
Pinching-antenna systems (PASSs) offer a great degree of flexibility for integrated sensing and communications (ISAC) by adapting the pinching locations for both communication chan…
Global Unknown Estimation: A Statistical Framework for Wireless Distributed Learning
Yicheng Qu, Ali Bereyhi, Ben Liang
Over-the-air computation (AirComp) is widely used for model aggregation in wireless distributed learning. Although it enhances communication efficiency, we believe the AirComp aggr…
Low-complexity tuning of pinching-antenna systems for integrated sensing and communication
Saba Asaad, Chongjun Ouyang, Zhiguo Ding +1
Pinching antenna systems (PASSs) can dynamically adapt their transmit and receive arrays for sensing and communication in wireless systems. This work explores the potential of PASS…
Regime-aware financial volatility forecasting via in-context learning
Saba Asaad, Shayan Mohajer Hamidi, Ali Bereyhi
This work introduces a regime-aware in-context learning framework that leverages large language models (LLMs) for financial volatility forecasting under nonstationary market condit…
Energy-Efficient Over-the-Air Federated Learning via Pinching Antenna Systems
Saba Asaad, Ali Bereyhi
Pinching antennas systems (PASSs) have recently been proposed as a novel flexible-antenna technology. These systems are implemented by attaching low-cost pinching elements to diele…
Dynamic and Static Energy Efficient Design of Pinching Antenna Systems
Saba Asaad, Chongjun Ouyang, Ali Bereyhi +1
We study the energy efficiency of pinching-antenna systems (PASSs) by developing a consistent formulation for power distribution in these systems. The per-antenna power distributio…
Revisiting GAN with Bayes-Optimal Discrimination
Mohammadreza Tavasoli Naeini, Ali Bereyhi, Morteza Noshad +2
We propose an alternative to the standard GAN training approach, in which the discriminator is a binary classifier trained by cross-entropy to distinguish real samples from generat…
Coding for Computation: Efficient Compression of Neural Networks for Reconfigurable Hardware
Hans Rosenberger, Rodrigo Fischer, Johanna S. Fröhlich +2
As state of the art neural networks (NNs) continue to grow in size, their resource-efficient implementation becomes ever more important. In this paper, we introduce a compression s…
MIMO-PASS: Uplink and Downlink Transmission via MIMO Pinching-Antenna Systems
Ali Bereyhi, Chongjun Ouyang, Saba Asaad +2
Pinching-antenna systems (PASSs) are a recent flexible-antenna technology that is realized by attaching simple components, referred to as pinching elements, to dielectric waveguide…
Downlink Beamforming with Pinching-Antenna Assisted MIMO Systems
Ali Bereyhi, Saba Asaad, Chongjun Ouyang +2
Pinching antennas have been recently proposed as a promising flexible-antenna technology, which can be implemented by attaching low-cost pinching elements to dielectric waveguides.…
BOLT: Universal Classifier Training via a Bayes-Error Upper Bound
Mohammadreza Tavasoli Naeini, Ali Bereyhi, Morteza Noshad +2
This work introduces a novel approach to compute a universal upper bound on the Bayes error rate (BER) from classifier-output samples, which serves as a Bayes-error-related perform…
Over-the-Air Fair Federated Learning via Multi-Objective Optimization
Shayan Mohajer Hamidi, Ali Bereyhi, Saba Asaad +1
In federated learning (FL), heterogeneity among the local dataset distributions of clients can result in unsatisfactory performance for some, leading to an unfair model. To address…
Regularized Top-: A Bayesian Framework for Gradient Sparsification
Ali Bereyhi, Ben Liang, Gary Boudreau +1
Error accumulation is effective for gradient sparsification in distributed settings: initially-unselected gradient entries are eventually selected as their accumulated error exceed…
GP-FL: Model-Based Hessian Estimation for Second-Order Over-the-Air Federated Learning
Shayan Mohajer Hamidi, Ali Bereyhi, Saba Asaad +1
Second-order methods are widely adopted to improve the convergence rate of learning algorithms. In federated learning (FL), these methods require the clients to share their local H…
Novel Gradient Sparsification Algorithm via Bayesian Inference
Ali Bereyhi, Ben Liang, Gary Boudreau +1
Error accumulation is an essential component of the Top- sparsification method in distributed gradient descent. It implicitly scales the learning rate and prevents the slow-down…
Rate-Constrained Quantization for Communication-Efficient Federated Learning
Shayan Mohajer Hamidi, Ali Bereyhi
Quantization is a common approach to mitigate the communication cost of federated learning (FL). In practice, the quantized local parameters are further encoded via an entropy codi…
Graph-based Algorithms for Linear Computation Coding
Hans Rosenberger, Ali Bereyhi, Ralf R. Müller
We revisit existing linear computation coding (LCC) algorithms, and introduce a new framework that measures the computational cost of computing multidimensional linear functions, n…
Linear Computation Coding: Exponential Search and Reduced-State Algorithms
Hans Rosenberger, Johanna S. Fröhlich, Ali Bereyhi +1
Linear computation coding is concerned with the compression of multidimensional linear functions, i.e. with reducing the computational effort of multiplying an arbitrary vector to…
Joint Receive Antenna Selection and Beamforming in RIS-Aided MIMO Systems
Chongjun Ouyang, Ali Bereyhi, Saba Asaad +2
This work studies a low-complexity design for reconfigurable intelligent surface (RIS)-aided multiuser multiple-input multiple-output systems. The base station (BS) applies receive…
Statistical-CSI-Based Antenna Selection and Precoding in Uplink MIMO
Chongjun Ouyang, Ali Bereyhi, Saba Asaad +2
Classical antenna selection schemes require instantaneous channel state information (CSI). This leads to high signaling overhead in the system. This work proposes a novel joint rec…
A High-Level Comparison of Recent Technologies for Massive MIMO Architectures
Hans Rosenberger, Bernhard Gäde, Ali Bereyhi +6
Since the introduction of massive MIMO (mMIMO), the design of a transceiver with feasible complexity has been a challenging problem. Initially, it was believed that the main issue…
Analysis of Sparse Recovery Algorithms via the Replica Method
Ali Bereyhi, Ralf R. Müller, Hermann Schulz-Baldes
This manuscript goes through the fundamental connections between statistical mechanics and estimation theory by focusing on the particular problem of compressive sensing. We first…
How to Coordinate Edge Devices for Over-the-Air Federated Learning?
Mohammad Ali Sedaghat, Ali Bereyhi, Saba Asaad +1
This work studies the task of device coordination in wireless networks for over-the-air federated learning (OTA-FL). For conventional metrics of aggregation error, the task is show…
A Novel Antenna Placement Algorithm for Compressive Sensing MIMO Radar
Bastian Eisele, Ali Bereyhi, Ingrid Ullmann +1
In colocated compressive sensing MIMO radar, the measurement matrix is specified by antenna placement. To guarantee an acceptable recovery performance, this measurement matrix shou…