Search Results for author: Yulin Shao

Found 19 papers, 5 papers with code

The Power of Large Language Models for Wireless Communication System Development: A Case Study on FPGA Platforms

no code implementations14 Jul 2023 Yuyang Du, Soung Chang Liew, Kexin Chen, Yulin Shao

We begin by exploring LLM-assisted code refactoring, reuse, and validation, using an open-source software-defined radio (SDR) project as a case study.


Wireless Point Cloud Transmission

no code implementations14 Jun 2023 Chenghong Bian, Yulin Shao, Deniz Gunduz

3D point cloud is a three-dimensional data format generated by LiDARs and depth sensors, and is being increasingly used in a large variety of applications.

DeepJSCC-l++: Robust and Bandwidth-Adaptive Wireless Image Transmission

1 code implementation22 May 2023 Chenghong Bian, Yulin Shao, Deniz Gunduz

This paper presents a novel vision transformer (ViT) based deep joint source channel coding (DeepJSCC) scheme, dubbed DeepJSCC-l++, which can be adaptive to multiple target bandwidth ratios as well as different channel signal-to-noise ratios (SNRs) using a single model.

Feedback is Good, Active Feedback is Better: Block Attention Active Feedback Codes

no code implementations3 Nov 2022 Emre Ozfatura, Yulin Shao, Amin Ghazanfari, Alberto Perotti, Branislav Popovic, Deniz Gunduz

Deep neural network (DNN)-assisted channel coding designs, such as low-complexity neural decoders for existing codes, or end-to-end neural-network-based auto-encoder designs are gaining interest recently due to their improved performance and flexibility; particularly for communication scenarios in which high-performing structured code designs do not exist.

Space-time design for deep joint source channel coding of images Over MIMO channels

1 code implementation30 Oct 2022 Chenghong Bian, Yulin Shao, Haotian Wu, Deniz Gunduz

We propose novel deep joint source-channel coding (DeepJSCC) algorithms for wireless image transmission over multi-input multi-output (MIMO) Rayleigh fading channels, when channel state information (CSI) is available only at the receiver.

Decentralized Channel Management in WLANs with Graph Neural Networks

no code implementations30 Oct 2022 Zhan Gao, Yulin Shao, Deniz Gunduz, Amanda Prorok

Wireless local area networks (WLANs) manage multiple access points (APs) and assign scarce radio frequency resources to APs for satisfying traffic demands of associated user devices.


Semantic Communications with Discrete-time Analog Transmission: A PAPR Perspective

1 code implementation17 Aug 2022 Yulin Shao, Deniz Gunduz

Recent progress in deep learning (DL)-based joint source-channel coding (DeepJSCC) has led to a new paradigm of semantic communications.

Image Reconstruction Open-Ended Question Answering

Learning-based Autonomous Channel Access in the Presence of Hidden Terminals

no code implementations7 Jul 2022 Yulin Shao, Yucheng Cai, Taotao Wang, Ziyang Guo, Peng Liu, Jiajun Luo, Deniz Gunduz

We consider the problem of autonomous channel access (AutoCA), where a group of terminals tries to discover a communication strategy with an access point (AP) via a common wireless channel in a distributed fashion.

All you need is feedback: Communication with block attention feedback codes

no code implementations19 Jun 2022 Emre Ozfatura, Yulin Shao, Alberto Perotti, Branislav Popovic, Deniz Gunduz

Deep learning based channel code designs have recently gained interest as an alternative to conventional coding algorithms, particularly for channels for which existing codes do not provide effective solutions.

AttentionCode: Ultra-Reliable Feedback Codes for Short-Packet Communications

no code implementations30 May 2022 Yulin Shao, Emre Ozfatura, Alberto Perotti, Branislav Popovic, Deniz Gunduz

The training methods can potentially be generalized to other wireless communication applications with machine learning.

Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs

no code implementations20 Mar 2022 Francesc Wilhelmi, Jernej Hribar, Selim F. Yilmaz, Emre Ozfatura, Kerem Ozfatura, Ozlem Yildiz, Deniz Gündüz, Hao Chen, Xiaoying Ye, Lizhao You, Yulin Shao, Paolo Dini, Boris Bellalta

As wireless standards evolve, more complex functionalities are introduced to address the increasing requirements in terms of throughput, latency, security, and efficiency.

Federated Learning

Efficient FFT Computation in IFDMA Transceivers

no code implementations5 Mar 2022 Yuyang Du, Soung Chang Liew, Yulin Shao

Our experimental results indicate that when the number of hardware processors is a power of two: 1) MPS-FFT has near-optimal computation time; 2) MPS-FFT incurs less than 44. 13\% of the computation time of the conventional pipelined FFT.


Bayesian Over-The-Air Computation

no code implementations8 Sep 2021 Yulin Shao, Deniz Gunduz, Soung Chang Liew

In the low signal-to-noise ratio (SNR) regime, the LMMSE estimator reduces the mean squared error (MSE) by at least 6 dB; in the high SNR regime, the LMMSE estimator lowers the error floor of MSE by 86. 4%; 2) For the asynchronous OAC, our LMMSE and sum-product maximum a posteriori (SP-MAP) estimators are on an equal footing in terms of the MSE performance, and are significantly better than the ML estimator.


Denoising Noisy Neural Networks: A Bayesian Approach with Compensation

1 code implementation22 May 2021 Yulin Shao, Soung Chang Liew, Deniz Gunduz

Deep neural networks (DNNs) with noisy weights, which we refer to as noisy neural networks (NoisyNNs), arise from the training and inference of DNNs in the presence of noise.

Denoising Quantization

Federated Edge Learning with Misaligned Over-The-Air Computation

1 code implementation26 Feb 2021 Yulin Shao, Deniz Gunduz, Soung Chang Liew

Over-the-air computation (OAC) is a promising technique to realize fast model aggregation in the uplink of federated edge learning.

Flow Sampling: Network Monitoring in Large-Scale Software-Defined IoT Networks

no code implementations21 Jul 2020 Yulin Shao, Soung Chang Liew, He Chen, Yuyang Du

Software-defined Internet-of-Things networking (SDIoT) greatly simplifies the network monitoring in large-scale IoT networks by per-flow sampling, wherein the controller keeps track of all the active flows in the network and samples the IoT devices on each flow path to collect real-time flow statistics.

Sporadic Ultra-Time-Critical Crowd Messaging in V2X

no code implementations4 Mar 2020 Yulin Shao, Soung Chang Liew, Jiaxin Liang

To circumvent potential inefficiency arising from sporadicity, we propose an override network architecture whereby warning messages are delivered on the spectrum of the ordinary vehicular messages.

New Transceiver Designs for Interleaved Frequency Division Multiple Access

no code implementations23 Nov 2019 Soung Chang Liew, Yulin Shao

For flexible resource allocation, this paper puts forth a new IFDMA resource allocation framework called Multi-IFDMA, in which a user can be allocated multiple IFDMA streams.

AlphaSeq: Sequence Discovery with Deep Reinforcement Learning

no code implementations26 Sep 2018 Yulin Shao, Soung Chang Liew, Taotao Wang

We demonstrate the searching capabilities of AlphaSeq in two applications: 1) AlphaSeq successfully rediscovers a set of ideal complementary codes that can zero-force all potential interferences in multi-carrier CDMA systems.

reinforcement-learning Reinforcement Learning (RL)

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