NIULAB

Getting Started

Sat, 17 Feb 2024 00:00:00 +0000

Quick Start from Template

Create a site

Configure your new site

Add your content

Publish your site

Your site will automatically publish ~1-5 minutes after you commit (save) changes to files in your GitHub repository.

Let’s customize your new site:

Project Structure Configuration Create content

Customizing Hugo

Mon, 01 Jan 0001 00:00:00 +0000

View the full docs at

Project Structure

Mon, 01 Jan 0001 00:00:00 +0000

Folder Structure

There are 4 main folders for Hugo-based sites:

content/ for your Markdown-formatted content files (homepage, etc.)
- _index.md the homepage (Hugo requires that the homepage and archive pages have an underscore prefix)
assets/
- media/ for your media files (images, videos)
  - icons/custom/ upload any custom SVG icons you want to use
config/_default/ for your site configuration files
- hugo.yaml to configure Hugo (site title, URL, Hugo options, setup per-folder page features)
- module.yaml to install or uninstall Hugo themes and plugins
- params.yaml to configure Hugo Blox options (SEO, analytics, site features)
- menus.yaml to configure your menu links (if the menu is enabled in params.yaml)
- languages.yaml to configure your site’s language or to set language-specific options in a multilingual site
static/uploads/ for any files you want visitors to download, such as a PDF
go.mod sets the version of Hugo themes/plugins which your site uses

Hugo File Naming Convention

Hugo gives us two options to name standard page files: as TITLE/index.md or TITLE.md where TITLE is your page name.

The page name should be lowercase and using hyphens (-) instead of spaces.

Both approaches result in the same output, so you can choose your preferred approach to naming and organizing files. A benefit to the folder-based approach is that all your page’s files (such as images) are self-contained within the page’s folder, so it’s more portable if you wish to share the original Markdown page with someone.

The homepage is a special case as Hugo requires the homepage and listing pages to be named _index.md.

The docs navigation is automatically generated based on the content in the docs/ folder and is sorted alphabetically.

The order of pages can be changed by adding the weight parameter in the front matter of your Markdown files.

In the example below, the example.md page will appear before the test.md page as it has a lower weight:

Page example.md:

---
title: My Example
weight: 1
---

Page test.md:

---
title: My Test
weight: 2
---

Configuration

Mon, 01 Jan 0001 00:00:00 +0000

The configuration of your site can be found in config/_default/.

Full Documentation

See

Links are automatically generated from the structure of your content directory. Simply add a folder to nest a page.

Extra Links

Additional links can be added under the sidebar section of your config/_default/menus.yaml:

menu:
 sidebar:
 - name: "Need help?"
 params:
 type: separator
 weight: 1
 - name: "A page"
 pageRef: "/page-filename-here"
 weight: 2
 - name: "An external link ↗"
 url: "https://hugoblox.com"
 weight: 3

A table of contents is automatically generated from the headings your Markdown file.

It can optionally be disabled by setting toc: false in the front matter of a page:

---
title: My Page
toc: false
---

清华大学电子系牛志升教授课题组招聘博士后

Wed, 14 Oct 2026 00:00:00 +0000

清华大学电子系牛志升教授课题组招聘博士后

清华大学电子工程系牛志升教授/周盛副教授课题组主要从事新一代移动通信系统的研究，现招聘博士后2名。

要求如下：

科研作风严谨，诚实，具有良好的合作精神；
即将或已经获得博士学位，具有信息与通信工程或是人工智能、认知科学与技术等相关专业背景，具有承担国内外科研工作的理论基础和项目研究经历；
年龄35岁以下；
英文良好，在相关领域的国际期刊发表过学术论文。

工资待遇：

按照清华大学博士后工资待遇执行，具体可面议；
学校设有博士后公寓，可根据有关规定排队入住；
入站博士后享受清华大学事业编制教职工子女入学、入园的规定以及附属学校、幼儿园的有关规定；
对于优秀博士后申请者，学校设有博士后支持计划和水木学者计划，详情登陆清华大学博士后官网查询。

实验室主页：https://network.ee.tsinghua.edu.cn/niulab/ 有意者请与许萍老师（xuping811@tsinghua.edu.cn, 010-62773634）联系。

The research group led by Professor Zhisheng Niu and Associate Professor Sheng Zhou in the Department of Electronic Engineering at Tsinghua University focuses on next-generation mobile communication systems. The group is currently recruiting two postdoctoral researchers.

Requirements

A rigorous and responsible approach to research, integrity, and a strong spirit of collaboration.
Candidates who are about to receive or have already obtained a Ph.D. degree in Information and Communication Engineering, Artificial Intelligence, Cognitive Science and Technology, or a related field. Applicants should have a solid theoretical foundation and research experience in domestic or international research projects.
Applicants must be under 35 years of age.
Good English proficiency and a record of publications in international journals in relevant fields.

Salary and Benefits

Compensation will follow Tsinghua University’s postdoctoral salary policy. Specific terms are negotiable.
Postdoctoral housing is available on campus, with allocation subject to the university’s relevant regulations and availability.
Postdoctoral researchers are eligible for the university’s policies regarding school and kindergarten enrollment for children of faculty and staff with institutional appointments, as well as applicable policies for affiliated schools and kindergartens.
Outstanding candidates may apply for the university’s postdoctoral support programs and the Shuimu Scholars Program. Please visit Tsinghua University’s official postdoctoral website for further information.

Laboratory Website:

Contact: Ping Xu

Email:

Tel: +86-10-62773634

Robust DNN Partitioning and Resource Allocation Under Uncertain Inference Time

Sun, 01 Mar 2026 00:00:00 +0000

C-MASS: Combinatorial Mobility-Aware Sensor Scheduling for Collaborative Perception With Second-Order Topology Approximation

Thu, 01 Jan 2026 00:00:00 +0000

CoSTr: Fully Sparse Transformer with Mutual Information for Pragmatic Collaborative Perception

Thu, 01 Jan 2026 00:00:00 +0000

DH-VLM: Dual-Horizon Cooperative Latent Reasoning for Autonomous Driving

Thu, 01 Jan 2026 00:00:00 +0000

DPNet: Doppler LiDAR Motion Planning for Highly-Dynamic Environments

Thu, 01 Jan 2026 00:00:00 +0000

DRIVE: Dynamic Residual Information Exchange for Communication-Efficient Collaborative Perception in Autonomous Driving

Thu, 01 Jan 2026 00:00:00 +0000

Energy-Efficient Collaborative Perception: A Block-Skipping DNN Approach With Dynamic Frequency Scaling and Environment Awareness

Thu, 01 Jan 2026 00:00:00 +0000

FedCGD: Collective Gradient Divergence Optimized Scheduling for Wireless Federated Learning

Thu, 01 Jan 2026 00:00:00 +0000

Learning to Jointly Optimize Antenna Positioning and Beamforming for Movable Antenna-Aided Systems

Thu, 01 Jan 2026 00:00:00 +0000

Mobility-Aware Asynchronous Federated Learning With Dynamic Sparsification

Thu, 01 Jan 2026 00:00:00 +0000

SparseCoM: Fully Sparse Collaborative Perception via Mixture of BEV Experts

Thu, 01 Jan 2026 00:00:00 +0000

Task Profiling and Draft Model Selection for Accelerating Distributed Speculative Decoding

Thu, 01 Jan 2026 00:00:00 +0000

UniMM-V2X: MoE-Enhanced Multi-Level Fusion for End-to-End Cooperative Autonomous Driving

Thu, 01 Jan 2026 00:00:00 +0000

Joint Memory Frequency and Computing Frequency Scaling for Energy-efficient DNN Inference

Mon, 01 Dec 2025 00:00:00 +0000

Agile coverage for low-altitude aerial intelligent networks: A blended hyper-cellular solution

Mon, 01 Sep 2025 00:00:00 +0000

Mixture of Experts-Augmented Deep Unfolding for Activity Detection in IRS-Aided Systems

Mon, 01 Sep 2025 00:00:00 +0000

Robust Task Offloading and Resource Allocation Under Imperfect Computing Capacity Information in Edge Intelligence Systems

Tue, 01 Jul 2025 00:00:00 +0000

DVFS-Aware DNN Inference on GPUs: Latency Modeling and Performance Analysis

Sun, 01 Jun 2025 00:00:00 +0000

Dynamic Scheduling for Vehicle-to-Vehicle Communications Enhanced Federated Learning

Sun, 01 Jun 2025 00:00:00 +0000

AEPHORA: AI/ML-Based Energy-Efficient Proactive Handover and Resource Allocation

Wed, 01 Jan 2025 00:00:00 +0000

Distributed Activity Detection for Cell-Free Hybrid Near-Far Field Communications

Wed, 01 Jan 2025 00:00:00 +0000

FedTeddi: Temporal Drift and Divergence Aware Scheduling for Timely Federated Edge Learning

Wed, 01 Jan 2025 00:00:00 +0000

FlexGen: Efficient On-Demand Generative AI Service With Flexible Diffusion Model in Mobile Edge Networks

Wed, 01 Jan 2025 00:00:00 +0000

Grouping-Based Cyclic Scheduling Under Age of Correlated Information Constraints

Wed, 01 Jan 2025 00:00:00 +0000

Image Analysis Oriented Integrated Sensing and Communication via Intelligent Reflecting Surface

Wed, 01 Jan 2025 00:00:00 +0000

Joint Optimization of Offloading, Batching and DVFS for Multiuser Co-Inference

Wed, 01 Jan 2025 00:00:00 +0000

Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks

Wed, 01 Jan 2025 00:00:00 +0000

Near-Sensor LiDAR and Visual Feature Extraction and Communication for Low-Latency Roadside Cooperative Perception

Wed, 01 Jan 2025 00:00:00 +0000

Nonparametric Teaching for Graph Property Learners

Wed, 01 Jan 2025 00:00:00 +0000

On the Impact of Mobility in Asynchronous Federated Learning over Device-to-Device Networks

Wed, 01 Jan 2025 00:00:00 +0000

SMDP-Based Dynamic Batching for Improving Responsiveness and Energy Efficiency of Batch Services

Wed, 01 Jan 2025 00:00:00 +0000

SNAKE: Sequential Continual Learning for Knowledge Extension over Communication-Constrained Networks

Wed, 01 Jan 2025 00:00:00 +0000

Unlimited Vector Processing for Wireless Baseband Based on RISC-V Extension

Wed, 01 Jan 2025 00:00:00 +0000

Venus: A RISC-V Domain Specific Architecture Towards Integrated AI and Wireless Baseband Processing for 6G Edge Intelligence

Wed, 01 Jan 2025 00:00:00 +0000

WHALES: A Multi-Agent Scheduling Dataset for Enhanced Cooperation in Autonomous Driving

Wed, 01 Jan 2025 00:00:00 +0000

Learning-Assisted User Scheduling and Beamforming for mmWave Vehicular Networks

Thu, 01 Aug 2024 00:00:00 +0000

Adaptive Privacy-Preserving Coded Computing with Hierarchical Task Partitioning

Mon, 01 Jan 2024 00:00:00 +0000

AI-Native Networking

Mon, 01 Jan 2024 00:00:00 +0000

CPU-Utilization-Aware Scheduling for In-Vehicle Distributed Computing

Mon, 01 Jan 2024 00:00:00 +0000

Edge Intelligence

Mon, 01 Jan 2024 00:00:00 +0000

Green Wireless Systems

Mon, 01 Jan 2024 00:00:00 +0000

Infrastructure-Assisted Collaborative Perception in Automated Valet Parking: A Safety Perspective

Mon, 01 Jan 2024 00:00:00 +0000

Joint Frame Structure and Beamwidth Optimization for Integrated Localization and Communication

Mon, 01 Jan 2024 00:00:00 +0000

Low-Altitude Intelligent Networks

Mon, 01 Jan 2024 00:00:00 +0000

Multi-Agent DRL-Based Two-Timescale Resource Allocation for Network Slicing in V2X Communications

Mon, 01 Jan 2024 00:00:00 +0000

QMNet: Importance-Aware Message Exchange for Decentralized Multi-Agent Reinforcement Learning

Mon, 01 Jan 2024 00:00:00 +0000

Resource Allocation for Channel Estimation in Reconfigurable Intelligent Surface-Aided Multi-Cell Networks

Mon, 01 Jan 2024 00:00:00 +0000

RSU-Aided Energy-Efficient Collaborative Perception for Connected Autonomous Vehicles

Mon, 01 Jan 2024 00:00:00 +0000

Task-Oriented Wireless Communications for Collaborative Perception in Intelligent Unmanned Systems

Mon, 01 Jan 2024 00:00:00 +0000

Vehicular & Autonomous Systems

Mon, 01 Jan 2024 00:00:00 +0000

能量信息深度融合的移动网络架构及其技术挑战

Mon, 01 Jan 2024 00:00:00 +0000

面向6G网络的高可靠低延时通信计算与控制

Mon, 01 Jan 2024 00:00:00 +0000

Pandas

Thu, 26 Oct 2023 00:00:00 +0000

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures.

PyTorch

Thu, 26 Oct 2023 00:00:00 +0000

PyTorch is a Python package that provides tensor computation (like NumPy) with strong GPU acceleration.

scikit-learn

Thu, 26 Oct 2023 00:00:00 +0000

scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.

Embed Media

Tue, 24 Oct 2023 00:00:00 +0000

is designed to give technical content creators a seamless experience. You can focus on the content and the Hugo Blox Builder which this template is built upon handles the rest.

Embed videos, podcasts, code, LaTeX math, and even test students!

On this page, you’ll find some examples of the types of technical content that can be rendered with Hugo Blox.

Video

Teach your course by sharing videos with your students. Choose from one of the following approaches:

Youtube:

{{< youtube w7Ft2ymGmfc >}}

Bilibili:

{{< bilibili id="BV1WV4y1r7DF" >}}

Video file

Videos may be added to a page by either placing them in your assets/media/ media library or in your , and then embedding them with the video shortcode:

{{< video src="my_video.mp4" controls="yes" >}}

Podcast

You can add a podcast or music to a page by placing the MP3 file in the page’s folder or the media library folder and then embedding the audio on your page with the audio shortcode:

{{< audio src="ambient-piano.mp3" >}}

Try it out:

Test students

Provide a simple yet fun self-assessment by revealing the solutions to challenges with the spoiler shortcode:

{{< spoiler text="👉 Click to view the solution" >}}
You found me!
{{< /spoiler >}}

renders as

👉 Click to view the solution

You found me 🎉

Math

Hugo Blox Builder supports a Markdown extension for $\LaTeX$ math. You can enable this feature by toggling the math option in your config/_default/params.yaml file.

To render inline or block math, wrap your LaTeX math with {{< math >}}$...${{< /math >}} or {{< math >}}$$...$${{< /math >}}, respectively.

Note

We wrap the LaTeX math in the Hugo Blox math shortcode to prevent Hugo rendering our math as Markdown. This callout now uses the standard Markdown alert syntax!

Example math block:

{{< math >}}
$$
\gamma_{n} = \frac{ \left | \left (\mathbf x_{n} - \mathbf x_{n-1} \right )^T \left [\nabla F (\mathbf x_{n}) - \nabla F (\mathbf x_{n-1}) \right ] \right |}{\left \|\nabla F(\mathbf{x}_{n}) - \nabla F(\mathbf{x}_{n-1}) \right \|^2}
$$
{{< /math >}}

renders as

$$\gamma_{n} = \frac{ \left | \left (\mathbf x_{n} - \mathbf x_{n-1} \right )^T \left [\nabla F (\mathbf x_{n}) - \nabla F (\mathbf x_{n-1}) \right ] \right |}{\left \|\nabla F(\mathbf{x}_{n}) - \nabla F(\mathbf{x}_{n-1}) \right \|^2}$$

Example inline math {{< math >}}$\nabla F(\mathbf{x}_{n})${{< /math >}} renders as $\nabla F(\mathbf{x}_{n})$ .

Example multi-line math using the math linebreak (\\):

{{< math >}}
$$f(k;p_{0}^{*}) = \begin{cases}p_{0}^{*} & \text{if }k=1, \\
1-p_{0}^{*} & \text{if }k=0.\end{cases}$$
{{< /math >}}

renders as

$$ f(k;p_{0}^{*}) = \begin{cases}p_{0}^{*} & \text{if }k=1, \\ 1-p_{0}^{*} & \text{if }k=0.\end{cases} $$

Code

Hugo Blox Builder utilises Hugo’s Markdown extension for highlighting code syntax. The code theme can be selected in the config/_default/params.yaml file.

```python
import pandas as pd
data = pd.read_csv("data.csv")
data.head()
```

renders as

import pandas as pd
data = pd.read_csv("data.csv")
data.head()

Inline Images

{{< icon name="python" >}} Python

renders as

Python

Join Us

Tue, 24 Oct 2023 00:00:00 +0000

Data-Heterogeneous Hierarchical Federated Learning with Mobility

Fri, 01 Sep 2023 00:00:00 +0000

Hierarchical Federated Learning: Architecture, Challenges, and its Implementation in Vehicular Networks

Wed, 01 Mar 2023 00:00:00 +0000

A Predictive Frame Transmission Scheme for Cloud Gaming in Mobile Edge Cloudlet Systems

Sun, 01 Jan 2023 00:00:00 +0000

Delay Optimization of Coded Computing With Hierarchical Task Partitioning

Sun, 01 Jan 2023 00:00:00 +0000

Joint Task Offloading and Resource Allocation for Vehicular Edge Computing with Result Feedback Delay

Sun, 01 Jan 2023 00:00:00 +0000

MASS: Mobility-Aware Sensor Scheduling of Cooperative Perception for Connected Automated Driving

Sun, 01 Jan 2023 00:00:00 +0000

MEET: Mobility-Enhanced Edge inTelligence for Smart and Green 6G Networks

Sun, 01 Jan 2023 00:00:00 +0000

MOB-FL: Mobility-Aware Federated Learning for Intelligent Connected Vehicles

Sun, 01 Jan 2023 00:00:00 +0000

MoRFF: Multi-View Object Detection for Connected Autonomous Driving under Communication and Localization Limitations

Sun, 01 Jan 2023 00:00:00 +0000

Multiuser Co-inference with Batch Processing Capable Edge Server

Sun, 01 Jan 2023 00:00:00 +0000

NI-MAC: MAC Protocol Design for Neural Interfaces

Sun, 01 Jan 2023 00:00:00 +0000

Optimizing Task-Specific Timeliness With Edge-Assisted Scheduling for Status Update

Sun, 01 Jan 2023 00:00:00 +0000

Over-the-Air Integrated Sensing, Communication, and Computation in IoT Networks

Sun, 01 Jan 2023 00:00:00 +0000

Random Access Protocol Design and Analysis for Neural Interfaces Under Non-Saturated Regime

Sun, 01 Jan 2023 00:00:00 +0000

Sensing and Communication Co-Design for Status Update in Multiaccess Wireless Networks

Sun, 01 Jan 2023 00:00:00 +0000

SMDP-Based Dynamic Batching for Efficient Inference on GPU-Based Platforms

Sun, 01 Jan 2023 00:00:00 +0000

Time-Triggered Reservation for Cooperative Random Access in Wireless LANs

Sun, 01 Jan 2023 00:00:00 +0000

V2V-Assisted Timely Hierarchical Federated Learning

Sun, 01 Jan 2023 00:00:00 +0000

定位与通信受限的网联协同感知算法

Sun, 01 Jan 2023 00:00:00 +0000

Dolphins Dataset

Fri, 09 Dec 2022 00:00:00 +0000

DOLPHINS, Dataset for cOLlaborative Perception enabled Harmonious and INterconnected Self-driving, provides temporally aligned visual and LiDAR information collected from different perspectives, i.e. vehicles and road side units. We use the to complete this work, which can provide us with realistic environment modeling, as well as dynamics and sensors simulations of various vehicle.

For more information, please visit .

Smart Intersection Sandbox Demonstration Platform

Fri, 09 Dec 2022 00:00:00 +0000

Coded Computation across Shared Heterogeneous Workers with Communication Delay

Sat, 01 Jan 2022 00:00:00 +0000

Coded Computation Across Shared Heterogeneous Workers with Communication Delay

Sat, 01 Jan 2022 00:00:00 +0000

Coverage Analyses on Directional Transmissions Ultra-Dense Networks with Imperfect Beam Alignment

Sat, 01 Jan 2022 00:00:00 +0000

DOLPHINS: Dataset for collaborative perception enabled harmonious and interconnected self-driving

Sat, 01 Jan 2022 00:00:00 +0000

Dynamic Scheduling for Over-the-Air Federated Edge Learning With Energy Constraints

Sat, 01 Jan 2022 00:00:00 +0000

Importance-Aware Data Pre-Processing and Device Scheduling for Multi-Channel Edge Learning

Sat, 01 Jan 2022 00:00:00 +0000

Importance-Aware Message Exchange and Prediction for Multi-Agent Reinforcement Learning

Sat, 01 Jan 2022 00:00:00 +0000

Online V2X Scheduling for Raw-Level Cooperative Perception

Sat, 01 Jan 2022 00:00:00 +0000

Time-Correlated Sparsification for Efficient Over-the-Air Model Aggregation in Wireless Federated Learning

Sat, 01 Jan 2022 00:00:00 +0000

Timely and Sustainable: Utilising Correlation in Status Updates of Battery-Powered and Energy-Harvesting Sensors Using Deep Reinforcement Learning

Sat, 01 Jan 2022 00:00:00 +0000

面向’双碳’战略的绿色通信与网络：挑战与对策

Sat, 01 Jan 2022 00:00:00 +0000

1st ISCA for 6G

Thu, 15 Apr 2021 00:00:00 +0000

A UoI-Optimal Policy for Timely Status Updates with Resource Constraint

Fri, 01 Jan 2021 00:00:00 +0000

Age-Optimal Scheduling for Heterogeneous Traffic with Timely-Throughput Constraint

Fri, 01 Jan 2021 00:00:00 +0000

Age-Optimal Scheduling for Heterogeneous Traffic with Timely-Throughput Constraint

Fri, 01 Jan 2021 00:00:00 +0000

AoI-Delay Tradeoff in Mobile Edge Caching With Freshness-Aware Content Refreshing

Fri, 01 Jan 2021 00:00:00 +0000

Coded Computation over Heterogeneous Workers with Random Task Arrivals

Fri, 01 Jan 2021 00:00:00 +0000

Device Scheduling and Resource Allocation for Federated Learning under Delay and Energy Constraints

Fri, 01 Jan 2021 00:00:00 +0000

Distributed Task Replication for Vehicular Edge Computing: Performance Analysis and Learning-based Algorithm

Fri, 01 Jan 2021 00:00:00 +0000

Error Analysis for Status Update from Sensors with Temporally and Spatially Correlated Observations

Fri, 01 Jan 2021 00:00:00 +0000

Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning

Fri, 01 Jan 2021 00:00:00 +0000

On the Capacity of Privacy-Preserving and Straggler-Robust Distributed Coded Computing

Fri, 01 Jan 2021 00:00:00 +0000

SMART: Situationally-Aware Multi-Agent Reinforcement Learning-Based Transmissions

Fri, 01 Jan 2021 00:00:00 +0000

The Impact of Interference Reflection on Reconfigurable Intelligent Surface-Aided Directional Transmissions

Fri, 01 Jan 2021 00:00:00 +0000

面向6G网络的信息时效性度量及研究进展

Fri, 01 Jan 2021 00:00:00 +0000

6th NEWTON Forum

Fri, 25 Dec 2020 00:00:00 +0000

Date: December 25–26, 2020 Venue: Multi-Function Hall, 11th Floor, Rohm Building, Department of Electronic Engineering, Tsinghua University

Background

In recent years, wireless communications and networking technologies have advanced rapidly, fundamentally transforming the way people communicate and their everyday lives. These technologies have also begun to permeate nearly every aspect of society, including intelligent transportation, smart manufacturing, and telemedicine. With further advances in emerging mobile communication technologies such as 5G/6G, artificial intelligence, and edge computing, we can expect future society to become smarter, more reliable, and more secure.

At the same time, wireless communications and networks are becoming increasingly complex, consuming ever-greater temporal, spatial, frequency, and energy resources. These demands directly or indirectly constrain the further deployment and development of networks. Addressing these challenges requires exploring new dimensions of resource utilization through interdisciplinary collaboration and incorporating theories and methods from related fields to reduce network complexity and improve service reliability.

The NEWTON (National Forum on Emerging Wireless Technologies and Open INnovations) Forum was established in response to these challenges. By bringing together outstanding young scholars and industry leaders from China and abroad in wireless communications and related fields, the forum explores cutting-edge technologies, systems, and standardization in wireless communications and networking, while highlighting recent advances in related disciplines. Its aim is to inspire new concepts, methods, and perspectives. As a small-scale seminar centered on panel discussions, the forum focuses on envisioning future developments, with particular emphasis on interdisciplinary advances and emerging trends in wireless communications.

The forum was jointly organized by the Department of Electronic Engineering at Tsinghua University and the Key Laboratory of Intelligent Connected Networks at the Beijing National Research Center for Information Science and Technology, with Journal of Communications and Information Networks (JCIN) as a supporting journal. The one-and-a-half-day event featured a keynote presentation by Academician Yu Quan entitled “Swarm Democratic Decision-Making and Brain-Inspired Computing,” along with three panel discussions on Intelligent Connectivity and Connected Intelligence, Green Information and Energy Informatics, and Intelligent Sensing and Collaboration. The discussions were lively, and the participating students gained valuable insights.

2020 Beijing International Automotive Exhibition

Fri, 02 Oct 2020 00:00:00 +0000

Date: October 2, 2020

On October 2, 2020, as China celebrated the 71st anniversary of the founding of the People’s Republic of China, NiuLab students visited the Beijing International Automotive Exhibition to learn about the latest developments in the connected vehicle industry.

Our first stop was Huawei’s exhibition booth, where staff introduced the company’s intelligent computing platform built around three layers: cloud, road, and vehicle. They also showcased the internal structure of intelligent electric vehicles, and the group took a commemorative photo at the booth.

Next came free exploration time! Everyone eagerly recommended premium car models to our senior student Yuxuan, while Qicheng showed off his skills in front of the car models.

After the exhibition, we enjoyed a delightful dinner together at Tanglang Restaurant. The atmosphere was lively, and we played a round of Pictionary at the table. Guangchao, meanwhile, declared that he had never watched Pleasant Goat and Big Big Wolf!

Finally, as the Chinese saying goes, “The moon is fullest on the sixteenth day of the lunar month.” Using a Huawei P30, we captured the moon after the Mid-Autumn Festival and wished NiuLab continued growth and ever-greater success in research!

A 2.92-Gb/s/W and 0.43-Gb/s/MG Flexible and Scalable CGRA-Based Baseband Processor for Massive MIMO Detection