相关论文: ViWi: A Deep Learning Dataset Framework for Vision…

Artificial intelligence is a key enabler for next-generation wireless communication and sensing. Yet, today's learning-based wireless techniques do not generalize well: most models are task-specific, environment-dependent, and limited to…

As data generation increasingly takes place on devices without a wired connection, machine learning (ML) related traffic will be ubiquitous in wireless networks. Many studies have shown that traditional wireless protocols are highly…

Deep learning-based vision is characterized by intricate frameworks that often necessitate a profound understanding, presenting a barrier to newcomers and limiting broad adoption. With many researchers grappling with the constraints of…

We present the DeepWiFi protocol, which hardens the baseline WiFi (IEEE 802.11ac) with deep learning and sustains high throughput by mitigating out-of-network interference. DeepWiFi is interoperable with baseline WiFi and builds upon the…

The ongoing evolution of 5G and its enhanced version, 5G+, has significantly transformed the telecommunications landscape, driving an unprecedented demand for ultra-high-speed data transmission, ultra-low latency, and resilient…

The growing landscape of emerging wireless applications is a key driver toward the development of novel wireless system designs. Such a design can be based on the metaverse that uses a virtual model of the physical world systems along with…

Prior to the era of artificial intelligence and big data, wireless communications primarily followed a conventional research route involving problem analysis, model building and calibration, algorithm design and tuning, and holistic and…

The advent of next-generation wireless communication systems heralds an era characterized by high data rates, low latency, massive connectivity, and superior energy efficiency. These systems necessitate innovative and adaptive strategies…

Recent advances in generative models have empowered impressive layered image generation, yet their success is largely confined to graphic design domains. The layering of in-the-wild images remains an underexplored problem, limiting…

Large AI models have been widely adopted in wireless communications for channel modeling, beamforming, and resource optimization. However, most existing efforts remain limited to single-modality inputs and channel-specific objec- tives,…

Accurate, real-time wireless signal prediction is essential for next-generation networks. However, existing vision-based frameworks often rely on computationally intensive models and are also sensitive to environmental interference. To…

The next-generation of wireless networks will enable many machine learning (ML) tools and applications to efficiently analyze various types of data collected by edge devices for inference, autonomy, and decision making purposes. However,…

As wireless networks evolve towards high mobility and providing better support for connected vehicles, a number of new challenges arise due to the resulting high dynamics in vehicular environments and thus motive rethinking of traditional…

A comprehensive artificial intelligence system needs to not only perceive the environment with different `senses' (e.g., seeing and hearing) but also infer the world's conditional (or even causal) relations and corresponding uncertainty.…

While commonly used for communication purposes, an increasing number of recent studies consider WiFi for sensing. In particular, wireless signals are altered (e.g., reflected and attenuated) by the human body and objects in the environment.…

With the rapid development of Internet-of-Things (IoT) technology and machine-type communications, various emerging applications appear in industrial productions and our daily lives. Among these, applications like industrial sensing and…

Recent years have witnessed a growing interest in Wi-Fi-based gesture recognition. However, existing works have predominantly focused on closed-set paradigms, where all testing gestures are predefined during training. This poses a…

Signal recognition is a spectrum sensing problem that jointly requires detection, localization in time and frequency, and classification. This is a step beyond most spectrum sensing work which involves signal detection to estimate "present"…

Modern Unmanned Aerial Vehicles equipped with state of the art artificial intelligence (AI) technologies are opening to a wide plethora of novel and interesting applications. While this field received a strong impact from the recent AI…

Recent advances in Wireless Physical Layer Foundation Models (WPFMs) promise a new paradigm of universal Radio Frequency (RF) representations. However, these models inherit critical limitations found in deep learning such as the lack of…