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The impending spectrum congestion imposed by the emergence of new bandwidth-thirsty applications may be mitigated by the integration of radar and classic communications functionalities in a common system. Furthermore, the merger of a…
Future Industrial 4.0 applications in the 6G era is calling for high dependability that goes far beyond the current ultra-reliable low latency communication (URLLC), and therewith proposed critical challenges to the communication…
Traditional single-modality sensing faces limitations in accuracy and capability, and its decoupled implementation with communication systems increases latency in bandwidth-constrained environments. Additionally, single-task-oriented…
As a key technology in metaversa, wireless ultimate extended reality (XR) has attracted extensive attentions from both industry and academia. However, the stringent latency and ultra-high data rates requirements have hindered the…
Personalized expression recognition (ER) involves adapting a machine learning model to subject-specific data for improved recognition of expressions with considerable interpersonal variability. Subject-specific ER can benefit significantly…
Federated learning is a privacy-preserving approach to train a global model at a central server by collaborating with wireless devices, each with its own local training data set. In this paper, we present a compressive sensing approach for…
Driven by the vision of intelligent connection of everything and digital twin towards 6G, a myriad of new applications, such as immersive extended reality, autonomous driving, holographic communications, intelligent industrial internet,…
Accurate beam prediction is a key enabler for next-generation wireless communication systems. In this paper, we propose a multimodal large language model (LLM)-based beam prediction framework that effectively utilizes contextual…
Semantic communication in the 6G era has been deemed a promising communication paradigm to break through the bottleneck of traditional communications. However, its applications for the multi-user scenario, especially the broadcasting case,…
Recently, emotion recognition based on physiological signals has emerged as a field with intensive research. The utilization of multi-modal, multi-channel physiological signals has significantly improved the performance of emotion…
The ability to associate touch with other modalities has huge implications for humans and computational systems. However, multimodal learning with touch remains challenging due to the expensive data collection process and non-standardized…
With the growing complexity and dynamics of the mobile communication networks, accurately predicting key system parameters, such as channel state information (CSI), user location, and network traffic, has become essential for a wide range…
The latest discussions on the upcoming sixth Generation (6G) of wireless communications are envisioning future networks as a unified communications, sensing, and computing platform. The recently conceived concept of the smart radio…
6G technology targets to revolutionize the mobility industry by revamping the role of wireless connections. In this article, we draw out our vision on an intelligent, cooperative, and sustainable mobility environment of the future,…
Joint image-text embedding is the bedrock for most Vision-and-Language (V+L) tasks, where multimodality inputs are simultaneously processed for joint visual and textual understanding. In this paper, we introduce UNITER, a UNiversal…
This paper introduces the distributed and intelligent integrated sensing and communications (DISAC) concept, a transformative approach for 6G wireless networks that extends the emerging concept of integrated sensing and communications…
Sixth-generation (6G) mobile communications have attracted substantial attention in the global research community of information and communication technologies (ICTs). 6G systems are expected to support not only extended 5G usage scenarios…
The recently completed 5G new radio standard is a result of several cutting-edge technologies, including massive multiple-input multiple-output (MIMO), millimeter (mm)-Wave communication and network densification. However, these…
The 6th generation (6G) wireless networks will likely to support a variety of capabilities beyond communication, such as sensing and localization, through the use of communication networks empowered by advanced technologies. Integrated…
Multimodal learning aims to imitate human beings to acquire complementary information from multiple modalities for various downstream tasks. However, traditional aggregation-based multimodal fusion methods ignore the inter-modality…