Related papers: Ultra-Low-Latency Edge Inference for Distributed S…
Future mobile networks not only envision enhancing the traditional link quality and data rates of mobile broad band (MBB) links, but also development of new control channels to meet the requirements of delay sensitive use cases. In…
Rapid advancements in sixth-generation (6G) networks and large language models (LLMs) have paved the way for ubiquitous intelligence, wherein seamless connectivity and distributed artificial intelligence (AI) have revolutionized various…
The future Fifth Generation (5G) mobile cellular networks that are currently in research phase today enable broad range of services/applications beyond classical mobile communications. One key enabler for Ultra-Reliable services to be…
Edge intelligence (EI) allows resource-constrained edge devices (EDs) to offload computation-intensive AI tasks (e.g., visual object detection) to edge servers (ESs) for fast execution. However, transmitting high-volume raw task data (e.g.,…
The Internet of Things (IoT) has a significant demand in society due to its features, and it is constantly improving. In the context of wireless technology, Ultra-reliable and low-latency communication (URLLC) is one of the essential and…
With various time-sensitive tasks to be served, ultra-reliable and low-latency communications (URLLC) has become one of the most important scenarios for the fifth generation (5G) wireless communications. The end-to-end delay from the…
Accurately predicting end-to-end network latency is essential for enabling reliable task offloading in real-time edge computing applications. This paper introduces a lightweight latency prediction scheme based on rational modelling that…
The large artificial intelligence models (LAMs) show strong capabilities in perception, reasoning, and multi-modal understanding, and can enable advanced capabilities in low-altitude edge intelligence. However, the deployment of LAMs at the…
With the introduction of shared spectrum sensing and beam-forming based multi-antenna transceivers, 5G networks demand spectrum sensing to identify opportunities in time, frequency, and spatial domains. Narrow beam-forming makes it…
Embodied AI requires sub-second inference near the Radio Access Network (RAN), but deployments span heterogeneous tiers (on-device, RAN-edge, cloud) and must not disrupt real-time baseband processing. We report measurements from a 5G…
The ability to perform computation on devices, such as smartphones, cars, or other nodes present at the Internet of Things leads to constraints regarding bandwidth, storage, and energy, as most of these devices are mobile and operate on…
Sixth-generation (6G) networks anticipate intelligently supporting a massive number of coexisting and heterogeneous slices associated with various vertical use cases. Such a context urges the adoption of artificial intelligence (AI)-driven…
In this paper, we propose a novel algorithm for energy-efficient, low-latency, accurate inference at the wireless edge, in the context of 6G networks endowed with reconfigurable intelligent surfaces (RISs). We consider a scenario where new…
The rapid evolution of forthcoming sixth-generation (6G) wireless networks necessitates the seamless integration of artificial intelligence (AI) with wireless communications to support emerging intelligent applications that demand both…
AI WiFi offload is emerging as a promising approach for providing large language model (LLM) services to resource-constrained wireless devices. However, unlike conventional edge computing, LLM inference over WiFi must jointly address…
In this letter, we analyze the achievable rate of ultra-reliable low-latency communications (URLLC) in a randomly modeled wireless network. We use two mathematical tools to properly characterize the considered system: i) stochastic geometry…
Rare events, despite their infrequency, often carry critical information and require immediate attentions in mission-critical applications such as autonomous driving, healthcare, and industrial automation. The data-intensive nature of these…
The combination of Integrated Sensing and Communication (ISAC) and Mobile Edge Computing (MEC) enables devices to simultaneously sense the environment and offload data to the base stations (BS) for intelligent processing, thereby reducing…
This work investigates an integrated sensing and edge artificial intelligence (ISEA) system, where multiple devices first transmit probing signals for target sensing and then offload locally extracted features to the access point (AP) via…
Low earth orbit (LEO) mega-constellations, integrating government space systems and commercial practices, have emerged as enabling technologies for the sixth generation (6G) networks due to their good merits of global coverage and…