Related papers: Gleam: An RDMA-accelerated Multicast Protocol for …
Dual-Functional Radar-Communication (DFRC) system is an essential and promising technique for beyond 5G. In this work, we propose a powerful and unified multi-antenna DFRC transmission framework, where an additional radar sequence is…
Splitting the inference model between device, edge server, and cloud can improve the performance of EI greatly. Additionally, the non-orthogonal multiple access (NOMA), which is the key supporting technologies of B5G/6G, can achieve massive…
Network traffic is difficult to monitor and analyze, especially in high-bandwidth networks. Performance analysis, in particular, presents extreme complexity and scalability challenges. GPU (Graphics Processing Unit) technology has been…
Conventional wisdom holds that an efficient interface between an OS running on a CPU and a high-bandwidth I/O device should use Direct Memory Access (DMA) to offload data transfer, descriptor rings for buffering and queuing, and interrupts…
Recent trends suggest that cognitive radio based wireless networks will be frequency agile and the nodes will be equipped with multiple radios capable of tuning across large swaths of spectrum. The MAC scheduling problem in such networks…
Existing distributed machine learning (DML) systems focus on improving the computational efficiency of distributed learning, whereas communication aspects have received less attention. Many DML systems treat the network as a blackbox. Thus,…
Emerging AI-enabled applications such as augmented/virtual reality (AR/VR) leverage multiple deep neural network (DNN) models for sub-tasks such as object detection, hand tracking, and so on. Because of the diversity of the sub-tasks, the…
The popularity of mobile devices results in the availability of enormous data and computational resources at the network edge. To leverage the data and resources, a new machine learning paradigm, called edge learning, has emerged where…
A new non-orthogonal multiple access scheme performing simultaneous transmission to multiple users characterized by different signal-to-noise ratios is proposed. Different users are multiplexed by storing their codewords into a multiplexing…
As distributed machine learning (ML) workloads scale to thousands of GPUs connected by high-speed interconnects, tail latency in collective communication has become a major bottleneck. Existing RDMA transports, such as RoCE, IRN, SRNIC, and…
Many existing medium access control (MAC) protocols utilize past information (e.g., the results of transmission attempts) to adjust the transmission parameters of users. This paper provides a general framework to express and evaluate…
In the last decade, the demand for Internet applications has been increased, which increases the number of data centers across the world. These data centers are usually connected to each other using long-distance and high-speed networks. As…
The demand for providing multicast services in cellular networks is continuously and fastly increasing. In this work, we propose a non-orthogonal transmission framework based on layered-division multiplexing (LDM) to support multicast and…
Generative AI (GenAI) services powered by large language models (LLMs) increasingly deliver real-time interactions, yet existing 5G multi-access edge computing (MEC) architectures often treat communication and computing as separate domains,…
RDMA-empowered cloud services are gradually deployed across datacenters (DCs) with multiple paths, which exhibit new properties of path asymmetry, delayed congestion signals, and simultaneous flow routing collisions, and further fail…
Offloading communication to existing direct memory access (DMA) engines, available on most state-of-the-art commercial GPUs, has emerged as an interesting and low-cost solution to efficiently overlap computation and communication in machine…
This paper investigates a new class of carrier-sense multiple access (CSMA) protocols that employ deep reinforcement learning (DRL) techniques for heterogeneous wireless networking, referred to as carrier-sense deep-reinforcement learning…
Cognitive Radio Networks (CRN) have enabled us to efficiently reuse the underutilized radio spectrum. The MAC protocol in CRN defines the spectrum usage by sharing the channels efficiently among users. In this paper we propose a novel TDMA…
Full-duplex (FD) wireless is an attractive communication paradigm with high potential for improving network capacity and reducing delay in wireless networks. Despite significant progress on the physical layer development, the challenges…
Limited bandwidth resources and higher energy efficiency requirements motivate incorporating multicast and broadcast transmission into the next-generation cellular network architectures, particularly for multimedia streaming applications.…