Related papers: Wide Area Network Intelligence with Application to…
We consider distributed machine learning at the wireless edge, where a parameter server builds a global model with the help of multiple wireless edge devices that perform computations on local dataset partitions. Edge devices transmit the…
The emerging trend of ubiquitous and pervasive computing aims at embedding everyday devices such as wristwatches, smart phones, home video systems, autofocus cameras, intelligent vehicles, musical instruments, kitchen appliances etc. with…
Next generation of wireless local area networks (WLANs) will operate in dense, chaotic and highly dynamic scenarios that in a significant number of cases may result in a low user experience due to uncontrolled high interference levels.…
Human-centric applications such as virtual reality and immersive gaming will be central to the future wireless networks. Common features of such services include: a) their dependence on the human user's behavior and state, and b) their need…
Cognitive radio is an intelligent radio that can be programmed and configured dynamically to fully use the frequency resources that are not used by licensed users. It defines the radio devices that are capable of learning and adapting to…
The ability to intelligently utilize resources to meet the need of growing diversity in services and user behavior marks the future of wireless communication systems. Intelligent wireless communications aims at enabling the system to…
Edge intelligence requires to fast access distributed data samples generated by edge devices. The challenge is using limited radio resource to acquire massive data samples for training machine learning models at edge server. In this…
In industrial environments, an increasing amount of wireless devices are used, which utilize license-free bands. As a consequence of these mutual interferences of wireless systems might decrease the state of coexistence. Therefore, a…
It has been a long-held belief that judicious resource allocation is critical to mitigating interference, improving network efficiency, and ultimately optimizing wireless communication performance. The traditional wisdom is to explicitly…
Predicting the behavior of a wireless link in terms of, e.g., the frame delivery ratio, is a critical task for optimizing the performance of wireless industrial communication systems. This is because industrial applications are typically…
A Web service is a software system designed to support interoperable machine-to-machine interaction over a network. Web services provide a standard means of interoperating between different software applications, running on a variety of…
Adaptive inference is a promising technique to improve the computational efficiency of deep models at test time. In contrast to static models which use the same computation graph for all instances, adaptive networks can dynamically adjust…
Driven by the advent of sophisticated and ubiquitous applications, and the ever-growing need for information, wireless networks are without a doubt steadily evolving into profoundly more complex and dynamic systems. The user demands are…
In a multi-agent system, agents can cooperatively learn a model from data by exchanging their estimated model parameters, without the need to exchange the locally available data used by the agents. This strategy, often called federated…
Caching at the edge is a promising technique to cope with the increasing data demand in wireless networks. This paper analyzes the performance of cellular networks consisting of a tier macro-cell wireless backhaul nodes overlaid with a tier…
Along with the rapid developments in communication technologies and the surge in the use of mobile devices, a brand-new computation paradigm, Edge Computing, is surging in popularity. Meanwhile, Artificial Intelligence (AI) applications are…
Wireless systems are expanding their purposes, from merely connecting humans and things to connecting intelligence and opportunistically sensing of the environment through radio-frequency signals. In this paper, we introduce the concept of…
The optimal scheduling of interfering links in a dense wireless network with full frequency reuse is a challenging task. The traditional method involves first estimating all the interfering channel strengths then optimizing the scheduling…
Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and…
We present a study of deep learning applied to the domain of network traffic data forecasting. This is a very important ingredient for network traffic engineering, e.g., intelligent routing, which can optimize network performance,…