Related papers: Optimizing Wireless Resource Management and Synchr…
The damage and the impact of natural disasters are becoming more destructive with the increase of urbanization. Today's metropolitan cities are not sufficiently prepared for the pre and post-disaster situations. Digital Twin technology can…
Dynamic distribution network reconfiguration (DNR) algorithms perform hourly status changes of remotely controllable switches to improve distribution system performance. The problem is typically solved by physical model-based control…
In this paper, a joint task, spectrum, and transmit power allocation problem is investigated for a wireless network in which the base stations (BSs) are equipped with mobile edge computing (MEC) servers to jointly provide computational and…
Residual radio resources are abundant in wireless networks due to dynamic traffic load, which can be exploited to support high throughput for serving non-real-time (NRT) traffic. In this paper, we investigate how to achieve this by resource…
Training Deep Neural Networks (DNNs) is a widely popular workload in both enterprises and cloud data centers. Existing schedulers for DNN training consider GPU as the dominant resource, and allocate other resources such as CPU and memory…
Space-air-ground integrated network (SAGIN) is a new type of wireless network mode. The effective management of SAGIN resources is a prerequisite for high-reliability communication. However, the storage capacity of space-air network segment…
Network slicing enables multiple virtual networks run on the same physical infrastructure to support various use cases in 5G and beyond. These use cases, however, have very diverse network resource demands, e.g., communication and…
This work addresses resource allocation challenges in multi-cell wireless systems catering to enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC) users. We present a distributed learning framework tailored…
We consider a joint uplink and downlink scheduling problem of a fully distributed wireless networked control system (WNCS) with a limited number of frequency channels. Using elements of stochastic systems theory, we derive a sufficient…
In this paper, we propose a digital twin (DT)-assisted resource demand prediction scheme to enhance prediction accuracy for multicast short video streaming. Particularly, we construct user DTs (UDTs) for collecting real-time user status,…
Drone base stations (DBSs) can enhance network coverage and area capacity by moving supply towards demand when required. This degree of freedom could be especially useful for future applications with extreme demands, such as ultra reliable…
The coordination of base stations in mobile access networks is an important approach to reduce harmful interference and to deliver high data rates to the users. Such coordination mechanisms, like Coordinated Multi-Point (CoMP) where…
Network slicing has been considered as one of the key enablers for 5G to support diversified services and application scenarios. This paper studies the distributed network slicing utilizing both the spectrum resource offered by…
The proliferation of diverse wireless services in 5G and beyond has led to the emergence of network slicing technologies. Among these, admission control plays a crucial role in achieving service-oriented optimization goals through the…
This work proposes and studies the distributed resource allocation problem in asynchronous and stochastic settings. We consider a distributed system with multiple workers and a coordinating server with heterogeneous computation and…
In this paper, we study the resource allocation algorithm design for distributed antenna multiuser networks with full-duplex (FD) radio base stations (BSs) which enable simultaneous uplink and downlink communications. The considered…
In this paper, we investigate dynamic resource allocation (DRA) problems for Internet of Things (IoT) in real-time cloud radio access networks (C-RANs), by combining gradient boosting approximation and deep reinforcement learning to solve…
Distributed cloud networking enables the deployment of a wide range of services in the form of interconnected software functions instantiated over general purpose hardware at multiple cloud locations distributed throughout the network. We…
Binarized Neural Networks (BNNs) can significantly reduce the inference latency and energy consumption in resource-constrained devices due to their pure-logical computation and fewer memory accesses. However, training BNNs is difficult…
A new network named the "Digital Twin Network" (DTN) uses the "Digital Twin" (DT) technology to produce virtual twins of real things. The network load and size continue to grow as a result of the development of 5G, the Internet of Things,…