In this paper, we propose a method to design the training data that can support robust generalization of trained neural networks to unseen channels. The proposed design that improves the generalization is described and analysed. It avoids the requirement of online training for previously unseen channels, as this is a memory and processing intensive solution, especially for battery powered mobile terminals. To prove the validity of the proposed method, we use the channels modelled by different standards and fading modelling for simulation. We also use an attention-based structure and a convolutional neural network to evaluate the generalization results achieved. Simulation results show that the trained neural networks maintain almost identical performance on the unseen channels.
A Novel Spatiotemporal Correlation Anomaly Detection Method Based on Time-Frequency-Domain Feature Fusion and a Dynamic Graph Neural Network in Wireless Sensor Network
Intelligent reflecting surface (IRS) is a promising technology to boost the efficiency of wireless energy transfer (WET) systems. However, for a multiuser WET system, simultaneous multi-beam energy transmission is generally required to achieve the maximum performance, which may not be implemented by using the IRS having only a single set of coefficients. As a result, it remains unknowns how to exploit the IRS to approach such a performance upper bound. To answer this question, we aim to maximize the total harvested energy of a multiuser WET system subject to the user fairness constraints and t…
We consider the problem of resource allocation in large scale wireless networks. When contextualizing wireless network structures as graphs, we can model the limits of very large wireless systems as manifolds. To solve the problem in the machine learning framework, we propose the use of Manifold Neural Networks (MNNs) as a policy parametrization. In this work, we prove the stability of MNN resource allocation policies under the absolute perturbations to the Laplace-Beltrami operator of the manifold, representing system noise and dynamics present in wireless systems. These results establish the…
The next 5 th generation (5G) and above ultra-high speed, ultra-low latency, and extremely high reliable communication systems will consist of heterogeneous networks. These heterogeneous networks will consist not only radio frequency (RF) based systems but also optical wireless based systems. Hybrid architectures among different networks is an excellent approach for achieving the required level of service quality. In this paper, we provide the opportunities bring by hybrid systems considering RF as well as optical wireless based communication technologies. We also discuss about the key researc…
Highly sensitive smart sensors for early fire detection with remote warning capabilities are urgently required to improve the fire safety of combustible materials in diverse applications. The highly-sensitive fire alarm can detect fire situation within a short time quickly when a fire disaster is about to occur, which is conducive to achieve fire tuned. Herein, a novel fire alarm is designed by using flame-retardant cellulose paper loaded with graphene oxide (GO) and two-dimensional titanium carbide (Ti3C2, MXene). Owing to the excellent temperature dependent electrical resistance switching ef…
By serving as an analog to traffic signal lights, communication signaling for drone to drone communications holds the key to the success of advanced air mobility (AAM) in both urban and rural settings. Deployment of AAM applications such as air taxis and air ambulances, especially at large-scale, requires a reliable channel for a point-to-point and broadcast communication between two or more aircraft. Achieving such high reliability, in a highly mobile environment, requires communication systems designed for agility and efficiency. This paper presents the foundations for establishing and maint…
WirelessAgent++: Automated Agentic Workflow Design and Benchmarking for Wireless Networks
College of Electronics and Information Engineering, Shenzhen University（深圳大学电子与信息工程学院）；Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology（香港理工大学电子与计算机工程系）
Optical wireless communication is an effective potential solution for enabling high speed next generation cellular networks. In this paper, laser sources, in particular, vertical-cavity surface-emitting (VCSEL) lasers are used for data transmission due to their high modulation speed compared with light emitting diode (LED) sources. To manage multi-user interference, rate splitting (RS) is implemented where the message of a user is split into common and private parts. However, the performance of RS is limited in high density networks. Therefore, hierarchical rate splitting (HRS) particularly su…
We consider a cell-free wireless system operated in Time Division Duplex (TDD) mode with user-centric clusters of remote radio units (RUs). Since the uplink pilot dimensions per channel coherence slot is limited, co-pilot users might incur mutual pilot contamination. In the current literature, it is assumed that the long-term statistical knowledge of all user channels is available. This enables Minimum Mean-Square Error channel estimation or simplified dominant subspace projection, which achieves significant pilot decontamination under certain assumptions on the channel covariance matrices. Ho…
Simultaneous wireless information and power transfer (SWIPT) is a remarkable technology to support both the data and the energy transfer in the era of Internet of Things (IoT). In this paper, we proposed a long-range optical wireless information and power transfer system utilizing retro-reflectors, a gain medium, a telescope internal modulator to form the resonant beam, achieving high-power and high-rate SWIPT. We adopt the transfer matrix, which can depict the beam modulated, resonator stability, transmission loss, and beam distribution. Then, we provide a model for energy harvesting and data…
KTH - Royal Institute of Technology（KTH皇家理工学院）；MIT - Massachusetts Institute of Technology（麻省理工学院）；Princeton University（普林斯顿大学）
As data generation increasingly takes place on devices without a wired connection, machine learning (ML) related traffic will be ubiquitous in wireless networks. Many studies have shown that traditional wireless protocols are highly inefficient or unsustainable to support ML, which creates the need for new wireless communication methods. In this survey, we give an exhaustive review of the state-of-the-art wireless methods that are specifically designed to support ML services over distributed datasets. Currently, there are two clear themes within the literature, analog over-the-air computation …
We propose a data-driven approach for power allocation in the context of federated learning (FL) over interference-limited wireless networks. The power policy is designed to maximize the transmitted information during the FL process under communication constraints, with the ultimate objective of improving the accuracy and efficiency of the global FL model being trained. The proposed power allocation policy is parameterized using a graph convolutional network and the associated constrained optimization problem is solved through a primal-dual algorithm. Numerical experiments show that the propos…
In this paper, we design and experiment a far-field wireless power transfer (WPT) architecture based on distributed antennas, so-called WPT DAS, that dynamically selects transmit antenna and frequency to increase the output dc power. Uniquely, spatial and frequency diversities are jointly exploited in the proposed WPT DAS with low complexity, low cost, and flexible deployment to combat the wireless fading channel. A numerical experiment is designed to show the benefits using antenna and frequency selections in spatially and frequency selective fading channels for single-user and multi-user cas…
Blockchain has been deemed as a promising solution for providing security and privacy protection in the next-generation wireless networks. Large-scale concurrent access for massive wireless devices to accomplish the consensus procedure may consume prohibitive communication and computing resources, and thus may limit the application of blockchain in wireless conditions. As most existing consensus protocols are designed for wired networks, directly apply them for wireless users may exhaust their scarce spectrum and computing resources. In this paper, we propose AirCon, a byzantine fault-tolerant…
This paper presents a wireless neural recording system featuring energy-efficient data compression and encryption. An ultra-high efficiency is achieved by leveraging compressed sensing (CS) for simultaneous data compression and encryption. CS enables sub-Nyquist sampling of neural signals by taking advantage of its intrinsic sparsity. It simultaneously encrypts the data with the sampling matrix being the cryptographic key. To share the key over an insecure wireless channel, we implement an elliptic-curve cryptography (ECC) based key exchanging protocol. The CS operation is executed in a custom…
