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Introduction
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June 2017 - October 2022
Shanghai Advanced Research Institute, Chinese Academy of Sciences
Position
- Professor (Full)
Publications
Publications (113)
The Reconfigurable Intelligent Surface (RIS) is seen as one of the most prospective technologies for next-generation networks. RIS can form virtual line-of-sight (LoS) link during non-line-of-sight (NLoS) transmission to improve system performance with low power consumption, especially for urban scenarios. In this paper, for an RIS-aided system, we...
The bit error rate (BER) analysis has been recognized as an effective approach to investigate the problems in nonorthogonal multiple access (NOMA) systems, such as inter-user interference (IUI) and error propagation. However, the impact of asymmetric channels on adaptive modulation and coding (AMC) will bring great challenges to the BER analysis of...
In steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs), the limited availability of frequency resources inherently constrains the scale of the instruction set, presenting a substantial challenge for efficient communication. As the number of stimuli increases, the comfort level of the stimulus interface also becomes i...
Recent advances in neuroscience, neuromorphic intelligence, and brain–computer interface (BCI) technologies have created a need for fast, efficient, and convenient electroencephalogram (EEG) data acquisition systems. However, the existing equipment was limited in its flexibility, restricting non-invasive studies to research or medical settings. To...
With the global promotion of fifth-generation (5G) communications, researches for sixth generation (6G) communications are being globally launched from various perspectives. Industrial Internet-of-Things (IIoT), which is the most representative application that reflects the ubiquitous connectivity characteristics of 6G, has attracted much attention...
Objective
The brain-computer interface (BCI) systems based on rapid serial visual presentation (RSVP) have been widely utilized for the detection of target and non-target images. Collaborative brain-computer interface (cBCI) effectively fuses electroencephalogram (EEG) data from multiple users to overcome the limitations of low single-user performa...
As a vital enabler for ubiquitous connectivity in space-air-ground integrated networks, the satellite-terrestrial communication system has been envisioned to be a crucial complement to terrestrial networks because of its superior capability of providing wide coverage. However, there are many practical limitations that degrade system performance, in...
Due to the influence of sparse scattering, wave movement and variable climate, maritime wireless channel modeling is particularly difficult. In this letter, a maritime channel measurement scheme is designed and implemented. A clustering algorithm-based channel modeling framework is further proposed to process the measurement data and build a mariti...
Brain-computer interfaces (BCIs) have been widely focused and extensively studied in recent years for their huge prospect of medical rehabilitation and commercial applications. Transfer learning exploits the information in the source domain and applies in another different but related domain (target domain), and is therefore introduced into the BCI...
As an essential cognitive function, attention has been widely studied and various indices based on EEG have been proposed for its convenience and easy availability for real-time attention monitoring. Although existing indices based on spectral power of empirical frequency bands are able to describe the attentional state in some way, the reliability...
Objective:
The information transfer rate (ITR) is widely accepted as a performance metric for generic brain-computer interface (BCI) spellers, while it is noticeable that the communication speed given by ITR is actually an upper bound which however can never be reached in real systems. A new performance metric is therefore needed.
Methods:
In th...
Steady-state visual evoked potential brain-computer interfaces (SSVEP-BCI) have attracted significant attention due to their ease of deployment and high performance in terms of information transfer rate (ITR) and accuracy, making them a promising candidate for integration with consumer electronics devices. However, as SSVEP characteristics are dire...
Recently, non-orthogonal multiple access (NOMA) has become prevalent in 5G communication. However, the traditional successive interference cancellation (SIC) receivers for NOMA still encounter challenges. The near-far effect between the users and the base stations (BS) results in a higher bit error rate (BER) for the SIC receiver. Additionally, the...
We proposed a brain‐to‐brain interface (B2BI) that enabled effective control of mouse turning behavior by human mind using an implantable, ultra‐flexible neural probe. The neural probe was capable of writing in neural signals to the mouse brain, with effective electrical stimulation observed at a low current of 5 μA. Additionally, a wireless electr...
Brain-computer interfaces (BCIs) aim to directly bridge the human brain and the outside world through acquiring and processing the brain signals in real time. In recent two decades, tremendous progress has been made in terms of BCI paradigms and decoding algorithms. The information transfer rate of the BCI systems has been significantly enhanced, a...
Most phase-shift models for reconfigurable intelligent surfaces (RIS) rely on ideal models of the reflection coefficient, i.e., assuming full-reflection amplitude and constant reflection coefficient for any incident angle. Since electromagnetic waves incident on RIS from varying directions exhibit different responses, ideal phase-shift models may o...
To realize the 6G maritime broadband communications, it is essential to address the challenge of limited coverage caused by the unique characteristics of maritime environment. Fortunately, as a prevalent maritime atmospheric layer with super refraction, evaporation ducts present an opportunity for extending long-distance coverage and enhancing the...
Atmospheric ducts can result in severe remote interference in time-division duplex (TDD) communication systems of the sixth-generation (6G). The accurate remote interference discrimination is crucial for ensuring communication reliability. In this paper, an evolutionary ensemble learning method is originally proposed, that allows effectively discri...
Non-orthogonal multiple access (NOMA) is a promising technology for the next generation of wireless networks. However, maximizing energy efficiency (EE) for NOMA systems may cause unbearable near-far unfairness. In this letter, a novel fairness-aware energy-efficient power allocation for uplink NOMA systems with imperfect successive interference ca...
Traditional single-modality brain-computer interface (BCI) systems are limited by their reliance on a single characteristic of brain signals. To address this issue, incorporating multiple features from EEG signals can provide robust information to enhance BCI performance. In this study, we designed and implemented a novel hybrid paradigm that combi...
As a significant aspect of cognition, attention has been extensively studied and numerous measurements have been developed based on brain signal processing. Although existing attentional state classification methods have achieved good accuracy by extracting a variety of handcrafted features, spatial features have not been fully explored. This paper...
Engagement ability plays a fundamental role in allocating attentional resources and helps us perform daily tasks efficiently. Therefore, it is of great importance to recognize engagement level. Electroencephalography is frequently employed to recognize engagement for its objective and harmless nature. To fully exploit the information contained in E...
The development of computation-intensive and delay-sensitive smart applications has put forward great challenge to the current cellular networks. To cope with this challenge, unmanned aerial vehicles (UAVs) providing additional on-demand communication and computing services has become a promising technology. This letter proposes a novel task offloa...
Unmanned aerial vehicles (UAVs) providing additional on-demand communication and computing services have become a promising technology. However, the limited energy supply of UAVs, which constrains their service duration, has emerged as an obstacle in UAV-enabled networks. In this context, a novel task offloading framework is proposed in UAV-enabled...
The construction of a new power system based on new energy sources can support the successful transition of energy consumption toward a low-carbon environment. Large-scale clusters of electric vehicles (EVs) are an important reserve measure supporting the flexibility of the new power system. To summarize the roles of EVs as a reserve measure in pra...
For maritime broadband communications, atmospheric ducts can enable beyond line-of-sight communications or cause severe interference. Due to the strong spatial–temporal variability of atmospheric conditions in near-shore areas, atmospheric ducts have inherent spatial heterogeneity and suddenness. This paper aims to evaluate the effect of horizontal...
With the continuous development of wireless communication technology, the number of access devices continues to soar, which poses a grate challenge to the already scarce spectrum resources. Meanwhile, 6G will be an era of air-space-terrestrial-sea integration, and satellite spectrum resources are also very tight in the context of giant constellatio...
In recent years, deep neural network-based transfer learning (TL) has shown outstanding performance in EEG-based motor imagery (MI) brain-computer interface (BCI). However, due to the long preparation for pre-trained models and the arbitrariness of source domain selection, using deep transfer learning on different datasets and models is still chall...
Maritime channel modeling can be affected by some key time-varying environmental factors. The ducting effect is one of the thorniest factors since it causes anomalous propagation enhancement and severe co-channel interference. Moreover, the atmospheric attenuation is much more severe in the ocean environment, resulting in shorter coverage distance...
The sixth-generation (6G) network will shift its focus to supporting everything including various machine-type devices (MTDs) in an every-one-centric manner. To ubiquitously cover the MTDs working in rural and disastrous areas, satellite communications become indispensable, while mobile edge computing (MEC) also plays an increasingly crucial role....
The Internet-of-Things (IoT) massive access is a significant scenario for sixth-generation (6G) communications. However, low-power IoT devices easily suffer from remote interference caused by the atmospheric duct under the 6G time-division duplex (TDD) mode. It causes distant downlink wireless signals to propagate beyond the designed protection dis...
With the rapid growth in the requirements of the Internet of Things (IoT), the scarcity of spectrum resources is becoming serious. Non-orthogonal multiple access (NOMA) and spectrum sensing offer the opportunity of addressing spectrum shortage to some extent. In particular, NOMA stably enables multiple users to share the same frequency band, while...
The sixth-generation communication networks aim to integrate space, air, and ground communications into a robust network. However, maritime communications are confronted with the challenge of the atmospheric duct, which could capture wireless signals and propagate beyond the line of sight. In this paper, a parabolic equation-based modeling approach...
In this letter, we investigate the ergodic capacity of the Relay-Reconfigurable Intelligent Surface (Relay-RIS) system exploiting the three-dimensional channel model, which is different from existing works ignoring antenna height. Specifically, we propose a novel three-dimensional statistical channel for the Relay-RIS system. The upper bound expres...
With the rapid increase of the demand for the Internet of Things (IoT), spectrum resources have incremental challenges. Non-orthogonal Multiple Access (NOMA) and spectrum sensing are considered key candidate technologies for next-generation wireless communications to improve spectrum utilization. Nevertheless, using both technologies at the same ti...
The sixth-generation (6G) network will shift its focus to supporting everything including various machine-type devices (MTDs) in an everyone-centric manner. To ubiquitously cover the MTDs working in rural and disastrous areas, satellite communications become indispensable, while mobile edge computing (MEC) also plays an increasingly crucial role. T...
Non-orthogonal multiple access (NOMA) technology allows multiple users to share the same spectrum resource. Meanwhile, the technology of spectrum sensing enables us to find the free time of the spectrum. Both two technologies can significantly improve spectrum efficiency. In this paper, we attempt to combine the two techniques, for meeting the high...
With the rollout of fifth-generation (5G) communications, researches for beyond fifth generation (B5G) communications are being launched globally. In this paper, we explore for possible ways to integrate two promising techniques, including non-orthogonal multiple access (NOMA) and statistical signal transmission (SST), seeking a feasible perspectiv...
The exponential growth of mobile terminals and the explosion of data volume are promoting the continuous evolution of mobile communication network and also increasing the complexity of the system. Meanwhile, 5G system-level simulation also requires more complex operations and more data processing. Conventional system simulation platform based on CP...
In this paper, we propose a novel deep unsupervised learning-based approach that jointly optimizes antenna selection and hybrid beamforming to improve the hardware and spectral efficiencies of massive multiple-input-multiple-output (MIMO) downlink systems. By employing ResNet to extract features from the channel matrices, two neural networks, i.e.,...
Brain-computer interface based on steady-state visual evoked potential (SSVEP-BCI) has been widely concerned because of its highest SNR of EEG signals. This kind of BCIs needs to modulate the control instructions with visual stimuli. However, a large number of visual stimuli will induce strong visual fatigue, and occupy a large area of screen space...
Millimeter wave (mmWave) multi-user massive multi-input multi-output (MIMO) is a promising technique for the next generation communication systems. However, the hardware cost and power consumption grow significantly as the number of radio frequency (RF) components increases, which hampers the deployment of practical massive MIMO systems. To address...
Non-orthogonal multiple access (NOMA) is one of candidate technologies in the next generation radio access networks, in which the joint maximum-likelihood (JML) detector has the optimal estimation performance. In this paper, we propose a rotated-constellation based method to regularize the decision boundaries of received constellation. Through regu...
This letter considers the beamforming optimization of a heterogeneous intelligent reflective surfaces (IRSs)-aided downlink wireless system. We aim to maximize the achievable sum rate by jointly optimizing the active beamforming at base station (BS) and the passive phase shifts at IRSs, respectively, when maximum transmit power constraint at the BS...
In this paper, we develop a dynamic detection network (DDNet) based detector for multiple-input multiple-output (MIMO) systems. By constructing an improved DetNet (IDetNet) detector and the OAMPNet detector as two independent network branches, the DDNet detector performs sample-wise dynamic routing to adaptively select a better one between the IDet...
Power allocation has a significant impact on sum rate in non-orthogonal multiple access (NOMA) systems. In this paper, we propose a dynamic power allocation (D-NOMA) strategy that can optimize the sum rate compared with the fixed power allocation (F-NOMA) method in uplink NOMA systems. In particular, we first design an evaluation model to analyze s...
In this paper, we develop a dynamic detection network (DDNet) based detector for multiple-input multiple-output (MIMO) systems. By constructing an improved DetNet (IDetNet) detector and the OAMPNet detector as two independent network branches, the DDNet detector performs sample-wise dynamic routing to adaptively select a better one between the IDet...
In order to reduce the downlink training overhead of mmWave communications, we propose a novel downlink beamforming strategy using the uplink sub-6GHz channel and downlink mmWave pilots that are sent from a few active antennas. Specifically, we design a novel dual-input neural network architecture, called FusionNet, to merge the sub-6GHz channel an...
Non-orthogonal multiple access (NOMA) as a promising technology, can achieve enhanced connectivity and spectral efficiency. However, the asymmetric channels in uplink NOMA systems can bring distinct uncertainty of the bit error rate (BER) and throughput performances to the users. To address this problem, an asymmetric adaptive modulation (AAM) fram...
A critical bottleneck of massive multiple-input multiple-output (MIMO) system is the huge training overhead caused by downlink transmission, like channel estimation, downlink beamforming and covariance observation. In this paper, we propose to use the channel state information (CSI) of a small number of antennas to extrapolate the CSI of the other...
Millimeter wave (mmWave) multi-user massive multi-input multi-output (MIMO) is a promising technique for the next generation communication systems. However, the hardware cost and power consumption grow significantly as the number of radio frequency (RF) components increases, which hampers the deployment of practical massive MIMO systems. To address...
In this paper, we consider a massive multiple-input-multiple-output (MIMO) downlink system that improves the hardware efficiency by dynamically selecting the antenna subarray and utilizing 1-bit phase shifters for hybrid beamforming. To maximize the spectral efficiency, we propose a novel deep unsupervised learning-based approach that avoids the co...