arXiv subjects

Jiayi Zhang

Publications and source records attributed to Jiayi Zhang.

At least 181 records · Page 10Linked to original sources

arXiv2022

Applications of Reconfigurable Intelligent Surface in Smart High Speed Train Communications

Reconfigurable intelligent surface (RIS) is one of the most promising technologies for 5G-Adv and 6G. It has the characteristics of low cost, low complexity, and easy deployment, which provides a new opportunity to develop intelligent high-speed railway communications. The typical applications of RIS-assisted smart high-speed railway communications are introduced in detail, including suppressing the Doppler shift effect, solving frequent handoff problems, overcoming high penetration loss problems, and supporting high-precision train positioning. The key technologies of RIS-assisted smart high-speed railway communications are discussed in-depth, including channel measurement and modeling, channel estimation and feedback, beamforming, network architecture, and network deployment. It is believed that the combination of the new intelligent high-speed railway infrastructure and the new electromagnetic infrastructure built by RIS will bring broad industrial prospects to the intelligent high-speed railway in the future.

eess.SP↗

arXiv2022

Asynchronous Cell-Free Massive MIMO With Rate-Splitting

In practical cell-free (CF) massive multiple-input multiple-output (MIMO) networks with distributed and low-cost access points, the asynchronous arrival of signals at the user equipments increases multi-user interference that degrades the system performance. Meanwhile, rate-splitting (RS), exploiting the transmission of both common and private messages, has demonstrated to offer considerable spectral efficiency (SE) improvements and its robustness against channel state information (CSI) imperfection. The signal performance of a CF massive MIMO system is first analyzed for asynchronous reception capturing the joint effects of propagation delays and oscillator phases of transceivers. Taking into account the imperfect CSI caused by asynchronous phases and pilot contamination, we derive novel and closed-form downlink SE expressions for characterizing the performance of both the RS-assisted and conventional non-RS-based systems adopting coherent and non-coherent data transmission schemes, respectively. Moreover, we formulate the design of robust precoding for the common messages as an optimization problem that maximizes the minimum individual SE of the common message. To address the non-convexity of the design problem, a bisection method is proposed to solve the problem optimally. Simulation results show that asynchronous reception indeed destroys both the orthogonality of the pilots and the coherent data transmission resulting in poor system performance. Besides, thanks to the uniform coverage properties of CF massive MIMO systems, RS with a simple low-complexity precoding for the common message obtained by the equal ratio sum of the private precoding is able to achieve substantial downlink sum SE gains, while the application of robust precoding to the common message is shown to be useful in some extreme cases, e.g., serious oscillator mismatch and unknown delay phase.

cs.IT↗

arXiv2022

Improving Fairness for Cell-Free Massive MIMO Through Interference-Aware Massive Access

Cell-free massive multiple-input multiple-output (CF mMIMO) provides good interference management by coordinating many more access points (APs) than user equipments (UEs). It becomes challenging to determine which APs should serve which UEs with which pilots when the number of UEs approximates the number of APs and far exceeds the number of pilots. Compared to the previous work, a better compromise between spectral efficiency (SE) and implementation simplicity is needed in such massive access scenarios. This paper proposes an interference-aware massive access (IAMA) scheme realizing joint AP-UE association and pilot assignment for CF mMIMO by exploiting the large-scale interference features. We propose an interference-aware reward as a novel performance metric and use it to develop two iterative algorithms to optimize the association and pilot assignment. The numerical results show a prominent advantage of our IAMA scheme over the benchmark schemes in terms of the user fairness and the average SE.

cs.IT↗

arXiv2022

Federated Learning-Based Cell-Free Massive MIMO System for Privacy-Preserving

Cell-free massive MIMO (CF mMIMO) is a promising next generation wireless architecture to realize federated learning (FL). However, sensitive information of user equipments (UEs) may be exposed to the involved access points or the central processing unit in practice. To guarantee data privacy, effective privacy-preserving mechanisms are defined in this paper. In particular, we demonstrate and characterize the possibility in exploiting the inherent quantization error, caused by low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs), for privacy-preserving in a FL CF mMIMO system. Furthermore, to reduce the required uplink training time in such a system, a stochastic non-convex design problem that jointly optimizing the transmit power and the data rate is formulated. To address the problem at hand, we propose a novel power control method by utilizing the successive convex approximation approach to obtain a suboptimal solution. Besides, an asynchronous protocol is established for mitigating the straggler effect to facilitate FL. Numerical results show that compared with the conventional full power transmission, adopting the proposed power control method can effectively reduce the uplink training time under various practical system settings. Also, our results unveil that our proposed asynchronous approach can reduce the waiting time at the central processing unit for receiving all user information, as there are no stragglers that requires a long time to report their local updates.

cs.IT↗

arXiv2022

Hard Exudate Segmentation Supplemented by Super-Resolution with Multi-scale Attention Fusion Module

Hard exudates (HE) is the most specific biomarker for retina edema. Precise HE segmentation is vital for disease diagnosis and treatment, but automatic segmentation is challenged by its large variation of characteristics including size, shape and position, which makes it difficult to detect tiny lesions and lesion boundaries. Considering the complementary features between segmentation and super-resolution tasks, this paper proposes a novel hard exudates segmentation method named SS-MAF with an auxiliary super-resolution task, which brings in helpful detailed features for tiny lesion and boundaries detection. Specifically, we propose a fusion module named Multi-scale Attention Fusion (MAF) module for our dual-stream framework to effectively integrate features of the two tasks. MAF first adopts split spatial convolutional (SSC) layer for multi-scale features extraction and then utilize attention mechanism for features fusion of the two tasks. Considering pixel dependency, we introduce region mutual information (RMI) loss to optimize MAF module for tiny lesions and boundary detection. We evaluate our method on two public lesion datasets, IDRiD and E-Ophtha. Our method shows competitive performance with low-resolution inputs, both quantitatively and qualitatively. On E-Ophtha dataset, the method can achieve $\geq3\%$ higher dice and recall compared with the state-of-the-art methods.

eess.IV↗

arXiv2022

Performance Analysis of Cell-Free Massive MIMO Systems with Asynchronous Reception

Cell-free (CF) massive multiple-input multiple-output (MIMO) is considered as a promising technology for achieving the ultimate performance limit. However, due to its distributed architecture and low-cost access points (APs), the signals received at user equipments (UEs) are most likely asynchronous. In this paper, we investigate the performance of CF massive MIMO systems with asynchronous reception, including both effects of delay and oscillator phases. Taking into account the imperfect channel state information caused by phase asynchronization and pilot contamination, we obtain novel and closed-form downlink spectral efficiency (SE) expressions with coherent and non-coherent data transmission schemes, respectively. Simulation results show that asynchronous reception destroys the orthogonality of pilots and coherent transmission of data, and thus results in poor system performance. In addition, getting a highly accurate delay phase is substantial for CF massive MIMO systems to achieve coherent transmission gain. Moreover, the oscillator phase of UEs has a larger effect on SE than that of the APs, because the latter can be significantly reduced by increasing the number of antennas.

cs.IT↗

arXiv2022

Decentralized Coordinated Precoding Design in Cell-Free Massive MIMO Systems for URLLC

Cell-free massive multiple-input multiple-output (MIMO) is a promising network to offer huge improvement of the achievable rate compared with conventional cellular massive MIMO systems. However, the commonly adopted Shannon-type achievable rate is only valid in the long block length regime that is not applicable to the emerging short-packet communication. To realize ultra-reliable and low-latency communication (URLLC) in cell-free massive MIMO systems, we optimize the precoding vector at the access points (APs) to maximize the minimum user rate in both the centralized and decentralized fashion. The design takes into account the impact of URLLC and we propose path-following algorithms (PFA) to address the considered problem which generates a sequence of advanced feasible points and converges to at least a locally optimal solution of the design problem. Moreover, we investigate the requirement of the precoding schemes, the length of the transmission duration, the number of antennas equipped at each AP, and the size of each AP cluster on the URLLC rate. Numerical results show that the decentralized PFA precoding can achieve 80\% of the 95\%-likely URLLC rate of the centralized precoding and 89\% of the average URLLC rate with only 12\% computational complexity of the centralized precoding.

cs.IT↗

arXiv2022

Uplink Performance of RIS-aided Cell-Free Massive MIMO System Over Spatially Correlated Channels

We consider a practical spatially correlated reconfigurable intelligent surface (RIS)-aided cell-free (CF) massive multiple-input-multiple-output (mMIMO) system with multi-antenna access points (APs) over spatially correlated Rician fading channels. The minimum mean square error (MMSE) channel estimator is adopted to estimate the aggregated RIS channels. Then, we investigate the uplink spectral efficiency (SE) with the maximum ratio (MR) and the local minimum mean squared error (L-MMSE) combining at the APs and obtain the closed-form expression for characterizing the performance of the former. The accuracy of our derived analytical results has been verified by extensive Monte-Carlo simulations. Our results show that increasing the number of RIS elements is always beneficial, but with diminishing returns when the number of RIS elements is sufficiently large. Furthermore, the effect of the number of AP antennas on system performance is more pronounced under a small number of RIS elements, while the spatial correlation of RIS elements imposes a more severe negative impact on the system performance than that of the AP antennas.

cs.IT↗

arXiv2022

Cell-Free Massive MIMO with Multi-Antenna Users over Weichselberger Rician Channels

We consider a cell-free massive multiple-input multiple-output (MIMO) system with multi-antenna access points and user equipments (UEs) over Weichselberger Rician fading channels with random phase-shifts. More specifically, we investigate the uplink spectral efficiency (SE) for two pragmatic processing schemes: 1) the fully centralized processing scheme with global minimum mean square error (MMSE) or maximum ratio (MR) combining; 2) the large-scale fading decoding (LSFD) scheme with local MMSE or MR combining. To improve the system SE performance, we propose a practical uplink precoding scheme based on only the eigenbasis of the UE-side correlation matrices. Moreover, we derive novel closed-form SE expressions for characterizing the LSFD scheme with the MR combining. Numerical results validate the accuracy of our derived expressions and show that the proposed precoding scheme can significantly improve the SE performance compared with the scenario without any precoding scheme.

cs.IT↗

arXiv2022

Sparse Large-Scale Fading Decoding in Cell-Free Massive MIMO Systems

Cell-free massive multiple-input multiple-output (CF mMIMO) systems are characterized by having many more access points (APs) than user equipments (UEs). A key challenge is to determine which APs should serve which UEs. Previous work has tackled this combinatorial problem heuristically. This paper proposes a sparse large-scale fading decoding (LSFD) design for CF mMIMO to jointly optimize the association and LSFD. We formulate a group sparsity problem and then solve it using a proximal algorithm with block-coordinate descent. Numerical results show that sparse LSFD achieves almost the same spectral efficiency as optimal LSFD, thus achieving a higher energy efficiency since the processing and signaling are reduced.

cs.IT↗

arXiv2022

C3KG: A Chinese Commonsense Conversation Knowledge Graph

Existing commonsense knowledge bases often organize tuples in an isolated manner, which is deficient for commonsense conversational models to plan the next steps. To fill the gap, we curate a large-scale multi-turn human-written conversation corpus, and create the first Chinese commonsense conversation knowledge graph which incorporates both social commonsense knowledge and dialog flow information. To show the potential of our graph, we develop a graph-conversation matching approach, and benchmark two graph-grounded conversational tasks.

cs.CL↗

arXiv2022

Performance and Optimization of Reconfigurable Intelligent Surface Aided THz Communications

TeraHertz (THz) communications can satisfy the high data rate demand with massive bandwidth. However, severe path attenuation and hardware imperfection greatly alleviate its performance. Therefore, we utilize the reconfigurable intelligent surface (RIS) technology and investigate the RIS-aided THz communications. We first prove that the small-scale amplitude fading of THz signals can be accurately modeled by the fluctuating two-ray distribution based on two THz signal measurement experiments conducted in a variety of different scenarios. To optimize the phase-shifts at the RIS elements, we propose a novel swarm intelligence-based method that does not require full channel estimation. We then derive exact statistical characterizations of end-to-end signal-to-noise plus distortion ratio (SNDR) and signal-to-noise ratio (SNR). Moreover, we present asymptotic analysis to obtain more insights when the SNDR or the number of RIS's elements is high. Finally, we derive analytical expressions for the outage probability and ergodic capacity. The tight upper bounds of ergodic capacity for both ideal and nonideal radio frequency chains are obtained. It is interesting to find that increasing the number of RIS's elements can significantly improve the THz communications system performance. For example, the ergodic capacity can increase up to 25% when the number of elements increases from 40 to 80, which incurs only insignificant costs to the system.

cs.IT↗

arXiv2022

Local Partial Zero-Forcing Combining for Cell-Free Massive MIMO Systems

Cell-free massive multiple-input multiple-output (MIMO) provides more uniform spectral efficiency (SE) for users (UEs) than cellular technology. The main challenge to achieve the benefits of cell-free massive MIMO is to realize signal processing in a scalable way. In this paper, we consider scalable fullpilot zero-forcing (FZF), partial FZF (PFZF), protective weak PFZF (PWPFZF), and local regularized ZF (LRZF) combining by exploiting channel statistics. We derive closed-form expressions of the uplink SE for FZF, PFZF, and PWPFZF combining with large-scale fading decoding over independent Rayleigh fading channels, taking channel estimation errors and pilot contamination into account. Moreover, we investigate the impact of the number of pilot sequences, antennas per AP, and APs on the performance. Numerical results show that LRZF provides the highest SE. However, PWPFZF is preferable when the number of pilot sequences is large and the number of antennas per AP is small. The reason is that PWPFZF has lower computational complexity and the SE expression can be computed in closed-form. Furthermore, we investigate the performance of PWPFZF combining with fractional power control and the numerical results show that it improves the performance of weak UEs and realizes uniformly good service for all UEs in a scalable fashion.

cs.IT↗

arXiv2022

Uplink Performance of Cell-Free Massive MIMO with Multi-Antenna Users Over Jointly-Correlated Rayleigh Fading Channels

In this paper, we investigate a cell-free massive MIMO system with both access points (APs) and user equipments (UEs) equipped with multiple antennas over jointly-correlated Rayleigh fading channels. We study four uplink implementations, from fully centralized processing to fully distributed processing, and derive their achievable spectral efficiency (SE) expressions with minimum mean-squared error successive interference cancellation (MMSE-SIC) detectors and arbitrary combining schemes. Furthermore, the global and local MMSE combining schemes are derived based on full and local channel state information (CSI) obtained under pilot contamination, which can maximize the achievable SE for the fully centralized and distributed implementation, respectively. We study a two-layer decoding implementation with an arbitrary combining scheme in the first layer and optimal large-scale fading decoding (LSFD) in the second layer. Besides, we compute novel closed-form SE expressions for the two-layer decoding implementation with maximum ratio (MR) combining. In the numerical results, we compare the SE performance for different implementation levels, combining schemes, and channel models. It is important to note that increasing the number of antennas per UE may degrade the SE performance.

cs.IT↗

arXiv2022

Reconfigurable Intelligent Surface-Aided Joint Radar and Covert Communications: Fundamentals, Optimization, and Challenges

Future wireless communication systems will evolve toward multi-functional integrated systems to improve spectrum utilization and reduce equipment sizes. A joint radar and communication (JRC) system, which can support simultaneous information transmission and target detection, has been regarded as a promising solution for emerging applications such as autonomous vehicles. In JRC, data security and privacy protection are critical issues. Thus, we first apply covert communication into JRC and propose a joint radar and covert communication (JRCC) system to achieve high spectrum utilization and secure data transmission simultaneously. In the JRCC system, an existence of sensitive data transmission is hidden from a maliciously observant warden. However, the performance of JRCC is restricted by severe signal propagation environment and hardware devices. Fortunately, reconfigurable intelligent surfaces (RISs) can change the signal propagation smartly to improve the networks performance with low cost. We first overview fundamental concepts of JRCC and RIS and then propose the RIS-aided JRCC system design. Furthermore, both covert communication and radar performance metrics are investigated and a game theory-based covert rate optimization scheme is designed to achieve secure communication. Finally, we present several promising applications and future directions of RIS-aided JRCC systems.

eess.SY↗

arXiv2022

A Survey for Solving Mixed Integer Programming via Machine Learning

This paper surveys the trend of leveraging machine learning to solve mixed integer programming (MIP) problems. Theoretically, MIP is an NP-hard problem, and most of the combinatorial optimization (CO) problems can be formulated as the MIP. Like other CO problems, the human-designed heuristic algorithms for MIP rely on good initial solutions and cost a lot of computational resources. Therefore, we consider applying machine learning methods to solve MIP, since ML-enhanced approaches can provide the solution based on the typical patterns from the historical data. In this paper, we first introduce the formulation and preliminaries of MIP and several traditional algorithms to solve MIP. Then, we advocate further promoting the different integration of machine learning and MIP and introducing related learning-based methods, which can be classified into exact algorithms and heuristic algorithms. Finally, we propose the outlook for learning-based MIP solvers, direction towards more combinatorial optimization problems beyond MIP, and also the mutual embrace of traditional solvers and machine learning components.

cs.AI↗

arXiv2022

Reconfigurable Intelligent Surface (RIS)-aided Vehicular Networks: Their Protocols, Resource Allocation, and Performance

Reconfigurable intelligent surfaces (RISs) assist in paving the way for the evolution of conventional vehicular networks to autonomous driving. Having said that, the 3rd Generation Partnership Project (3GPP) faces numerous open challenges concerning the RIS-aided vehicle-to-everything (V2X) solutions of the near future. To tackle these challenges and to stimulate future research, this article focuses on the prospective transmission design of RIS-aided V2X communications. In particular, two V2X sidelink modes are enhanced by exploiting RISs and their variants, followed by a customized transmission frame structure that partitions the transmission efforts into different phases. Next, effective channel tracking and resource allocation techniques are developed for attaining a high beamforming gain at low overhead and complexity. Finally, promising research topics are highlighted and future 3GPP standardization items are proposed for RISaided V2X systems.

eess.SP↗

arXiv2022

Cell-Free Massive MIMO-OFDM for High-Speed Train Communications

Cell-free (CF) massive multiple-input multiple-output (MIMO) systems show great potentials in low-mobility scenarios, due to cell boundary disappearance and strong macro diversity. However, the great Doppler frequency offset (DFO) leads to serious inter-carrier interference in orthogonal frequency division multiplexing (OFDM) technology, which makes it difficult to provide high-quality transmissions for both high-speed train (HST) operation control systems and passengers. In this paper, we focus on the performance of CF massive MIMO-OFDM systems with both fully centralized and local minimum mean square error (MMSE) combining in HST communications. Considering the local maximum ratio (MR) combining, the large-scale fading decoding (LSFD) cooperation and the practical effect of DFO on system performance, exact closed-form expressions for uplink spectral efficiency (SE) expressions are derived. We observe that cooperative MMSE combining achieves better SE performance than uncooperative MR combining. In addition, HST communications with small cell and cellular massive MIMO-OFDM systems are compared in terms of SE. Numerical results reveal that the CF massive MIMO-OFDM system achieves a larger and more uniform SE than the other systems. Finally, the train antenna centric (TA-centric) CF massive MIMO-OFDM system is designed for practical implementation in HST communications, and three power control schemes are adopted to optimize the propagation of TAs for reducing the impact of the DFO.

cs.IT↗