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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Wang, Jianyu Yang, Liu Bai, Chaoyuan Liu, Heng Chengdu611756 China Southwest Jiaotong University Key Lab of Information Coding & Transmission Institude of Mobile Communication Chengdu611756 China Southwest Jiaotong University National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu611756 China

ISBN: (纸本)9798331517786

Device activity detection and channel estimation are central problems in massive Machine Type Communication (mMTC) scenarios. Given the sparse distribution of active devices, compressive sensing (CS) emerges as a viable solution at the gNB to mitigate interference stemming from non-orthogonal preamble sets. This paper proposes an algorithm for optimizing measurement matrix, thereby elevating the performance of signal recovery in CS. Within the proposed algorithm, a optimization model that integrates eigenvalue averaging and equiangular tight frame (ETF) theory is formulated, and an iterative algorithm is devised to approximate the optimal solution utilizing singular value decomposition (SVD). Further, a weight-based strategie is discussed with respect to the feasibility of the proposed algorithm, accompanied by the introduction of iteration termination condition. Experimental results corroborate the algorithm's swift convergence, underpinning the efficient production of high-performance matrices that refine the accuracy of joint device activity detection and channel estimation. © 2024 IEEE.

关键词： Eigenvalues and eigenfunctions

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Joint Activity Detection and Channel Estimation in MIMO Grant-Free Random Access Networks

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IEEE Transactions on Wireless Communications 2025年

作者： Yang, Boran Zhang, Xiaoxu Hao, Li Karagiannidis, George K. Southwest Jiaotong University Provincial Key Lab of Information Coding and Transmission Chengdu611756 China Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki Greece

Massive machine communication is predicted to provide widespread and unparalleled connectivity for cellular Internet of Things (IoT) applications via multiple-input multiple-output (MIMO) and grant-free random access (GF-RA) techniques. Compressed sensing (CS) has been widely advocated to support massive connectivity due to the bursty nature of traffic transmission. In this paper, the joint activity detection and channel estimation in MIMO-enabled GF-RA system is formulated as a block single measurement vector (SMV) problem and efficiently addressed by using Bayesian-based CS algorithms. First, the pattern coupled sparse Bayesian learning (PCSBL) and block sparse Bayesian learning (BSBL) algorithms are introduced to solve this problem, where the potential block sparsity properties induced by multi-antenna reception are exploited by assigning the structured hyperpriors. Then, by embedding the Generalized Approximate Message Passing (GAMP) technique into the PCSBL and BSBL frameworks to enable effective approximation of posterior distributions, we propose two computationally efficient Bayesian learning algorithms, i.e., GAMP-PCSBL and GAMP-BSBL. Fortunately, the proposed Bayesian algorithms allow automatic learning of block sparse solutions without requiring noise level and user sparsity ratio as explicit conditions. Simulation results show that the proposed algorithms provide improved performance gains over the standard CS-based methods. © 2002-2012 IEEE.

关键词： Channel estimation

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Incentive Based Federated Learning Data Dissemination for Vehicular Edge Computing Networks

Incentive Based Federated Learning Data Dissemination for Ve...

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IEEE Conference on Vehicular Technology (VTC)

作者： Muhammad Saleh Bute Pingzhi Fan Quyuan Luo Key Lab. of Information Coding & Transmission School of Information Science and Technology Southwest Jiaotong University Chengdu China

The advancements in vehicular networks and applications brings about a huge demand for vehicles to process computation-intensive tasks such as machine learning (ML) algorithms. There is a need for an efficient solution to meet up these challenges. Federated learning (FL), which is distributed and does not require the transmission of dataset to the server, is more suitable to the resource constraint vehicular edge network. However, not all vehicles will participate in FL training without any reward. This paper proposes an incentive-based federated learning scheme for vehicular networks. Vehicles participating in federated learning are selected using an auction algorithm based on maximized social welfare. Simulations are conducted to evaluate the performance of the proposed scheme.

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Security of Integrated Sensing and Communication Systems with Hybrid Eavesdroppers 2

Security of Integrated Sensing and Communication Systems wit...

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2nd IEEE International Conference on Signal, information and Data Processing, ICSIDP 2024

作者： Liu, Meiding Zhou, Zhengchun Shi, Qiao Li, Guyue Liu, Zilong Fan, Pingzhi Lee, Inkyu Southwest Jiaotong University School of Information Science and Technology Chengdu China Southeast University School of Cyber Science and Engineering Nanjing China University of Essex School of Computer Science and Electronics Engineering Colchester United Kingdom Southwest Jiaotong University Key Lab of Information Coding and Transmission Chengdu China Korea University School of Electrical Engineering Seoul Korea Republic of

ISBN: (纸本)9798331515669

In this paper, we consider the joint beamforming design in secure integrated sensing and communication (ISAC) systems, where the active eavesdropper intercepts the transmitted confidential information with an external passive eavesdropper. To improve the sensing performance while preventing the potential eavesdropping, the base station transmits a signal consisting of information symbols and sensing waveform, in which the sensing waveform is also used as artificial noise to interfere with eavesdroppers. Under this setup, we formulate the communication and sensing beamforming design problem, which aims to enhance the transmit beampattern performance, while ensuring the quality of service (QoS) of communication transmission and the secure communication constraint. Furthermore, we propose the semi-definite relaxation (SDR) algorithm to solve the non-convex problem. Numerical results demonstrate the effectiveness of the proposed scheme in both sensing and secure communication. © 2024 IEEE.

关键词： Beamforming

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Federated Deep Reinforcement Learning-Based Intelligent Channel Access in Dense Wi-Fi Deployments

arXiv

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arXiv 2024年

作者： Du, Xinyang Fang, Xuming He, Rong Yan, Li Lu, Liuming Luo, Chaoming Key Lab of Information Coding & Transmission Southwest Jiaotong University Chengdu610031 China Guangdong OPPO Mobile Telecommunications Corp. Ltd Guangdong523859 China

The IEEE 802.11 MAC layer utilizes the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) mechanism for channel contention, but dense Wi-Fi deployments often cause high collision rates. To address this, this paper proposes an intelligent channel contention access mechanism that combines Federated Learning (FL) and Deep Deterministic Policy Gradient (DDPG) algorithms. We introduce a training pruning strategy and a weight aggregation algorithm to enhance model efficiency and reduce MAC delay. Using the NS3-AI framework, simulations show our method reduces average MAC delay by 25.24% in static scenarios and outperforms A-FRL and DRL by 25.72% and 45.9% in dynamic environments, respectively. Copyright © 2024, The Authors. All rights reserved.

关键词： Federated learning

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Delay Minimization in NOMA-Based Cooperative Mobile Edge Computing(MEC) Offloading

Delay Minimization in NOMA-Based Cooperative Mobile Edge Com...

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Radio Frequency and Antenna Technologies (iWRF&AT), IEEE International Workshop on

作者： Luyao Zhang Li Hao Information Coding & Transmission Key Lab of Sichuan Province CSNMT Int. Coop. Res. Centre (MoST) Southwest Jiaotong University Chengdu China

ISBN: (数字)9798350384765

ISBN: (纸本)9798350384772

This paper focuses on minimizing the offloading delay in the non-orthogonal multiple access (NOMA)-based cooperative three-node MEC system consisting of a user, a helper, and an access point(AP) attached to the MEC server. Unlike the existing research assuming the user is idle in the second slot, we consider the user offloads its data in both time slots. We formulate the delay minimization optimization problem based on joint communication and resource allocation. Then, we transform the nonconvex problem into an equivalent quasi-convex one to apply a bisection searching (BSS) based algorithm to obtain the optimal solution. Simulation results verify the effectiveness of the proposed scheme.

关键词： NOMA Computational modeling Simulation Transforms Minimization Search problems Delays

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Optimal Design of Energy-Harvesting Drone Communications in Cell-Free Massive MIMO with Finite-Resolution ADCs

Optimal Design of Energy-Harvesting Drone Communications in ...

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IEEE International Conference on Communications in China (ICCC)

作者： Ning Li Pingzhi Fan Information Coding & Transmission Key Lab of Sichuan Province CSNMT Int. Coop. Res. Centre (MoST) Southwest Jiaotong University Chengdu China

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

This paper investigates drone communications in user-centric cell-free massive multiple-input multiple-output (MIMO) networks under spatially correlated Rician fading channels. Finite-resolution analog-to-digital converters (ADCs) are configured at both the drone and the multiple-antenna access points (APs) to reduce hardware costs and power consumption. The drone utilizes the harvested energy (HE) from downlink wireless power transfer (WPT) for uplink pilot and information transmission. The linear minimum mean square error (LMMSE) estimator is developed for channel acquisition, revealing the impact of quantization bits on estimation quality. Closed-form expressions for downlink HE and uplink spectral efficiency (SE) can be obtained based on channel estimation. The SE is maximized by setting the fraction of downlink WPT, which shows that the SE-optimal operating point depends on the number of APs, number of antennas, flight altitude, and quantization bits. Finally, the correctness of the analysis and observations is validated through simulation results.

关键词： Quantization (signal) Power demand Costs Channel estimation Rician channels information processing Downlink

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A Survey on Low Complexity Detectors for OTFS Systems

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ZTE Communications 2021年第4期19卷 3-15页

作者： ZHANG Zhengquan LIU Heng WANG Qianli FAN Pingzhi Key Lab of Information Coding and Transmission Southwest Jiaotong UniversityChengdu 611756China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071China

The newly emerging orthogonal time frequency space(OTFS)modulation can ob⁃tain delay-Doppler diversity gain to significantly improve the system performance in high mobility wireless communication scenarios such as vehicle-to-everything(V2X),high-speed railway and unmanned aerial vehicles(UAV),by employing inverse symplectic finite Fouri⁃er transform(ISFFT)and symplectic finite Fourier transform(SFFT).However,OTFS modu⁃lation will dramatically increase system complexity,especially at the receiver ***,de⁃signing low complexity OTFS receiver is a key issue for OTFS modulation to be adopted by new-generation wireless communication *** this paper,we review low complexity OTFS detectors and provide some insights on future *** firstly present the OTFS system model and basic principles,followed by an overview of OTFS detector structures,classifications and comparative *** also survey the principles of OTFS detection ***,we discuss the design of hybrid OTFS and orthogonal frequency di⁃vision multiplexing(OFDM)detectors in single user and multi-user multi-waveform commu⁃nication ***,we address the main challenges in designing low complexity OT⁃FS detectors and identify some future research directions.

关键词： high mobility wireless communications OTFS ISFFT SFFT delay-Doppler di⁃versity iterative maximum ratio combining(MRC)detection message passing detection

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Linear Feedback coding for Gaussian Relay Channel with Various Feedback Links

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IEEE Transactions on Communications 2025年

作者： Deng, Han Xia, Dengfeng Zhang, Haonan Cai, Han Xu, Peng Dai, Bin Southwest Jiaotong University School of Information Science and Technology Chengdu610031 China Chongqing Key Laboratory of Mobile Communications Technology Chongqing400065 China Southwest Jiaotong University Provincial Key Lab of Information Coding and Transmission Chengdu611756 China Chongqing University of Posts and Telecommunications School of Communications and Information Engineering Chongqing400065 China

Linear feedback coding scheme, such as the elegant Schalkwijk-Kailath (SK) scheme, receives much attention in the literature since its decoding error probability decreases as a second-order exponential in the coding blocklength. In recent years, a linear feedback scheme has been proposed for the Gaussian relay channel (GRC) with destination-source feedback, which combines the SK scheme and the amplify-and-forward (AF) relay strategy. Since there exists three possible feedback links in the GRC, then one question beckons: is there any rate gain if there exist multiple feedback links in the GRC, and can any other relay strategy outperform the AF strategy? In this paper, we answer this question by investigating four feedback models of the GRC, namely, the GRC with destination-source and destination-relay feedback, the GRC with destination-relay and relay-source feedback, the GRC with destination-source and relay-source feedback, and the GRC with all feedback links, respectively. We propose SK-type schemes for these feedback models, and numerical examples show that when the coding blocklength is not long, the rates of our proposed schemes almost approach their asymptotic values, and these rates may be larger than those of existing schemes in the literature. The study of this paper shows that different number/location of feedback links may bring additional rate gain in finite blocklength regime. © 1972-2012 IEEE.

关键词： Gaussian distribution

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Low-complexity Resource Allocation for Uplink RSMA in Future 6G Wireless Networks

arXiv

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arXiv 2023年

作者： Hu, Jiewen Liu, Gang Ma, Zheng Xiao, Ming Fan, Pingzhi The Provincial Key Lab of Information Coding and Transmission Southwest Jiaotong University Chengdu611756 China The Department of Information Science and Engineering School of Electrical Engineering KTH Stockholm10044 Sweden

Uplink rate-splitting multiple access (RSMA) requires optimization of decoding order and power allocation, while decoding order is a discrete variable, and it is very complex to find the optimal decoding order if the number of users is large enough. This letter proposes a low-complexity user pairing-based resource allocation algorithm with the objective of minimizing the maximum latency. Closed-form expressions for power and bandwidth allocation for a given latency are first derived. Then a bisection method is used to determine the minimum latency and optimal resource allocation. Finally, the proposed algorithm is compared with unpaired RSMA using an exhaustive method to obtain the optimal decoding order, unpaired RSMA using a suboptimal decoding order, paired non-orthogonal multiple access (NOMA) and unpaired NOMA. The results show that our proposed algorithm outperforms NOMA and achieves similar performance to unpaired RSMA. In addition, the complexity of the proposed algorithm is significantly reduced. Copyright © 2023, The Authors. All rights reserved.

关键词： Wireless networks

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