arXiv subjects

Shanzhi Chen

Publications and source records attributed to Shanzhi Chen.

8 recordsLinked to original sources

arXiv2025

DCT-MARL: A Dynamic Communication Topology-Based MARL Algorithm for Connected Vehicle Platoon Control

With the rapid advancement of vehicular communication facilities and autonomous driving technologies, connected vehicle platooning has emerged as a promising approach to improve traffic efficiency and driving safety. Reliable Vehicle-to-Vehicle (V2V) communication is critical to achieving efficient cooperative control. However, in the real-world traffic environment, V2V communication may suffer from time-varying delay and packet loss, leading to degraded control performance and even safety risks. To mitigate the adverse effects of non-ideal communication, this paper proposes a Dynamic Communication Topology based Multi-Agent Reinforcement Learning (DCT-MARL) algorithm for robust cooperative platoon control. Specifically, the state space is augmented with historical control action and delay to enhance robustness against communication delay. To mitigate the impact of packet loss, a multi-key gated communication mechanism is introduced, which dynamically adjusts the communication topology based on the correlation between vehicles and their current communication status. Simulation results demonstrate that the proposed DCT-MARL significantly outperforms state-of-the-art methods in terms of string stability and driving comfort, validating its superior robustness and effectiveness.

eess.SY↗

arXiv2023

6G Network AI Architecture for Everyone-Centric Customized Services

Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources and improving spectrum and energy efficiency. How to effectively address diverse user requirements and guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem by utilizing heterogenous network resources and pervasive intelligence to support everyone-centric customized services anywhere and anytime. In this article, we first coin the concept of Service Requirement Zone (SRZ) on the user side to characterize and visualize the integrated service requirements and preferences of specific tasks of individual users. On the system side, we further introduce the concept of User Satisfaction Ratio (USR) to evaluate the system's overall service ability of satisfying a variety of tasks with different SRZs. Then, we propose a network Artificial Intelligence (AI) architecture with integrated network resources and pervasive AI capabilities for supporting customized services with guaranteed QoEs. Finally, extensive simulations show that the proposed network AI architecture can consistently offer a higher USR performance than the cloud AI and edge AI architectures with respect to different task scheduling algorithms, random service requirements, and dynamic network conditions.

cs.NI↗

arXiv2022

Joint Communications and Sensing Employing Optimized MIMO-OFDM Signals

Joint communication and sensing (JCAS) has the potential to improve the overall energy, cost and frequency efficiency of IoT systems. As a first effort, we propose to optimize the MIMO-OFDM data symbols carried by sub-carriers for better time- and spatial-domain signal orthogonality. This not only boosts the availability of usable signals for JCAS, but also significantly facilitates Internet-of-Things (IoT) devices to perform high-quality sensing. We establish an optimization problem that modifies data symbols on sub-carriers to enhance the above-mentioned signal orthogonality. We also develop an efficient algorithm to solve the problem based on the majorization-minimization framework. Moreover, we discover unique signal structures and features from the newly modeled problem, which substantially reduce the complexity of majorizing the objective function. We also develop new projectors to enforce the feasibility of the obtained solution. Simulations show that, compared with the original communication waveform to achieve the same sensing performance, the optimized waveform can reduce the signal-to-noise ratio (SNR) requirement by 3~4.5 dB, while the SNR loss for the uncoded bit error rate is only 1~1.5 dB.

eess.SP↗

arXiv2021

Enabling Joint Communication and Radar Sensing in Mobile Networks -- A Survey

Mobile network is evolving from a communication-only network towards one with joint communication and radar/radio sensing (JCAS) capabilities, that we call perceptive mobile network (PMN). In PMNs, JCAS integrates sensing into communications, sharing a majority of system modules and the same transmitted signals. The PMN is expected to provide a ubiquitous radio sensing platform and enable a vast number of novel smart applications, whilst providing non-compromised communications. In this paper, we present a broad picture of the motivation, methodologies, challenges, and research opportunities of realizing PMN, by providing a comprehensive survey for systems and technologies developed mainly in the last ten years. Beginning by reviewing the work on coexisting communication and radar systems, we highlight their limits on addressing the interference problem, and then introduce the JCAS technology. We then set up JCAS in the mobile network context and envisage its potential applications. We continue to provide a brief review of three types of JCAS systems, with particular attention to their differences in design philosophy. We then introduce a framework of PMN, including the system platform and infrastructure, three types of sensing operations, and signals usable for sensing. Subsequently, we discuss required system modifications to enable sensing on current communication-only infrastructure. Within the context of PMN, we review stimulating research problems and potential solutions, organized under nine topics: performance bounds, waveform optimization, antenna array design, clutter suppression, sensing parameter estimation, resolution of sensing ambiguity, pattern analysis, networked sensing under cellular topology, and sensing-assisted communications. We conclude the paper by listing key open research problems for the aforementioned topics and sharing some lessons that we have learned.

eess.SP↗

arXiv2020

Vision, Requirements, and Technology Trend of 6G: How to Tackle the Challenges of System Coverage, Capacity,User Data-Rate and Movement Speed

Since 5G new radio comes with non-standalone (NSA) and standalone (SA) versions in 3GPP, research on 6G has been on schedule by academics and industries. Though 6G is supposed to have much higher capabilities than 5G, yet there is no clear description about what 6G is. In this article, a comprehensive discussion of 6G is given based on the review of 5G developments, covering visions and requirements, technology trends and challenges, aiming at tackling the challenge of coverage, capacity, the user data rate and movement speed of mobile communication system. The vision of 6G is to fully support the development of a Ubiquitous Intelligent Mobile Society with intelligent life and industries. Finally, the roadmap of the 6G standard is suggested for the future.

cs.IT↗

arXiv2020

Beam-space Multiplexing: Practice, Theory, and Trends-From 4G TD-LTE, 5G, to 6G and Beyond

In this article, the new term, namely beam-space multiplexing, is proposed for the former multi-layer beamforming for 4G TD-LTE in 3GPP releases. We provide a systematic overview of beam-space multiplexing from engineering and theoretical perspectives. Firstly, we clarify the fundamental theory of beam-space multiplexing. Specifically, we provide a comprehensive comparison with the antenna-space multiplexing in terms of theoretical analysis, channel state information acquisition, and engineering implementation constraints. Then, we summarize the key technologies and 3GPP standardization of beam-space multiplexing in 4G TD-LTE and 5G new radio (NR) in terms of multi-layer beamforming and massive beamforming, respectively. We also provide system-level performance evaluation of beam-space multiplexing schemes and field results from current commercial TD-LTE networks and field trial of 5G. The practical deployments of 4G TD-LTE and 5G cellular networks demonstrate the superiority of beam-space multiplexing within the limitations of implementation complexity and practical deployment scenarios. Finally, the future trends of beam-space multiplexing in 6G and beyond are discussed, including massive beamforming for extremely large-scale MIMO (XL-MIMO), low earth orbit (LEO) satellites communication, data-driven intelligent massive beamforming, and multi-target spatial signal processing, i.e., joint communication and sensing, positioning, etc.

eess.SP↗

arXiv2019

When Full Duplex Wireless Meets Non-Orthogonal Multiple Access: Opportunities and Challenges

Non-orthogonal multiple access (NOMA) is a promising radio access technology for the 5G wireless systems. The core of NOMA is to support multiple users in the same resource block via power or code domain multiplexing, which provides great enhancement in spectrum efficiency and connectivity. Meanwhile, with the recent advance in self-interference (SI) cancelation techniques, full duplex (FD) wireless communication has become a feasible technology enabling radios to receive and transmit simultaneously. This article aims to investigate the combination of these two emerging technologies. At first, several typical scenarios and protocols are presented to illustrate the application of FD technique in NOMA systems. Then, a novel NOMA system with FD base stations (BSs) based on centralized radio access networks (C-RAN) is proposed. Furthermore, power allocation policies are discussed for the proposed scheme, and simulation results are provided to demonstrate its superiority. Finally, challenges and research opportunities of FD NOMA systems are also identified to stimulate the future research.

cs.IT↗

arXiv2018

Hybrid Precoding-Based Millimeter-Wave Massive MIMO-NOMA with Simultaneous Wireless Information and Power Transfer

Non-orthogonal multiple access (NOMA) has been recently considered in millimeter-wave (mmWave) massive MIMO systems to further enhance the spectrum efficiency. In addition, simultaneous wireless information and power transfer (SWIPT) is a promising solution to maximize the energy efficiency. In this paper, for the first time, we investigate the integration of SWIPT in mmWave massive MIMO-NOMA systems. As mmWave massive MIMO will likely use hybrid precoding (HP) to significantly reduce the number of required radio-frequency (RF) chains without an obvious performance loss, where the fully digital precoder is decomposed into a high-dimensional analog precoder and a low-dimensional digital precoder, we propose to apply SWIPT in HP-based MIMO-NOMA systems, where each user can extract both information and energy from the received RF signals by using a power splitting receiver. Specifically, the cluster-head selection (CHS) algorithm is proposed to select one user for each beam at first, and then the analog precoding is designed according to the selected cluster heads for all beams. After that, user grouping is performed based on the correlation of users' equivalent channels. Then, the digital precoding is designed by selecting users with the strongest equivalent channel gain in each beam. Finally, the achievable sum rate is maximized by jointly optimizing power allocation for mmWave massive MIMO-NOMA and power splitting factors for SWIPT, and an iterative optimization algorithm is developed to solve the non-convex problem. Simulation results show that the proposed HP-based MIMO-NOMA with SWIPT can achieve higher spectrum and energy efficiency compared with HP-based MIMO-OMA with SWIPT.

cs.IT↗