arXiv subjects

Boya Di

Publications and source records attributed to Boya Di.

At least 37 records · Page 2Linked to original sources

arXiv2024

Dual-Polarized Reconfigurable Intelligent Surface-Based Antenna for Holographic MIMO Communications

Holographic multiple-input-multiple output (HMIMO), which is enabled by large-scale antenna arrays with quasi-continuous apertures, is expected to be an important technology in the forthcoming 6G wireless network. Reconfigurable intelligent surface (RIS)-based antennas provide an energy-efficient solution for implementing HMIMO. Most existing works in this area focus on single-polarized RIS-enabled HMIMO, where the RIS can only reflect signals in one polarization towards users and signals in the other polarization cannot be received by intended users, leading to degraded data rate. To improve multiplexing performance, in this paper, we consider a dual-polarized RIS-enabled single-user HMIMO network, aiming to optimize power allocations across polarizations and analyze corresponding maximum system capacity. However, due to interference between different polarizations, the dual-polarized system cannot be simply decomposed into two independent single-polarized ones. Therefore, existing methods developed for the single-polarized system cannot be directly applied, which makes the optimization and analysis of the dual-polarized system challenging. To cope with this issue, we derive an asymptotically tight upper bound on the ergodic capacity, based on which the power allocations across two polarizations are optimized. Potential gains achievable with such dual-polarized RIS are analyzed. Numerical results verify our analysis.

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arXiv2024

Large Models for Aerial Edges: An Edge-Cloud Model Evolution and Communication Paradigm

The future sixth-generation (6G) of wireless networks is expected to surpass its predecessors by offering ubiquitous coverage through integrated air-ground facility deployments in both communication and computing domains. In this network, aerial facilities, such as unmanned aerial vehicles (UAVs), conduct artificial intelligence (AI) computations based on multi-modal data to support diverse applications including surveillance and environment construction. However, these multi-domain inference and content generation tasks require large AI models, demanding powerful computing capabilities, thus posing significant challenges for UAVs. To tackle this problem, we propose an integrated edge-cloud model evolution framework, where UAVs serve as edge nodes for data collection and edge model computation. Through wireless channels, UAVs collaborate with ground cloud servers, providing cloud model computation and model updating for edge UAVs. With limited wireless communication bandwidth, the proposed framework faces the challenge of information exchange scheduling between the edge UAVs and the cloud server. To tackle this, we present joint task allocation, transmission resource allocation, transmission data quantization design, and edge model update design to enhance the inference accuracy of the integrated air-ground edge-cloud model evolution framework by mean average precision (mAP) maximization. A closed-form lower bound on the mAP of the proposed framework is derived, and the solution to the mAP maximization problem is optimized accordingly. Simulations, based on results from vision-based classification experiments, consistently demonstrate that the mAP of the proposed framework outperforms both a centralized cloud model framework and a distributed edge model framework across various communication bandwidths and data sizes.

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arXiv2024

Hybrid Near-Far Field Channel Estimation for Holographic MIMO Communications

Holographic MIMO communications, enabled by large-scale antenna arrays with quasi-continuous apertures, is a potential technology for spectrum efficiency improvement. However, the increased antenna aperture size extends the range of the Fresnel region, leading to a hybrid near-far field communication mode. The users and scatterers randomly lie in near-field and far-field zones, and thus, conventional far-field-only and near-field-only channel estimation methods may not work. To tackle this challenge, we demonstrate the existence of the power diffusion (PD) effect, which leads to a mismatch between the hybrid-field channel and existing channel estimation methods. Specifically, in far-field and near-field transform domains, the power gain of one channel path may diffuse to other positions, thus generating fake paths. This renders the conventional techniques unable to detect those real paths. We propose a PD-aware orthogonal matching pursuit algorithm to eliminate the influence of the PD effect by identifying the PD range within which paths diffuse to other positions. PD-OMP fits a general case without prior knowledge of near-field and far-field path numbers and the user's location. The computational complexity of PD-OMP and the Cramer-Rao Lower Bound for the sparse-signal-recovery-based channel estimation are also derived. Simulation results show that PD-OMP outperforms state-of-the-art hybrid-field channel estimation methods.

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arXiv2024

Intelligent Surfaces Empowered Wireless Network: Recent Advances and The Road to 6G

Intelligent surfaces (ISs) have emerged as a key technology to empower a wide range of appealing applications for wireless networks, due to their low cost, high energy efficiency, flexibility of deployment and capability of constructing favorable wireless channels/radio environments. Moreover, the recent advent of several new IS architectures further expanded their electromagnetic functionalities from passive reflection to active amplification, simultaneous reflection and refraction, as well as holographic beamforming. However, the research on ISs is still in rapid progress and there have been recent technological advances in ISs and their emerging applications that are worthy of a timely review. Thus, we provide in this paper a comprehensive survey on the recent development and advances of ISs aided wireless networks. Specifically, we start with an overview on the anticipated use cases of ISs in future wireless networks such as 6G, followed by a summary of the recent standardization activities related to ISs. Then, the main design issues of the commonly adopted reflection-based IS and their state-of-the-art solutions are presented in detail, including reflection optimization, deployment, signal modulation, wireless sensing, and integrated sensing and communications. Finally, recent progress and new challenges in advanced IS architectures are discussed to inspire futrue research.

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arXiv2024

Multi-target Detection for Reconfigurable Holographic Surfaces Enabled Radar

Multi-target detection is one of the primary tasks in radar-based localization and sensing, typically built on phased array antennas. However, the bulky hardware in the phased array restricts its potential for enhancing detection accuracy, since the cost and power of the phased array can become unaffordable as its physical aperture scales up to pursue higher beam shaping capabilities. To resolve this issue, we propose a radar system enabled by reconfigurable holographic surfaces (RHSs), a novel meta-surface antenna composed of meta-material elements with cost-effective and power-efficient hardware, which performs multi-target detection in an adaptive manner. Different from the phase-control structure in the phased array, the RHS is able to apply beamforming by controlling the radiation amplitudes of its elements. Consequently, traditional beamforming schemes designed for phased arrays cannot be directly applied to RHSs due to this structural difference. To tackle this challenge, a waveform and amplitude optimization algorithm (WAOA) is designed to jointly optimize the radar waveform and RHS amplitudes in order to improve the detection accuracy. Simulation results reveal that the proposed RHS-enabled radar increases the probability of detection by 0.13 compared to phased array radars when six iterations of adaptive detection are performed given the same hardware cost.

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arXiv2024

Reconfigurable Holographic Surface Aided Wireless Simultaneous Localization and Mapping

As a crucial facilitator of future autonomous driving applications, wireless simultaneous localization and mapping (SLAM) has drawn growing attention recently. However, the accuracy of existing wireless SLAM schemes is limited because the antenna gain is constrained given the cost budget due to the expensive hardware components such as phase arrays. To address this issue, we propose a reconfigurable holographic surface (RHS)-aided SLAM system in this paper. The RHS is a novel type of low-cost antenna that can cut down the hardware cost by replacing phased arrays in conventional SLAM systems. However, compared with a phased array where the phase shifts of parallelfed signals are adjusted, the RHS exhibits a different radiation model because its amplitude-controlled radiation elements are series-fed by surface waves, implying that traditional schemes cannot be applied directly. To address this challenge, we propose an RHS-aided beam steering method for sensing the surrounding environment and design the corresponding SLAM algorithm. Simulation results show that the proposed scheme can achieve more than there times the localization accuracy that traditional wireless SLAM with the same cost achieves.

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arXiv2024

Channel Estimation for Holographic Communications in Hybrid Near-Far Field

To realize holographic communications, a potential technology for spectrum efficiency improvement in the future sixth-generation (6G) network, antenna arrays inlaid with numerous antenna elements will be deployed. However, the increase in antenna aperture size makes some users lie in the Fresnel region, leading to the hybrid near-field and far-field communication mode, where the conventional far-field channel estimation methods no longer work well. To tackle the above challenge, this paper considers channel estimation in a hybrid-field multipath environment, where each user and each scatterer can be in either the far-field or the near-field region. First, a joint angular-polar domain channel transform is designed to capture the hybrid-field channel's near-field and far-field features. We then analyze the power diffusion effect in the hybrid-field channel, which indicates that the power corresponding to one near-field (far-field) path component of the multipath channel may spread to far-field (near-field) paths and causes estimation error. We design a novel power-diffusion-based orthogonal matching pursuit channel estimation algorithm (PD-OMP). It can eliminate the prior knowledge requirement of path numbers in the far field and near field, which is a must in other OMP-based channel estimation algorithms. Simulation results show that PD-OMP outperforms current hybrid-field channel estimation methods.

cs.IT↗

arXiv2024

Near-Far Field Codebook Design for IOS-Aided Multi-User Communications

Recently, the rapid development of metasurface facilitates the growth of extremely large-scale antenna arrays, making the ultra-massive MIMO possible. In this paper, we study the codebook design and beam training for an intelligent omni-surface (IOS) aided multi-user system, where the IOS is a novel metasurface enabling simultaneous signal reflection and refraction. To deal with the near field expansion caused by the large-dimension of IOS, we design a near-far field codebook to serve users both in the near and far fields without prior knowledge of user distribution. Moreover, to fully exploit the dual functionality of the IOS, the coupling between the reflective and refractive signals is analyzed theoretically and utilized in the codebook design, thereby reducing the training overhead. On this basis, the multi-user beam training is adopted where each codeword covers multiple areas to enable all users to be trained simultaneously. Simulation results verify our theoretical analysis on the reflective-refractive coupling. Compared to the state-of-the-art schemes, the proposed scheme can improve the sum rate and throughput.

cs.IT↗

arXiv2024

Unified Near-field and Far-field Localization with Holographic MIMO

Localization which uses holographic multiple input multiple output surface such as reconfigurable intelligent surface (RIS) has gained increasing attention due to its ability to accurately localize users in non-line-of-sight conditions. However, existing RIS-enabled localization methods assume the users at either the near-field (NF) or the far-field (FF) region, which results in high complexity or low localization accuracy, respectively, when they are applied in the whole area. In this paper, a unified NF and FF localization method is proposed for the RIS-enabled localization system to overcome the above issue. Specifically, the NF and FF regions are both divided into grids. The RIS reflects the signals from the user to the base station~(BS), and then the BS uses the received signals to determine the grid where the user is located. Compared with existing NF- or FF-only schemes, the design of the location estimation method and the RIS phase shift optimization algorithm is more challenging because they are based on a hybrid NF and FF model. To tackle these challenges, we formulate the optimization problems for location estimation and RIS phase shifts, and design two algorithms to effectively solve the formulated problems, respectively. The effectiveness of the proposed method is verified through simulations.

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arXiv2023

RIS-based IMT-2030 Testbed for MmWave Multi-stream Ultra-massive MIMO Communications

As one enabling technique of the future sixth generation (6G) network, ultra-massive multiple-input-multiple-output (MIMO) can support high-speed data transmissions and cell coverage extension. However, it is hard to realize the ultra-massive MIMO via traditional phased arrays due to unacceptable power consumption. To address this issue, reconfigurable intelligent surface-based (RIS-based) antennas are an energy-efficient enabler of the ultra-massive MIMO, since they are free of energy-hungry phase shifters. In this article, we report the performances of the RIS-enabled ultra-massive MIMO via a project called Verification of MmWave Multi-stream Transmissions Enabled by RIS-based Ultra-massive MIMO for 6G (V4M), which was proposed to promote the evolution towards IMT-2030. In the V4M project, we manufacture RIS-based antennas with 1024 one-bit elements working at 26 GHz, based on which an mmWave dual-stream ultra-massive MIMO prototype is implemented for the first time. To approach practical settings, the Tx and Rx of the prototype are implemented by one commercial new radio base station and one off-the-shelf user equipment, respectively. The measured data rate of the dual-stream prototype approaches the theoretical peak rate. Our contributions to the V4M project are also discussed by presenting technological challenges and corresponding solutions.

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arXiv2023

A Heterogeneous 6G Networked Sensing Architecture with Active and Passive Anchors

In the future 6G integrated sensing and communication (ISAC) cellular systems, networked sensing is a promising technique that can leverage the cooperation among the base stations (BSs) to perform high-resolution localization. However, a dense deployment of BSs to fully reap the networked sensing gain is not a cost-efficient solution in practice. Motivated by the advance in the intelligent reflecting surface (IRS) technology for 6G communication, this paper examines the feasibility of deploying the low-cost IRSs to enhance the anchor density for networked sensing. Specifically, we propose a novel heterogeneous networked sensing architecture, which consists of both the active anchors, i.e., the BSs, and the passive anchors, i.e., the IRSs. Under this framework, the BSs emit the orthogonal frequency division multiplexing (OFDM) communication signals in the downlink for localizing the targets based on their echoes reflected via/not via the IRSs. However, there are two challenges for using passive anchors in localization. First, it is impossible to utilize the round-trip signal between a passive IRS and a passive target for estimating their distance. Second, before localizing a target, we do not know which IRS is closest to it and serves as its anchor. In this paper, we show that the distance between a target and its associated IRS can be indirectly estimated based on the length of the BS-target-BS path and the BS-target-IRS-BS path. Moreover, we propose an efficient data association method to match each target to its associated IRS. Numerical results are given to validate the feasibility and effectiveness of our proposed heterogeneous networked sensing architecture with both active and passive anchors.

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arXiv2023

Towards Ubiquitous Positioning by Leveraging Reconfigurable Intelligent Surface

The received signal strength (RSS) based technique is widely utilized for ubiquitous positioning due to its advantage of simple implementability. However, its accuracy is limited because the RSS values of adjacent locations can be very difficult to distinguish. Against this background, we propose the novel RSS-based positioning scheme enabled by reconfigurable intelligent surface (RIS). By modifying the reflection coefficient of the RIS, the propagation channels are programmed in such a way that the differences between the RSS values of adjacent locations can be enlarged to improve the positioning accuracy. New challenge lies in the selection of suitable reflection coefficients for high-accuracy positioning. To tackle this challenge, we formulate the RIS-aided positioning problem and design an iterative algorithm to solve the problem. The effectiveness of the proposed positioning scheme is validated through simulations.

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arXiv2023

MetaRadar: Indoor Localization by Reconfigurable Metamaterials

Indoor localization has drawn much attention owing to its potential for supporting location based services. Among various indoor localization techniques, the received signal strength (RSS) based technique is widely researched. However, in conventional RSS based systems where the radio environment is unconfigurable, adjacent locations may have similar RSS values, which limits the localization precision. In this paper, we present MetaRadar, which explores reconfigurable radio reflection with a surface/plane made of metamaterial units for multi-user localization. By changing the reflectivity of metamaterial, MetaRadar modifies the radio channels at different locations, and improves localization accuracy by making RSS values at adjacent locations have significant differences. However, in MetaRadar, it is challenging to build radio maps for all the radio environments generated by metamaterial units and select suitable maps from all the possible maps to realize a high accuracy localization. To tackle this challenge, we propose a compressive construction technique which can predict all the possible radio maps, and propose a configuration optimization algorithm to select favorable metamaterial reflectivities and the corresponding radio maps. The experimental results show a significant improvement from a decimeter-level localization error in the traditional RSS-based systems to a centimeter-level one in MetaRadar.

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arXiv2023

MetaLocalization: Reconfigurable Intelligent Surface Aided Multi-user Wireless Indoor Localization

The received signal strength (RSS) based technique is extensively utilized for localization in the indoor environments. Since the RSS values of neighboring locations may be similar, the localization accuracy of the RSS based technique is limited. To tackle this problem, in this paper, we propose to utilize reconfigurable intelligent surface (RIS) for the RSS based multi-user localization. As the RIS is able to customize the radio channels by adjusting the phase shifts of the signals reflected at the surface, the localization accuracy in the RIS aided scheme can be improved by choosing the proper phase shifts with significant differences of RSS values among adjacent locations. However, it is challenging to select the optimal phase shifts because the decision function for location estimation and the phase shifts are coupled. To tackle this challenge, we formulate the optimization problem for the RIS-aided localization, derive the optimal decision function, and design the phase shift optimization (PSO) algorithm to solve the formulated problem efficiently. Analysis of the proposed RIS aided technique is provided, and the effectiveness is validated through simulation.

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arXiv2023

MetaRadar: Multi-target Detection for Reconfigurable Intelligent Surface Aided Radar Systems

As a widely used localization and sensing technique, radars will play an important role in future wireless networks. However, the wireless channels between the radar and the targets are passively adopted by traditional radars, which limits the performance of target detection. To address this issue, we propose to use the reconfigurable intelligent surface (RIS) to improve the detection accuracy of radar systems due to its capability to customize channel conditions by adjusting its phase shifts, which is referred to as MetaRadar. In such a system, it is challenging to jointly optimize both radar waveforms and RIS phase shifts in order to improve the multi-target detection performance. To tackle this challenge, we design a waveform and phase shift optimization (WPSO) algorithm to effectively solve the multi-target detection problem, and also analyze the performance of the proposed MetaRadar scheme theoretically. Simulation results show that the detection performance of the MetaRadar scheme is significantly better than that of the traditional radar schemes.

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arXiv2023

Holographic Integrated Sensing and Communications: Principles, Technology, and Implementation

Integrated sensing and communication (ISAC) has attracted much attention as a promising approach to alleviate spectrum congestion. However, traditional ISAC systems rely on phased arrays to provide high spatial diversity, where enormous power-consuming components such as phase shifters are used, leading to the high power consumption of the system. In this article, we introduce holographic ISAC, a new paradigm to enable high spatial diversity with low power consumption by using reconfigurable holographic surfaces (RHSs), which is an innovative type of planar antenna with densely deployed metamaterial elements. We first introduce the hardware structure and working principle of the RHS and then propose a novel holographic beamforming scheme for ISAC. Moreover, we build an RHS-enabled hardware prototype for ISAC and evaluate the system performance in the built prototype. Simulation and experimental results verify the feasibility of holographic ISAC and reveal the great potential of the RHS for reducing power consumption. Furthermore, future research directions and key challenges related to holographic ISAC are discussed.

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arXiv2023

Technology Trends for Massive MIMO towards 6G

At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) has been envisioned as one of the enabling technologies. With the continued success of being applied in the 5G and beyond, the massive MIMO technology has demonstrated its advantageousness, integrability, and extendibility. Moreover, several evolutionary features and revolutionizing trends for massive MIMO have gradually emerged in recent years, which are expected to reshape the future 6G wireless systems and networks. Specifically, the functions and performance of future massive MIMO systems will be enabled and enhanced via combining other innovative technologies, architectures, and strategies such as intelligent omni-surfaces (IOSs)/intelligent reflecting surfaces (IRSs), artificial intelligence (AI), THz communications, cell free architecture. Also, more diverse vertical applications based on massive MIMO will emerge and prosper, such as wireless localization and sensing, vehicular communications, non-terrestrial communications, remote sensing, inter-planetary communications.

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arXiv2022

Reconfigurable Holographic Surface: A New Paradigm to Implement Holographic Radio

Ultra-massive multiple-input multiple-output (MIMO) is one of the key enablers in the forthcoming 6G networks to provide high-speed data services by exploiting spatial diversity. In this article, we consider a new paradigm termed holographic radio for ultra-massive MIMO, where numerous tiny and inexpensive antenna elements are integrated to realize high directive gain with low hardware cost. We propose a practical way to enable holographic radio by a novel metasurface-based antenna, i.e., reconfigurable holographic surface (RHS). Specifically, RHSs incorporating densely packed tunable metamaterial elements are capable of holographic beamforming. Based on the working principle and hardware design of RHSs, we conduct full-wave analyses of RHSs and build an RHS-aided point-to-point communication platform supporting real-time data transmission. Both simulated and experimental results show that the RHS has great potential to achieve high directive gain with a limited size, thereby substantiating the feasibility of RHS-enabled holographic radio. Moreover, future research directions for RHS-enabled holographic radio are also discussed.

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