Note 1: This article is one of the "Wireless Sensing Paper Express" series, dedicated to concisely, clearly and completely introducing and interpreting the latest top conference/journal papers in the field of wireless sensing (including but not limited to Nature/Science and its sub-journals; MobiCom, Sigcom, MobiSys, NSDI, SenSys, Ubicomp; JSAC, Acta Radar, etc.).
The paper introduced this time is: 2023, IEEE Journal of Selected Topics in Signal Processing, "Integrated Sensing and Communication for Wireless Extended Reality (XR) with Reconfigurable Intelligent Surface"
article DOI: 10.1109/JSTSP.2023.3304846.
1 Introduction
In this blog, we will discuss a research article titled "Integrated Sensing and Communication for Wireless Extended Reality (XR) with Reconfigurable Intelligent Surface" published in IEEE Journal of Selected Topics in Signal Processing . The main contribution of this paper is to propose a new practical localization algorithm for the integrated perception and communication (ISAC) framework in wireless extended reality (XR), and verify the effectiveness of the algorithm through simulation results.
In the development of wireless networks, human-computer interaction has become a ubiquitous phenomenon, especially in next-generation mobile systems, where extended reality (XR) is considered as a key application scenario. XR is a technology that organically combines the virtual environment with the physical world, including virtual reality (VR), augmented reality (AR) and mixed reality (MR). However, current wireless networks may not be able to fully support the full potential of XR, which has strict requirements for ultra-high immersion, ultra-reliable low-latency communication (URLLC), and management of a large number of sensors and Internet of Things (IoT) devices. Require. Therefore, integrated sensing and communication (ISAC) is considered as a new trend in future wireless networks, which aims to integrate sensing and communication systems to fully utilize wireless resources and realize potential mutual benefits between them.
2 motivation
With the continuous upgrading and iteration of equipment, users can get richer and more immersive experience. At the same time, since XR devices often have large computing and storage requirements, most of the computing and storage tasks are usually offloaded to nearby computers, smartphones, local servers, or micro base stations. In order to ensure high-quality service, current XR devices usually use wired connections, but this will sacrifice user experience. Therefore, wireless connection is considered to be the mainstream trend of XR development in the future. However, current wireless networks may not be able to support the full potential of XR, which has stringent requirements for ultra-high immersion, ultra-reliable low-latency communication (URLLC), and management of a large number of sensors and Internet of Things (IoT) devices .
To address these issues, this paper proposes an integrated perception and communication (ISAC) framework in wireless extended reality (XR) based on reconfigurable smart surfaces (RIS). RIS is a two-dimensional material composed of a large number of sub-wavelength elements, and its electromagnetic properties can be dynamically adjusted by controlling the variable capacitance diode at the bottom. This enables RIS to intelligently reconfigure the wireless propagation environment by introducing additional degrees of freedom. Therefore, in recent years, RIS has attracted extensive attention from academia and industry, and a large number of research results have emerged.
3 methods
In this study, the authors propose a RIS-based ISAC framework in wireless XR and design a practical localization algorithm based on MUSIC. Below we detail the key parts of the method:
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Reconfigurable Smart Surface (RIS) : In this study, RIS is designed as a two-dimensional material composed of a large number of sub-wavelength elements. The electromagnetic properties of the RIS can be dynamically adjusted by controlling the variable capacitance diode at the bottom, thereby changing the amplitude, phase, and even polarization of the reflected signal. This enables RIS to intelligently reconfigure the wireless propagation environment by introducing additional degrees of freedom.
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MUSIC-Based Localization Algorithm : The authors design a practical localization algorithm based on Multiple Signal Classification (MUSIC). The algorithm is able to locate a user (UE) and provide communication services to it using a specially designed RIS configuration.
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Joint optimization problem : The authors propose a problem to jointly optimize the user equipment (UE) beamformer and RIS phase shifter. The goal of this problem is to maximize the channel capacity subject to the Cramér-Rao lower bound (CRLB) constraint.
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Alternating Optimization Algorithm : To solve the joint optimization problem, the authors propose an alternating optimization algorithm based on gradient projection and manifold optimization. The algorithm can alternately optimize the UE beamformer and RIS phase shifter, thereby improving channel capacity and positioning accuracy.
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Channel Model : In this study, the authors considered a Ricean channel model with direct and indirect components. In this model, the direct component can be used for UE positioning, while the non-direct component can be used for communication.
This RIS-based ISAC framework and MUSIC-based positioning algorithm provide a new solution for positioning and communication in wireless XR, which has high practical value and broad application prospects.
4 Experiments and results
In this paper, the proposed positioning algorithm and optimization method are simulated and verified. In the simulation, a 2D scenario is considered, where a micro base station carrying NB antenna serves an XR-UE carrying NU antenna, where RIS with NR element can provide user positioning and communication services. The authors assume that NU ≤ NB ≤ NR, all devices are synchronized, and the orientation angles of UE-BS, UE-RIS, and RIS-BS are ϕ0, ϕ1, and ϕ2, respectively, while the positions of BS, RIS, and UE are pB, pR and pU. For the same path loss and Rician factor, the authors compared the effect of different numbers of RIS elements on the positioning accuracy and channel capacity.
Experimental results show that increasing the number of RIS elements can significantly improve positioning accuracy and channel capacity. In addition, the experimental results also verify the effectiveness of the proposed localization algorithm and optimization method. In wireless XR, the implementation of the ISAC framework can significantly improve user experience, while also opening up new possibilities for the development of future wireless networks.
5 Shortcomings and future prospects
Although the research results of this paper are of high value in theory, there are still some challenges in practical applications. First, the configuration of RIS needs to be adjusted in real time according to changes in the wireless environment, which requires efficient algorithms and powerful computing capabilities. Second, the hardware implementation of RIS is also a difficult problem, especially in massive MIMO systems. In addition, the positioning algorithm and optimization method in the article are based on the ideal wireless environment model, while the actual wireless environment may be affected by various factors, such as multipath propagation, occlusion, etc., which may affect the positioning accuracy and channel capacity.
6 Summary
In general, the article proposes a RIS-based ISAC framework in wireless XR and designs a practical localization algorithm based on MUSIC. Simulation results verify the effectiveness of the proposed positioning algorithm and optimization method, and also show that increasing the number of RIS elements can significantly improve positioning accuracy and channel capacity. This provides a new research direction for the development of future wireless networks, but also brings some new challenges. It is hoped that future research can address these challenges, thereby enabling wider applications of RIS in wireless XR.
The full text of this article can be found here , and interested readers are welcome to read it in depth.