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Intelligent Reflecting Surface Enhanced Indoor Robot Path Planning Using Radio Maps
TL;DR: An indoor robot navigation system is investigated, where an intelligent reflecting surface (IRS) is employed to enhance the connectivity between the access point (AP) and a mobile robotic user and 2- or 3-bit IRS phase shifters can achieve nearly the same performance as continuous IRS phase shifts.
Abstract: An indoor robot navigation system is investigated, where an intelligent reflecting surface (IRS) is employed to enhance the connectivity between the access point (AP) and a mobile robotic user. The considered system is optimized for minimization of the travelling time/distance of the mobile robotic user from a given starting point to a predefined final location, while satisfying constraints on the communication quality. To tackle this problem, a radio map based approach is proposed to exploit location-dependent channel propagation knowledge. Specifically, a channel power gain map is constructed, which characterizes the spatial distribution of the maximum expected effective channel power gain of the mobile robotic user for the optimal IRS phase shifts. Based on the obtained channel power gain map, the communication-aware robot path planing problem is solved as a shortest path problem by exploiting graph theory. Numerical results show that: 1) Deploying an IRS can significantly extend the coverage of the AP and reduce the travelling distance of the mobile robotic user; 2) 2- or 3-bit IRS phase shifters can achieve nearly the same performance as continuous IRS phase shifters.
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TL;DR: This work proposes and demonstrates how to exploit the diversity offered by RISs to generate and select easily differentiable radio maps for use in wireless fingerprinting localization applications and applies machine learning feature selection methods to prune the large state space of the RIS, thus reducing complexity and enhancing localization accuracy and position acquisition time.
Abstract: Reconfigurable Intelligent Surfaces (RISs) promise improved, secure and more efficient wireless communications. We propose and demonstrate how to exploit the diversity offered by RISs to generate and select easily differentiable radio maps for use in wireless fingerprinting localization applications. Further, we apply machine learning feature selection methods to prune the large state space of the RIS, thus reducing complexity and enhancing localization accuracy and position acquisition time. We evaluate our proposed approach by generation of radio maps with a novel radio propagation modelling and simulations.
16 citations
Cites background from "Intelligent Reflecting Surface Enha..."
...For instance in time-of-arrival (ToA) and in angle-of-arrival (AoA) based techniques it is difficult for the MU to determine whether a signal came from the AP or the RIS [6]....
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Posted Content•
TL;DR: Signal and spatial modeling for robotic communications are presented, and a novel simultaneous localization and radio mapping (SLARM) framework is proposed for integrating localization and communications into robotic networks.
Abstract: The ongoing surge in applications of robotics brings both opportunities and challenges for the fifth-generation (5G) and beyond (B5G) of communication networks. This article focuses on 5G/B5G-enabled terrestrial robotic communications with an emphasis on distinct characteristics of such communications. Firstly, signal and spatial modeling for robotic communications are presented. To elaborate further, both the benefits and challenges derived from robots' mobility are discussed. As a further advance, a novel simultaneous localization and radio mapping (SLARM) framework is proposed for integrating localization and communications into robotic networks. Furthermore, dynamic trajectory design and resource allocation for both indoor and outdoor robots are provided to verify the performance of robotic communications in the context of typical robotic application scenarios.
14 citations
Cites methods from "Intelligent Reflecting Surface Enha..."
...As a result, it is suitable to use the Rician fading model with a specific Rician factor for robotic communications, which characterizes the deterministic LoS components and the random non-LoS (NLoS) components caused by signal scattering, reflection, and diffraction on surrounding objects [8]....
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TL;DR: An indoor robot navigation system where an intelligent reflecting surface (IRS) is employed to enhance the connectivity between the access point (AP) and robotic users and a graph theory based solution for the robot path planning problem is derived by exploiting the obtained communication rate map.
Abstract: In this paper, an indoor robot navigation system is investigated, where an intelligent reflecting surface (IRS) is employed to enhance the connectivity between the access point (AP) and robotic users. Both single-user and multiple-user scenarios are considered. In the single-user scenario, one mobile robotic user (MRU) communicates with the AP. In the multiple-user scenario, the AP serves one MRU and one static robotic user (SRU) employing either non-orthogonal multiple access (NOMA) or orthogonal multiple access (OMA) transmission. The considered system is optimized for minimization of the travelling time/distance of the MRU from a given starting point to a predefined final location, while satisfying constraints on the communication quality of the robotic users. To this end, a radio map based approach is proposed to exploit location-dependent channel propagation knowledge. For the single-user scenario, a channel power gain map is constructed, which characterizes the spatial distribution of the maximum expected effective channel power gain of the MRU for the optimal IRS phase shifts. Based on the obtained channel power gain map, the communication-aware robot path planing problem is solved by exploiting graph theory. For the multiple-user scenario, a communication rate map is constructed, which characterizes the spatial distribution of the maximum expected rate of the MRU for the optimal power allocation at the AP and the optimal IRS phase shifts subject to a minimum rate requirement for the SRU. The joint optimization problem is efficiently solved by invoking bisection search and successive convex approximation methods. Then, a graph theory based solution for the robot path planning problem is derived by exploiting the obtained communication rate map. Our numerical results verify the effectiveness of the proposed designs.
2 citations
References
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Book•
14 Nov 1995
TL;DR: In this article, the authors introduce the concept of graph coloring and propose a graph coloring algorithm based on the Eulers formula for k-chromatic graphs, which can be seen as a special case of the graph coloring problem.
Abstract: 1. Fundamental Concepts. Definitions and examples. Paths and proofs. Vertex degrees and counting. Degrees and algorithmic proof. 2. Trees and Distance. Basic properties. Spanning trees and enumeration. Optimization and trees. Eulerian graphs and digraphs. 3. Matchings and Factors. Matchings in bipartite graphs. Applications and algorithms. Matchings in general graphs. 4. Connectivity and Paths. Cuts and connectivity. k-connected graphs. Network flow problems. 5. Graph Coloring. Vertex colorings and upper bounds. Structure of k-chromatic graphs. Enumerative aspects. 6. Edges and Cycles. Line graphs and edge-coloring. Hamiltonian cycles. Complexity. 7. Planar Graphs. Embeddings and Eulers formula. Characterization of planar graphs. Parameters of planarity. 8. Additional Topics. Perfect graphs. Matroids. Ramsey theory. More extremal problems. Random graphs. Eigenvalues of graphs. Glossary of Terms. Glossary of Notation. References. Author Index. Subject Index.
7,126 citations
01 Nov 2007
TL;DR: The contents have been restructured to achieve four main objectives: the enlargement of foundational topics for robotics, the enlightenment of design of various types of robotic systems, the extension of the treatment on robots moving in the environment, and the enrichment of advanced robotics applications.
Abstract: The second edition of this handbook provides a state-of-the-art cover view on the various aspects in the rapidly developing field of robotics. Reaching for the human frontier, robotics is vigorously engaged in the growing challenges of new emerging domains. Interacting, exploring, and working with humans, the new generation of robots will increasingly touch people and their lives. The credible prospect of practical robots among humans is the result of the scientific endeavour of a half a century of robotic developments that established robotics as a modern scientific discipline. The ongoing vibrant expansion and strong growth of the field during the last decade has fueled this second edition of the Springer Handbook of Robotics. The first edition of the handbook soon became a landmark in robotics publishing and won the American Association of Publishers PROSE Award for Excellence in Physical Sciences & Mathematics as well as the organizations Award for Engineering & Technology. The second edition of the handbook, edited by two internationally renowned scientists with the support of an outstanding team of seven part editors and more than 200 authors, continues to be an authoritative reference for robotics researchers, newcomers to the field, and scholars from related disciplines. The contents have been restructured to achieve four main objectives: the enlargement of foundational topics for robotics, the enlightenment of design of various types of robotic systems, the extension of the treatment on robots moving in the environment, and the enrichment of advanced robotics applications. Further to an extensive update, fifteen new chapters have been introduced on emerging topics, and a new generation of authors have joined the handbooks team. A novel addition to the second edition is a comprehensive collection of multimedia references to more than 700 videos, which bring valuable insight into the contents. The videos can be viewed directly augmented into the text with a smartphone or tablet using a unique and specially designed app.
3,174 citations
"Intelligent Reflecting Surface Enha..." refers background in this paper
...can achieve nearly the same performance as continuous IRS phase shifters. I. INTRODUCTION In the past few decades, robot technology has developed rapidly and has had a significant impact on human life [1]. Specifically, robots can help humans perform repetitive or dangerous tasks, thus liberating human resources and reducing health risks. There is a wide range of robot applications, including cargo/pac...
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TL;DR: Simulation results demonstrate that an IRS-aided single-cell wireless system can achieve the same rate performance as a benchmark massive MIMO system without using IRS, but with significantly reduced active antennas/RF chains.
Abstract: Intelligent reflecting surface (IRS) is a revolutionary and transformative technology for achieving spectrum and energy efficient wireless communication cost-effectively in the future. Specifically, an IRS consists of a large number of low-cost passive elements each being able to reflect the incident signal independently with an adjustable phase shift so as to collaboratively achieve three-dimensional (3D) passive beamforming without the need of any transmit radio-frequency (RF) chains. In this paper, we study an IRS-aided single-cell wireless system where one IRS is deployed to assist in the communications between a multi-antenna access point (AP) and multiple single-antenna users. We formulate and solve new problems to minimize the total transmit power at the AP by jointly optimizing the transmit beamforming by active antenna array at the AP and reflect beamforming by passive phase shifters at the IRS, subject to users’ individual signal-to-interference-plus-noise ratio (SINR) constraints. Moreover, we analyze the asymptotic performance of IRS’s passive beamforming with infinitely large number of reflecting elements and compare it to that of the traditional active beamforming/relaying. Simulation results demonstrate that an IRS-aided MIMO system can achieve the same rate performance as a benchmark massive MIMO system without using IRS, but with significantly reduced active antennas/RF chains. We also draw useful insights into optimally deploying IRS in future wireless systems.
3,045 citations
"Intelligent Reflecting Surface Enha..." refers background in this paper
...The authors of [7] proposed an alternating optimization based algorithm for the design of the active beamforming at the BS and the passive beamforming at the IRS with the objective of minimizing the transmit power....
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...Due to the high path loss, similar to [7], signals that are reflected by the IRS two or more times are ignored....
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TL;DR: In this article, the authors developed energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements subject to individual link budget guarantees for the mobile users.
Abstract: The adoption of a reconfigurable intelligent surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements subject to individual link budget guarantees for the mobile users. This leads to non-convex design optimization problems for which to tackle we propose two computationally affordable approaches, capitalizing on alternating maximization, gradient descent search, and sequential fractional programming. Specifically, one algorithm employs gradient descent for obtaining the RIS phase coefficients, and fractional programming for optimal transmit power allocation. Instead, the second algorithm employs sequential fractional programming for the optimization of the RIS phase shifts. In addition, a realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. In particular, our results show that the proposed RIS-based resource allocation methods are able to provide up to 300% higher energy efficiency in comparison with the use of regular multi-antenna amplify-and-forward relaying.
1,967 citations
TL;DR: In this paper, the authors provide an overview of the IRS technology, including its main applications in wireless communication, competitive advantages over existing technologies, hardware architecture as well as the corresponding new signal model.
Abstract: IRS is a new and revolutionizing technology that is able to significantly improve the performance of wireless communication networks, by smartly reconfiguring the wireless propagation environment with the use of massive low-cost passive reflecting elements integrated on a planar surface. Specifically, different elements of an IRS can independently reflect the incident signal by controlling its amplitude and/or phase and thereby collaboratively achieve fine-grained 3D passive beamforming for directional signal enhancement or nulling. In this article, we first provide an overview of the IRS technology, including its main applications in wireless communication, competitive advantages over existing technologies, hardware architecture as well as the corresponding new signal model. We then address the key challenges in designing and implementing the new IRS-aided hybrid (with both active and passive components) wireless network, as compared to the traditional network comprising active components only. Finally, numerical results are provided to show the great performance enhancement with the use of IRS in typical wireless networks.
1,897 citations