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Energy Efficiency Maximization in RIS-Aided Cell-Free Network With Limited Backhaul

IEEE COMMUNICATIONS LETTERS 2021年第6期25卷 1974-1978页

作者： Le, Quang Nhat Nguyen, Van-Dinh Dobre, Octavia A. Zhao, Ruiqin Mem Univ Dept Elect & Comp Engn St John NF A1B 3X9 Canada Univ Luxembourg Interdisciplinary Ctr Secur Reliabil & Trust SnT L-1855 Luxembourg Luxembourg Northwestern Polytech Univ Sch Marine Sci & Technol Key Lab Ocean Acoust & Sensing Xian 710072 Peoples R China

Integrating the reconfigurable intelligent surface in a cell-free (RIS-CF) network is an effective solution to improve the capacity and coverage of future wireless systems with low cost and power consumption. The reflecting coefficients of RISs can be programmed to enhance signals received at users. This letter addresses a joint design of transmit beamformers at access points and reflecting coefficients at RISs to maximize the energy efficiency (EE) of RIS-CF networks, taking into account the limited backhaul capacity constraints. Due to a very computationally challenging nonconvex problem, we develop a simple yet efficient alternating algorithm for its solution. Numerical results verify that the EE of RIS-CF networks is greatly improved, showing the benefit of using RISs.

关键词： Power demand Wireless communication Optimization Central Processing Unit Intercell interference Array signal processing approximation algorithms Cell-free network energy efficiency limited backhaul reconfigurable intelligent surface

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Budgeted Out-Tree Maximization with Submodular Prizes 33

Budgeted Out-Tree Maximization with Submodular Prizes

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33rd International Symposium on algorithms and Computation, ISAAC 2022

作者： D’Angelo, Gianlorenzo Delfaraz, Esmaeil Gilbert, Hugo Université Paris-Dauphine Université PSL CNRS LAMSADE Paris75016 France

We consider a variant of the prize collecting Steiner tree problem in which we are given a directed graph D = (V,A), a monotone submodular prize function p : 2V → R+∪{0}, a cost function c : V → Z+, a root vertex r... 详细信息

ISBN: (纸本)9783959772587

We consider a variant of the prize collecting Steiner tree problem in which we are given a directed graph D = (V,A), a monotone submodular prize function p : 2V → R+∪approximation, a cost function c : V → Z+, a root vertex r ∈ V, and a budget B. The aim is to find an out-subtree T of D rooted at r that costs at most B and maximizes the prize function. We call this problem Directed Rooted Submodular Tree (DRST). For the case of undirected graphs and additive prize functions, Moss and Rabani [SIAM J. Comput. 2007] gave an algorithm that guarantees an O(log |V|)-approximation factor if a violation by a factor 2 of the budget constraint is allowed. Bateni et al. [SIAM J. Comput. 2018] improved the budget violation factor to 1 + Ε at the cost of an additional approximation factor of O(1/Ε2), for any Ε ∈ (0, 1]. For directed graphs, Ghuge and Nagarajan [SODA 2020] gave an optimal quasi-polynomial time O (logloglogn′n′)-approximation algorithm, where n′ is the number of vertices in an optimal solution, for the case in which the costs are associated to the edges. In this paper, we give a polynomial time algorithm for DRST that guarantees an approximation factor of O(√B/Ε3) at the cost of a budget violation of a factor 1 + Ε, for any Ε ∈ (0, 1]. The same result holds for the edge-cost case, to the best of our knowledge this is the first polynomial time approximation algorithm for this case. We further show that the unrooted version of DRST can be approximated to a factor of O(√B) without budget violation, which is an improvement over the factor O(Δ√B) given in [Kuo et al. IEEE/ACM Trans. Netw. 2015] for the undirected and unrooted case, where Δ is the maximum degree of the graph. Finally, we provide some new/improved approximation bounds for several related problems, including the additive-prize version of DRST, the maximum budgeted connected set cover problem, and the budgeted sensor cover problem. © Gianlorenzo D’Angelo, Esmaeil Delfaraz, and Hugo Gilbert.

关键词： approximation algorithms

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A Low-SWaP 16-Beam 2.4 GHz Digital Phased Array Receiver Using DFT approximation

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2020年第5期56卷 3645-3654页

作者： Coutinho, Vitor A. Ariyarathna, Viduneth Coelho, Diego F. G. Pulipati, Sravan Kumar Cintra, Renato J. Madanayake, Arjuna Bayer, Fabio M. Dimitrov, Vassil S. Univ Fed Pernambuco Dept Estat Signal Proc Grp BR-50670901 Recife PE Brazil Florida Int Univ Dept Elect & Comp Engn Miami FL 33199 USA Univ Calgary Dept Elect & Comp Engn Calgary AB T2L 2A6 Canada Univ Fed Santa Maria Dept Estat BR-97105900 Santa Maria RS Brazil Univ Fed Santa Maria LACESM BR-97105900 Santa Maria RS Brazil IOTA Fdn D-10963 Berlin Germany

A low-complexity approximation for the 16-point DFT and its respective multiplierless fast algorithm is proposed. A receive mode multibeam phased-array experiment was realized at 2.4 GHz employing a 16-element IQ receiver array that uses the proposed approximate spatial DFT in real-time in order to achieve multibeam digital beamforming. The 16-beam digital receiver experiment uses a ROACH-2 based Xilinx Virtex-6 FPGA platform for both digital beam computation as well as to perform the multireceiver analog-to-digital conversion. Receive mode RF beams were measured and compared to the exact DFT (realized with fixed-point multipliers with 8-bit twiddle factors). The measured approximate DFT closely followed the measured beams resulting from the fixed-point conventional DFT implementation. The approximate DFT achieves RF beam performance (mainlobe gain, sidelobes) similar to the DFT at the cost of a small error which would be tolerable for the majority of multibeam phased-array receivers. The 16-point approximate DFT provides a hardware reduction of $\sim$70% with respect to FFTs, setting up a low size, weight and power (SWaP) *** maximum magnitude error of the filter bank response is 0.106 ($\approx -20$ dB).

关键词： Discrete Fourier transforms Array signal processing Receivers Complexity theory approximation algorithms Radio frequency Microwave antenna arrays DFT approximation low-complexity beamforming low-complexity FFT multibeam beamforming

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AoI Minimizing of Wireless Rechargeable Sensor Network Based on Trajectory Optimization of Laser-Charged UAV 16th

AoI Minimizing of Wireless Rechargeable Sensor Network Based...

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16th International Conference on Algorithmic Aspects in Information and Management, AAIM 2022

作者： Luo, Chuanwen Hou, Yunan Hong, Yi Chen, Zhibo Liu, Ning Li, Deying School of Information Science and Technology Beijing Forestry University Beijing100083 China Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing100083 China School of Information Renmin University of China Beijing100872 China

ISBN: (纸本)9783031160806

This paper investigates a new UAV-assisted Wireless Rechargeable Sensor Network (WRSNs) based on wireless powered technologies, where the Unmanned Aerial Vehicle (UAV) can not only be used as wireless aerial mobile base station for gathering data from sensors but also be used as mobile charger to replenish energy for sensors, and it also can be charged energy by Laser Beam Directors (LBDs) to overcome the limitation of on-board energy shortage. In such a network, we study the average Age of Information Optimization (AoIO) problem whose objective is to minimize the average AoI of data collected from sensors by UAV. We first prove that the AoIO problem is NP-hard. Since the average AoI depends on UAV’s flight trajectory, the hovering time required for data collection, energy power transfer and laser charging, we propose an approximation algorithm to solve the AoIO problem by jointly optimizing these factors. Afterwards, we conduct extensive simulation experiments to validate effectiveness of the proposed algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： approximation algorithms

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Approximating k-Edge-Connected Spanning Subgraphs via a Near-Linear Time LP Solver 49

Approximating k-Edge-Connected Spanning Subgraphs via a Near...

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49th EATCS International Conference on Automata, Languages, and Programming, ICALP 2022

作者： Chalermsook, Parinya Huang, Chien-Chung Nanongkai, Danupon Saranurak, Thatchaphol Sukprasert, Pattara Yingchareonthawornchai, Sorrachai Aalto University Espoo Finland École Normale Supérieure Paris France University of Copenhagen Denmark KTH Royal Institute of Technology Stockholm Sweden University of Michigan Ann ArborMI United States Northwestern University Evanston IL United States

ISBN: (纸本)9783959772358

In the k-edge-connected spanning subgraph (kECSS) problem, our goal is to compute a minimum-cost sub-network that is resilient against up to k link failures: Given an n-node m-edge graph with a cost function on the edges, our goal is to compute a minimum-cost k-edge-connected spanning subgraph. This NP-hard problem generalizes the minimum spanning tree problem and is the "uniform case" of a much broader class of survival network design problems (SNDP). A factor of two has remained the best approximation ratio for polynomial-time algorithms for the whole class of SNDP, even for a special case of 2ECSS. The fastest 2-approximation algorithm is however rather slow, taking O(mnk) time [Khuller, Vishkin, STOC'92]. A faster time complexity of O(n2) can be obtained, but with a higher approximation guarantee of (2k − 1) [Gabow, Goemans, Williamson, IPCO'93]. Our main contribution is an algorithm that (1 + Ε)-approximates the optimal fractional solution in Õ(m/Ε2) time (independent of k), which can be turned into a (2 + Ε) approximation algorithm that runs in time (Equation presented) for (integral) kECSS;this improves the running time of the aforementioned results while keeping the approximation ratio arbitrarily close to a factor of two. © Parinya Chalermsook, Chien-Chung Huang, Danupon Nanongkai, Thatchaphol Saranurak, Pattara Sukprasert, and Sorrachai Yingchareonthawornchai;licensed under Creative Commons License CC-BY 4.0

关键词： approximation algorithms

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Improved Polynomial-Time approximations for Clustering with Minimum Sum of Radii or Diameters 30

Improved Polynomial-Time Approximations for Clustering with ...

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30th Annual European Symposium on algorithms, ESA 2022

作者： Friggstad, Zachary Jamshidian, Mahya Department of Computing Science University of Alberta Edmonton Canada

ISBN: (纸本)9783959772471

We give an improved approximation algorithm for two related clustering problems. In the Minimum Sum of Radii clustering problem (MSR), we are to select k balls in a metric space to cover all points while minimizing the sum of the radii of these balls. In the Minimum Sum of Diameters clustering problem (MSD), we are to simply partition the points of a metric space into k parts while minimizing the sum of the diameters of these parts. We present a 3.389-approximation for MSR and a 6.546-approximation for MSD, improving over their respective 3.504 and 7.008 approximations developed by Charikar and Panigrahy (2001). In particular, our guarantee for MSD is better than twice our guarantee for MSR. Our approach refines a so-called bipoint rounding procedure of Charikar and Panigrahy's algorithm by considering centering balls at some points that were not necessarily centers in the bipoint solution. This added versatility enables the analysis of our improved approximation guarantees. We also provide an alternative approach to finding the bipoint solution using a straightforward LP rounding procedure rather than a primal-dual algorithm. © 2022 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： approximation algorithms

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Nonlinear Hyperbolic PDE-based Filter for Mixed Poisson-Gaussian Noise Removal from X-ray Images 10

Nonlinear Hyperbolic PDE-based Filter for Mixed Poisson-Gaus...

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10th E-Health and Bioengineering Conference, EHB 2022

作者： Barbu, Tudor Institute of Computer Science Romanian Academy Iași Branch Iași Romania The Academy of Romanian Scientists Romania

ISBN: (纸本)9781665485579

A nonlinear partial differential equation (PDE) – based mixed noise reduction technique for medical X-Ray images is proposed in this paper. The filtering approach uses a novel well-posed second-order hyperbolic PDE model that is solved numerically applying a fast-converging finite difference method-based discretization algorithm. This iterative numerical approximation scheme restores successfully the medical images affected by mixtures of noise, since it removes properly both the Gaussian and Poisson noise. The effectiveness of the introduced technique is illustrated by the restoration experiments and method comparison described in this work. © 2022 IEEE.

关键词： approximation algorithms

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Reconfigurable Intelligent Surface-Assisted Multi-Cell MISO Communication Systems Exploiting Statistical CSI

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IEEE WIRELESS COMMUNICATIONS LETTERS 2021年第10期10卷 2313-2317页

作者： Luo, Caihong Li, Xiao Jin, Shi Chen, Yijian Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Pazhou Lab Guangzhou 510330 Peoples R China ZTE Corp Shenzhen 518057 Peoples R China State Key Lab Mobile Network & Mobile Multimedia Shenzhen 518057 Peoples R China

In this letter, we investigate the reconfigurable intelligent surface (RIS) assisted multi-cell downlink multi-input single-output system under the assumption of only statistical channel state information at the base stations and RIS. Firstly, a closed-form ergodic weighted sum rate approximation is obtained. Then, based on this approximation, we propose an approximate optimal joint beamforming vectors and RIS phase shift matrix design algorithm utilizing the fractional programming and complex circle manifold. Simulation results show that the proposed low-complexity algorithm performs well.

关键词： Array signal processing Optimization Downlink Transmission line matrix methods Matrix decomposition approximation algorithms Wireless communication RIS statistical CSI fractional programming multi-cell

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Adaptive Seed Minimization for Diversified Influence Maximization 5

Adaptive Seed Minimization for Diversified Influence Maximiz...

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5th International Conference on Data Science and Information Technology, DSIT 2022

作者： Zhang, Yangguang Chen, Qi Shen, Ji Shi, Qihao Wang, Can College of Computer Science Zhejiang University Hang Zhou China

ISBN: (数字)9781665498685

ISBN: (纸本)9781665498685

The goal of the problem of maximizing influence in social networks is to trigger large-scale network chain influence spread by selecting seed users with greater influence. As a dual problem of maximizing impact, the seed minimization problem requires the minimum number of seed nodes to meet a given threshold. Most of the existing seed minimization algorithms consider non-adaptive settings, that is, select all seed nodes in the same batch without observing how they affect other users. Existing research mainly focuses on maximizing the number of activated nodes, but the diversity of activated nodes has been neglected. In this paper, the problem of diversity seed minimization in adaptive environment is studied. The goal of the problem is to select a minimum seed set so that the number and diversity of active nodes reach the target threshold. The seed node is selected from multiple batches, so the selection of a batch can use the actual impact information of the previous batch. This paper proposes an adaptive and effective diversity influence maximization algorithm, which provides the approximate guaranteed solution of ln2 ησ+ln2 ηd+2 ln ησ ln ηd+2 1-ϵ in the expected time of O((ηsigma+n/D(V) ηd) (n+m) · ln n/ϵ2), where ηsigma;and ηd is the target influence and diversity diffusion, and ϵin(0,1) is the user specified parameter. © 2022 IEEE.

关键词： Social networking (online) Data science Minimization approximation algorithms Information technology

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An Experimental Evaluation of Semidefinite Programming and Spectral algorithms for Max Cut 20

An Experimental Evaluation of Semidefinite Programming and S...

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20th International Symposium on Experimental algorithms, SEA 2022

作者： Mirka, Renee Williamson, David P. Cornell University IthacaNY United States

ISBN: (纸本)9783959772518

We experimentally evaluate the performance of several Max Cut approximation algorithms. In particular, we compare the results of the Goemans and Williamson algorithm using semidefinite programming with Trevisan’s algorithm using spectral partitioning. The former algorithm has a known .878 approximation guarantee whereas the latter has a .614 approximation guarantee. We investigate whether this gap in approximation guarantees is evident in practice or whether the spectral algorithm performs as well as the SDP. We also compare the performances to the standard greedy Max Cut algorithm which has a .5 approximation guarantee and two additional spectral algorithms. The algorithms are tested on Erdős-Renyi random graphs, complete graphs from TSPLIB, and real-world graphs from the Network Repository. We find, unsurprisingly, that the spectral algorithms provide a significant speed advantage over the SDP. In our experiments, the spectral algorithms return cuts with values which are competitive with those of the SDP. © Renee Mirka and David P. Williamson

关键词： approximation algorithms

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