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25th IEEE Symposium on Computers and Communications (ISCC)

作者： Li, Songyang Wang, Aimin Sun, Geng Liu, Lingling Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Minist Educ Key Lab Symbol Computat & Knowledge Engn Changchun 130012 Peoples R China

ISBN: (数字)9781728180861

ISBN: (纸本)9781728180861

Wireless power transfer based on charging unmanned aerial vehicles (CUAVs) is a promising method for enhancing the lifetime of wireless rechargeable sensor networks (WRSNs). However, how to deploy the CUAVs so that enhancing the charging efficiency is still a key issue. In this work, we formulate a CUAV deployment optimization problem (CUAVDOP) to jointly increase the number of the sensor nodes that within the charging scopes of CUAVs, improve the minimum charging efficiency in the network and reduce the motion energy consumptions of CUAVs. Moreover, the formulated CUAVDOP is analyzed and proofed as NP-hard. Then, we propose an improved firefly algorithm (IFA) to solve the formulated CUAVDOP. IFA introduces two improved items that are the attraction model and adaptive step size factor to enhance the performance of conventional firefly algorithm, so that making it more suitable for CUAVDOP. Simulation results demonstrate that the proposed algorithm is effective for the formulated joint optimization. Moreover, the performance of IFA is better than some other algorithms.

关键词： Wireless rechargeable sensor networks charging unmanned aerial vehicles charging efficiency joint optimization problem firefly algorithm

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Upper bounding service capacity in multi-hop wireless SSMA-based ad hoc networks

Upper bounding service capacity in multi-hop wireless SSMA-b...

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Annual International Conference on Ad Hoc Net-Works

作者： Du, Shirong Daigle, John N. Alidaee, Bahram Univ Mississippi Dept Elect Engn Ctr Wireless Commun University MS 38677 USA Univ Mississippi Sch Business Adm Dept Mkt University MS 38677 USA

Upper bounds on the service carrying capacity of a multi-hop, wireless, SSMA-based ad hoc network are considered herein. The network has a single radio band for transmission and reception. Each node can transmit to, or receive from, multiple nodes simultaneously. We formulate the scheduling of transmissions and control of transmit powers as a joint, mixed-integer, nonlinear optimization problem that yields maximum return at minimum power subject to SINR constraints. We present an efficient tabu search-based heuristic algorithm to solve the optimization problem and rigorously assess the quality of the results. Through analysis and simulation, we establish upper bounds on the VoIP call carrying capacity of the network as function of various parameters. We discuss the pros and cons of using SSMA as a spectrum sharing technique in wireless ad hoc networks. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Wireless ad hoc networks TDMA/SSMA Transmission scheduling and power control joint optimization problem Optimality Tabu search algorithm VoIP call carrying capacity

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Upper Bounding Service Capacity in Multihop Wireless SSMA-Based Ad Hoc Networks

Upper Bounding Service Capacity in Multihop Wireless SSMA-Ba...

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1st International Conference on Ad Hoc Networks (AdHocNets 2009)

作者： Du, Shirong Daigle, John N. Alidaee, Bahram Univ Mississippi Dept Elect Engn Ctr Wireless Commun University MS 38677 USA Univ Mississippi Sch Business Adm MIS POM DepT University MS 38677 USA

ISBN: (纸本)9783642117220

Upper bounds on the service carrying capacity of a multihop, wireless, SSMA-based ad hoc network are considered herein. The network has a single radio band for transmission and reception. Each node can transmit to, or receive from, multiple nodes simultaneously. We formulate the scheduling of transmissions and control of transmit powers as a joint, mixed-integer, nonlinear optimization problem that yields maximum return at minimum power subject to SINR constraints. We present an efficient tabu search-based heuristic algorithm to solve the optimization problem and rigorously assess the quality of the results. Through analysis and simulation, we establish upper bounds on the VoIP call carrying capacity of the network as function of various parameters. We discuss the pros and cons of using SSMA as a spectrum sharing technique in wireless ad hoc networks.

关键词： wireless ad hoc networks TDMA/SSMA transmission scheduling and power control joint optimization problem optimality tabu search algorithm VoIP call carrying capacity upper bounds

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QRD-based Precoder Selection for Maximum-likelihood MIMO Detection

QRD-based Precoder Selection for Maximum-likelihood MIMO Det...

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21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Lin, Chun-Tao Wu, Wen-Rong Natl Chiao Tung Univ Dept Elect Engn Hsinchu 300 Taiwan

ISBN: (纸本)9781424480166

Precoding is an effective method to improve the transmission quality in multiple-input multiple-output (MIMO) systems. In a real-world system, the precoder is selected from a codebook, and its index is fed back to the transmitter. For a maximum-likelihood (ML) receiver, the criterion for precoder selection is equivalent to maximizing the minimum distance of the received signal constellation. T he derivation of the optimum solution, however, may be of high computational complexity due to the requirement of the exhaustive search. To reduce the computational complexity, a suboptimum solution based on singular value decomposition (SVD) has been proposed in literature. In this paper, we propose using a QR decomposition (QRD) based method for precoder selection. To further improve the system performance, we also propose an enhanced QRD-based selection method. With Givens rotations, the computational complexity of the enhanced QRD-based method can be effectively reduced. Finally, we combine precoding with receive antenna selection, and use the proposed QRD-based methods to solve this joint optimization problem. Simulation results show that the proposed approaches can significantly improve the system performance.

关键词： MIMO communication ML receiver QR decomposition QRD-based precoder selection method SVD antenna arrays computational complexity computational complexity joint optimization problem maximum likelihood detection maximum-likelihood MIMO detection maximum-likelihood receiver multiple-input multiple-output systems precoding receive antenna selection received signal constellation receiving antennas singular value decomposition singular value decomposition transmitter

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joint User Pairing and Resource Allocation for Uplink SC-FDMA Systems

Joint User Pairing and Resource Allocation for Uplink SC-FDM...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Fan, Jiancun Yin, Qinye Li, Geoffrey Ye Peng, Bingguang Zhu, Xiaolong Xi An Jiao Tong Univ Sch Elect & Informat Engn MOE Key Lab INNS Xian 710049 Peoples R China Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA USA Huawei Shanghai Res Inst Shanghai Peoples R China

ISBN: (纸本)9781424492688

In this paper, we investigate joint user pairing and resource allocation under the practical constraints in single-carrier frequency-division multiple access (SC-FDMA) LTE uplink systems. We first introduce a joint optimal algorithm based on branch-and-bound search as a benchmark. To reduce complexity, we divide the joint optimization problem into two subproblems: user pairing and resource block allocation. For these subproblems, we develop suboptimal but low-complexity algorithm. The simulation results show that the proposed algorithms outperform the conventional one.

关键词： Complexity theory joints Long Term Evolution MIMO optimization Resource management Throughput Vectors branch-and-bound search algorithm frequency division multiple access joint optimal algorithm joint optimization problem joint user pairing low-complexity algorithms resource allocation resource allocation search problems single carrier frequency-division multiple access LTE uplink systems tree searching uplink SC-FDMA systems

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joint Offloading and Resource Allocation of UAV-assisted Mobile Edge Computing with Delay Constraints 41

Joint Offloading and Resource Allocation of UAV-assisted Mob...

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IEEE 41st International Conference on Distributed Computing Systems (ICDCS)

作者： Tan, Tiao Zhao, Ming Zhu, Yusen Zeng, Zhiwen Cent South Univ Sch Comp Sci & Engn Changsha 410000 Peoples R China Hunan Univ Sch Math Changsha 410000 Peoples R China

ISBN: (纸本)9781665449328

Due to the increase of mobile applications and their users, and the limited coverage of infrastructure, computing resources will inevitably become insufficient. Motivated by this, we consider a UAV-assisted mobile edge computing system with multiple users, an edge server, a remote cloud server, and an unmanned aerial vehicle (UAV). Unmanned aerial vehicles can provide users with a wide range of communication and certain computing power. It can not only process the tasks received by users but also unload the tasks to the edge server or the cloud server. Our proposed scheme aims to optimize the unloading decision of the tasks among all users and the allocation of computing and communication resources so as to minimize the overall energy consumption and the costs of computing and maximum delay. In order to solve the joint optimization problem, we propose an efficient USS algorithm, which includes UAV location optimization algorithm, semi-qualitative relaxation method, and self-adaptive adjustment method. Our numerical results show that the proposed algorithm can significantly reduce the unloading cost of multi-user task compared with other four unloading decisions such as traditional cloud computing which only uses the edge server.

关键词： Mobile edge computing unmanned aerial vehicle unloading decision joint optimization problem USS algorithm

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Charging UAV deployment for improving charging performance of wireless rechargeable sensor networks via joint optimization approach

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COMPUTER NETWORKS 2021年 201卷

作者： Liang, Shuang Fang, Zhiyi Sun, Geng Lin, Chi Li, Jiahui Li, Songyang Wang, Aimin Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Minist Educ Key Lab Symbol Computat & Knowledge Engn Changchun 130012 Peoples R China Jilin Univ Sch Math Changchun 130012 Peoples R China Dalian Univ Technol Sch Software Dalian 116621 Peoples R China

Wireless power transfer based on charging unmanned aerial vehicles (CUAVs) is a promising method for enhancing the lifetime of wireless rechargeable sensor networks (WRSNs). However, how to deploy the CUAVs so that enhancing the charging efficiency is still a challenge. In this work, we formulate a CUAV deployment optimization problem (CUAVDOP) to jointly increase the number of the sensor nodes that within the charging scopes of CUAVs, improve the minimum charging efficiency in the network and reduce the motion energy consumptions of CUAVs. Moreover, the formulated CUAVDOP is analyzed and proven as NP-hard. Then, we propose an improved firefly algorithm (IFA) to solve the formulated CUAVDOP. IFA introduces three improved items that are the opposition-based learning model, attraction model and adaptive step size factor to enhance the performance of conventional firefly algorithm, so that making it more suitable for solving the formulated CUAVDOP. Simulation results demonstrate that the proposed algorithm is effective for dealing with the formulated joint optimization problem. Moreover, the superiority of IFA is verified by tests.

关键词： Wireless rechargeable sensor networks Charging unmanned aerial vehicles Charging efficiency joint optimization problem Firefly algorithm

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