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joint optimization scheme for intelligent reflecting surface aided multi-relay networks

IET COMMUNICATIONS 2022年第13期16卷 1498-1508页

作者： Li, Xueyi Wong, Angus K. Y. Hung, Kevin Wang, Yonghua Wang, Everett X. Guangdong Univ Technol Sch Informat Engn Guangzhou Peoples R China Macao Polytech Inst Sch Appl Sci Taipa Macao Peoples R China Hong Kong Metropolitan Univ Sch Sci & Technol Hong Kong Peoples R China Guangdong Univ Technol Sch Automat Guangzhou Peoples R China

The latest research on hybrid networks of decode-and-forward (DF) relay and intelligent reflecting surface (IRS) is limited to just a single relay. To harvest multiple relay gains, this paper proposes a hybrid communication networks that combines multiple DF relays with an IRS. The authors formulate and address the joint optimization problem to maximize the end-to-end transmission rate by jointly optimizing the reflect beam forming, the best relay selection and the power allocation, subject to total transmit power constraint. Moreover, to better exploit the degrees of freedom, it is proposed that the source also transmits signals in the second time slot. While the optimization problem is difficult to solve, the authors propose some efficient approaches to make the problem tractable. First, power allocation problem is simplified by applying Cauchy-Schwarz inequality and introducing equivalent channel gain, second, non-convex rank-one constraint is overcome by utilizing semidefinite relaxation (SDR) approach, then the slacked non-convex constraint is overcome by applying first-order Taylor expansion approximation. The simulation results demonstrate that our proposed joint optimization scheme for hybrid networks of multiple DF relays with an IRS has significant performance improvement over the other optimization schemes, such as the optimization scheme for hybrid networks of single DF relay and an IRS.

关键词： nonconvex constraint joint optimization problem relay selection hybrid communication networks power allocation problem convex programming relay networks (telecommunication) end-to-end transmission rate optimisation concave programming telecommunication power management introducing equivalent channel gain decode and forward communication problem tractable IRS multiple relay gains joint optimization scheme single DF relay multiple DF relays hybrid networks total transmit power constraint cooperative communication multirelay networks latest research nonconvex rank-one constraint single relay intelligent reflecting surface

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Cascaded suppression method based on joint iterative optimization for airborne passive radar

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DIGITAL SIGNAL PROCESSING 2020年 100卷 102686-000页

作者： Deng, Yaqi Wang, Jun Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

To overcome the severe space-time adaptive processing (STAP) performance degradation caused by array gain/phase (GP) errors and undesirable random range sidelobe couplings, a novel cascaded suppression method based on joint iterative optimization is proposed for airborne passive radar. The proposed cascaded method (CM) exploits the sparse nature of these undesirable sidelobe couplings, reformulates the sparsity recovery problem as a joint optimization problem of the spatio-temporal profile and array GP errors, and achieves sidelobe couplings suppression before STAP. A range of simulations is conducted to test the proposed method. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Array gain/phase errors Sidelobe couplings Cascaded method joint optimization problem Airborne passive radar

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joint trajectory design and power allocation for unmanned aerial vehicles aided secure transmission in the presence of no-fly zone

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IET COMMUNICATIONS 2022年第2期16卷 172-186页

作者： Yin, Guoxiao Zhou, Xiaotian Ma, Piming Fang, Fang Zhao, Peng Shandong Univ Sch Control Sci & Engn Jinan Peoples R China Shandong Univ Shandong Key Lab Wireless Commun Technol Jinan Peoples R China Shandong Univ Sch Informat Sci & Engn Jinan Peoples R China Univ Durham Dept Engn Durham England

Unmanned aerial vehicles (UAVs) are widely considered as key enablers for future wireless networks due to their advantages, such as high mobility and flexible deployment. In this paper, the UAV assisted secure communication system is investigated, where the UAV is deployed as the mobile jammer to prevent the eavesdropper from overhearing the confidential message. With the objective of maximizing the secrecy rate, a joint optimization problem involving the trajectory and transmit power of UAV, as well as the transmit power of source node is formulated. Moreover, the effects of Non-Fly Zone (NFZ) and imperfect estimation on the location of eavesdropper are also taken into consideration. As the original problem is hardly trackable, the worst case secrecy rate (WCSR) assumption is first employed to bypass the uncertainty brought by the estimation error. Then a block coordinate descent (BCD) based algorithm is proposed to decompose the problem into three sub-ones, where the trajectory of UAV, the transmit power of UAV and the transmit power of source can be obtained in an iterative manner. Simulation results reveal that the proposed algorithm can improve the secrecy performance significantly. In addition, the robustness of the proposed algorithm under the estimation error can also be verified.

关键词： autonomous aerial vehicles mobile jammer BCD based algorithm wireless channels secure transmission joint trajectory design NFZ joint optimization problem no-fly zone eavesdropper optimisation concave programming worst case secrecy rate assumption UAV unmanned aerial vehicle aided secure transmission power allocation WCSR secure communication system worst case secrecy rate high mobility block coordinate descent flexible deployment cooperative communication wireless networks jamming imperfect estimation estimation error

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joint mission planning and spectrum resources optimization for multi-UAV reconnaissance

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IET COMMUNICATIONS 2023年第3期17卷 324-335页

作者： Liao, Naiwen He, Panfeng Du, Yihang Zhang, Yu Chen, Yong Liang, Tao Natl Univ Def Technol Res Inst 63 Nanjing Peoples R China Army Engn Univ PLA Coll Commun Engn Nanjing Peoples R China

In this paper, the problem of mission planning and spectrum resource allocation for cooperative reconnaissance of ground targets with multiple unmanned aerial vehicles (UAVs) is studied. A joint mission planning and spectrum resource optimization algorithm for multi-UAVs is proposed to improve the information transmission rate by reusing the spectrum of existing users. The joint optimization problem is formulated as mixed-integer non-linear programming. The block coordinate descent (BCD) method is further applied to achieve the optimal strategies of mission planning, channel allocation, and power control. Specifically, an improved genetic algorithm (GA) combined with the successive convex approximation (SCA) is used to solve the sub-problem of mission planning. For the channel allocation sub-problem, an iterative convergence channel allocation algorithm is proposed. Numerical results show that the proposed algorithm can achieve a higher UAV transmission rate and better robustness than existing algorithms.

关键词： multiple unmanned aerial vehicles genetic algorithms joint optimization problem Optimisation techniques spectrum resource optimization algorithm improved genetic algorithm information transmission rate mixed-integer nonlinear programming convex programming Mobile robots iterative methods autonomous aerial vehicles Telerobotics joint mission planning Aerospace control higher UAV transmission rate Power and energy control multiUAVs iterative convergence channel allocation algorithm channel allocation spectrum resource allocation integer programming Telecommunication systems (energy utilisation) optimal strategies spectrum resources optimization Interpolation and function approximation (numerical analysis) multiUAV reconnaissance linear programming resource allocation power control optimisation UAVs nonlinear programming

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

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AD HOC NETWORKS 2011年第2期9卷 120-130页

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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Resource allocation in OFDM-based cognitive radio networks with multiple AF relays 8

Resource allocation in OFDM-based cognitive radio networks w...

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8th International Conference on Signal Processing and Communication Systems, (ICSPCS)

作者： Biyanwilage, Shashika Gunawardana, Upul Liyanapathirana, Ranjith Univ Western Sydney Sch Comp Engn & Math Penrith NSW 2751 Australia

ISBN: (纸本)9781479952557

This paper investigates the relay selection and power allocation problems in OFDM-based cognitive radio networks with multiple amplify-and-forward relays. The objective is to maximize the total instantaneous capacity of the cognitive radio network while maintaining the interference introduced to the primary network below a given threshold and also maintaining the total transmit power below the individual power limitations at cognitive radio transmitters. The joint optimization problem is a mixed binary integer problem which is NP-hard. Thus, we divide the joint optimization problem into two subproblems, and solve the resource allocation problem suboptimally. Two suboptimal resource allocation methods are proposed and their performance is compared with the joint optimal resource allocation. Results show that near optimal performance can be obtained with less complex suboptimal approaches.

关键词： OFDM modulation amplify and forward communication cognitive radio computational complexity integer programming radio networks radiofrequency interference relay networks (telecommunication) resource allocation NP-hard problem OFDM-based cognitive radio networks cognitive radio transmitters joint optimal resource allocation joint optimization problem mixed binary integer problem multiple AF relays multiple amplify-and-forward relays power allocation problems relay selection suboptimal resource allocation methods Interference constraints joints OFDM optimization Relays Resource management Cognitive radio Resource utilization management of resources Orthogonal frequency division multiplexing Radio networks relay Interference constraints Nondeterministic polynomial-time hard Radiofrequency interference joints joints Integer Programming complexity classes

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Soft Spectrum Sensing and Power Adaptation in Multiband Cognitive Radios

Soft Spectrum Sensing and Power Adaptation in Multiband Cogn...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Mu, Hua Tugnait, Jitendra K. Auburn Univ Dept Elect & Comp Engn Auburn AL 36849 USA

ISBN: (纸本)9781424492688

We consider joint optimization of spectrum sensing, channel access and power allocation in a multi-band cognitive radio network. Instead of making hard binary decisions as in traditional hypothesis testing spectrum sensing schemes, a soft spectrum sensing concept using the continuous-valued sensing test statistics is considered. The channel access decision about whether to access the channel or not is relaxed into allowing the secondary user to access channels with some probability. This joint optimization problem is aimed at maximizing the secondary users' sum throughput while keeping the interference to primary users under a specified threshold. The problem is shown to be a convex optimization problem and the Lagrangian dual method is employed to obtain the optimal solution. Two heuristic algorithms are also proposed to reduce the complexity while achieving a near optimal performance. Simulation results show that our soft sensing based algorithm significantly outperforms traditional hard decision sensing algorithms.

关键词： Cognitive radio Interference Lagrangian dual method optimization Resource management Sensors Signal to noise ratio Throughput binary decision diagrams channel access cognitive radio continuous-valued sensing test statistic convex optimization problem convex programming hard binary decisions heuristic algorithm hypothesis testing spectrum sensing scheme interference suppression joint optimization problem multiband cognitive radio network power adaptation probability probability radiofrequency interference secondary user sum throughput soft spectrum sensing

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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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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

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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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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