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Statistically robust transceiver design algorithms for relay aided multiple-input multiple-output interference systems

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IET SIGNAL PROCESSING 2018年第1期12卷 51-63页

作者： Singh, Vindheshwari P. Chaturvedi, Ajit K. Indian Inst Technol Kanpur Dept Elect Engn Kanpur Uttar Pradesh India IIT Roorkee Dept Elect & Commun Engn Roorkee Uttar Pradesh India

In this study, the authors consider robust transceiver design for amplify-and-forward relay aided multiple-input multiple-output interference systems assuming direct transmitter-receiver links and imperfect channel state information (CSI). The imperfect CSI of each link consists of the estimated channel and the covariance matrix of the channel estimation error. The authors address two transceiver optimisation problems: one is minimising the sum of averaged mean squared error (MSE) at all the receivers and the other is minimising the maximum averaged MSE among all the receivers, both of which are subject to power constraints at the transmitter and relay nodes. The formulated sum-MSE minimisation and max-MSE minimisation based optimisation problems are non-convex with matrix variables and therefore a globally optimal solution is difficult to obtain. To solve these non-convex optimisation problems, they develop sub-optimal iterative algorithms based on alternating minimisation approach to jointly optimise the precoding matrices at the transmitter and relay nodes and the receiver filter matrices. Simulation results demonstrate the effectiveness of the proposed algorithms and their improved performance against CSI uncertainties at similar computational cost as the existing non-robust designs.

关键词： radio transceivers relay networks (telecommunication) MIMO communication radiofrequency interference amplify and forward communication channel estimation radio links covariance matrices mean square error methods concave programming minimax techniques minimisation iterative methods precoding statistically robust transceiver design algorithms amplify-and-forward relay aided multiple-input multiple-output interference systems direct transmitter-receiver links imperfect channel state information CSI covariance matrix channel estimation error averaged mean squared error minimization power constraints sum-MSE minimisation max-MSE minimisation based optimisation problems nonconvex optimisation problems matrix variables sub-optimal iterative algorithms alternating minimisation approach precoding matrices relay nodes receiver filter matrices

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Non-convex block-sparse compressed sensing with redundant dictionaries

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IET SIGNAL PROCESSING 2017年第2期11卷 171-180页

作者： Liu, Chunyan Wang, Jianjun Wang, Wendong Wang, Zhi Chongqing Normal Univ Foreign Trade & Business Coll Sch Math & Comp Chongqing Peoples R China Southwest Univ Sch Math & Stat Chongqing Peoples R China Southwest Univ Sch Comp & Informat Sci Chongqing Peoples R China

Compressed sensing is a novel theory for signal sampling, which breaks through Nyquist/Shannon sampling limitation and makes it into reality that one can efficiently collect and robustly reconstruct a sparse signal. However, some signals exhibit additional structures in some redundant dictionaries, which is called block-sparse signal. In this study, non-convex block-sparse compressed sensing with redundant dictionaries is investigated. Under the block D-RIP condition (root 2/2) <= delta(2k vertical bar tau)< 1, a sufficient condition for robust signal reconstruction with redundant dictionaries by mixed l (2)/ l (p)(0 < p < 1) minimisation is established. Furthermore, the authors' theoretical results show that, under the assumption that (root 2/2) <= delta 2(k vertical bar tau) < 1, p is an element of (0, (p) over cap], where (p) over cap ={1.6835(1 - delta(2k vertical bar tau), delta(2k vertical bar tau) is an element of[root 2/2,0.73) 0.45418, delta is an element of(0.73, 0.7983) 2.2522(1 - delta(2k vertical bar tau)) delta(2k vertical bar tau) [0.7883, 1), then the block k-sparse signal can be stably reconstructed via non- convex l(2)/l(p) minimisation with redundant dictionaries in the presence of noise. Particularly, this improves the existed result when the block- sparse signal degenerate to the conventional signal case. Besides, the authors also obtain robust reconstruction condition and error upper bound estimation when the block number is no more than four times the sparsity of the block signal( <= 4k). Moreover, the numerical experiments to some extent testify the performance of non- convex l (2)/ l (p)( 0 < p < 1) minimisation with redundant dictionaries.

关键词： compressed sensing signal sampling signal reconstruction concave programming minimisation nonconvex block-sparse compressed sensing redundant dictionaries signal sampling Shannon sampling limitation Nyquist sampling limitation sparse signal reconstruction convex block-sparse D-RIP condition k-sparse signal nonconvex minimisation error upper bound estimation

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Efficient sensitivity based approach for AC transmission expansion planning

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第12期14卷 2378-2388页

作者： Yasasvi, Puvvada Naga Mohapatra, Abheejeet Srivastava, Suresh C. IIT Kanpur Dept Elect Engn Kanpur 208016 Uttar Pradesh India

AC transmission expansion planning (TEP) is a complex problem to solve due to its large scale, mixed-integer, non-linear and non-convex characteristics. This paper presents an efficient sensitivity based approach which employs the primal-dual interior point method (PDIPM), for tackling integer variables in AC TEP. PDIPM's Hessian is used to evaluate the sensitivities of the objective function with respect to the line candidates, which are then used to find a feasible AC TEP solution. The proposed approach solves this non-convex mixed integer non-linear programming problem, without resorting to any use of relaxations/approximations in the AC TEP model. Also, the need and superiority of the AC TEP over the conventional DC TEP is established by comparing both using the proposed approach. Solutions of AC TEP with reactive power planning and an integrated multistage AC TEP are also obtained to demonstrate the performance of the proposed approach. Superior solution quality and lesser computation time of the proposed approach are confirmed by comparing the same with that of the branch and bound/cut approach, constructive heuristic algorithm, merit function-based approach, conic programming and particle swarm optimisation. The studies performed for the various test cases prove the efficacy and computational efficiency of the proposed approach.

关键词： particle swarm optimisation power transmission planning power grids power transmission economics concave programming power transmission reliability reactive power integer programming linear programming nonlinear programming AC transmission expansion planning mixed-integer nonconvex characteristics efficient sensitivity based approach primal-dual interior point method integer variables feasible AC TEP solution nonconvex mixed integer nonlinear programming problem AC TEP model conventional DC TEP reactive power planning integrated multistage AC TEP merit function based approach

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New method to describe the differential distribution table for large S-boxes in MILP and its application

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IET INFORMATION SECURITY 2019年第5期13卷 479-485页

作者： Liu, Ling-Chen Wu, Wen-Ling Zhang, Lei Zheng, Ya-Fei Chinese Acad Sci Inst Software South Four St 4 Beijing 100190 Peoples R China Univ Chinese Acad Sci East Rd 80 Beijing 100049 Peoples R China

Based on the method of the H-representation of the convex hull, the linear inequalities of all possible differential patterns of 4-bit S-boxes in the mix integer linear programming (MILP) model can be generated easily by the SAGE software. Whereas this method cannot be apply to 8-bit S-boxes. In this study, the authors propose a new method to obtain the inequalities for large S-boxes with the coefficients belonging to integer. The relationship between the coefficients of the inequalities and the corresponding excluded impossible differential patterns is obtained. As a result, the number of inequalities can be lower than 4000 for the AES S-box. Then, the new method for finding the best probability of the differential characteristics of 4-15 rounds SM4 in the single-key setting is presented. Especially, the authors found that the 15-round SM4 exists four differential characteristics with 12 active S-boxes. The exact lower bound of the number of differentially active S-boxes of the 16-round SM4 is 15. The authors also found eight differential characteristics of the 19-round SM4 with the probability 2(-124).

关键词： cryptography probability integer programming linear programming concave programming differential distribution table MILP convex hull linear inequalities mix integer linear programming model SAGE software AES S-box differentially active S-boxes differential patterns H-representation

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Signal design based on post-detection SINR for MIMO radar in the presence of signal-dependent interference

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IET RADAR SONAR AND NAVIGATION 2022年第1期16卷 76-90页

作者： Azarang, Marzieh Derakhtian, Mostafa Sheikhi, Abbas Shiraz Univ Sch Elect & Comp Engn Shiraz Iran

In this study, the target detection and signal design problems in the presence of signal-dependent interference for a colocated multiple-input multiple-output (MIMO) radar employing a space-(slow) time transmit signal are addressed. Due to the large dimension of the clutter covariance matrix (CCM) in MIMO radars, the Kronecker form of the CCM is exploited to derive a Rao-based detector, which does not require the secondary data. According to the numerical results, the proposed detector considerably outperforms its competitors. Additionally, by tackling a non-convex sum of ratio problem, a low-complexity algorithm is devised to maximise the post-detection signal-to-interference-plus-noise ratio (SINR) under constant modulus and similarity constraints. Finally, using the simulation results, the effectiveness of the designed signal on the system performance is highlighted.

关键词： clutter covariance matrix signal design problem nonconvex sum of ratio problem post-detection SINR radar interference MIMO radar colocated multiple-input multiple-output radar concave programming target detection radar signal processing signal-dependent interference object detection Rao-based detector CCM post-detection signal-to-interference-plus-noise ratio space-time transmit signal signal design radar detection covariance matrices

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Joint optimisation of UAV grouping and energy consumption in MEC-enabled UAV communication networks

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IET COMMUNICATIONS 2020年第16期14卷 2723-2730页

作者： Zhu, Zhengying Qian, Li Ping Shen, Jiafang Huang, Liang Wu, Yuan Zhejiang Univ Technol Coll Informat Engn Hangzhou 310023 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Univ Macau State Key Lab Internet Things Smart City Taipa Macao Peoples R China Univ Macau Dept Comp & Informat Sci Taipa Macao Peoples R China

This study presents a mobile edge computing (MEC)-enabled UAV communication system, where a number of UAVs are served by terrestrial base stations (TBSs) equipped with computation resource in the non-orthogonal multiple access manner. Each UAV has to offload its computing tasks to the proper TBS due to the limited energy supply. For this, the authors aim at minimising the sum of transmission energy of UAVs and computation energy of TBSs through jointly optimising the UAV transmit power, computation resource allocation, and UAV grouping. Considering the non-convexity of this optimisation problem, they obtain the optimal solution in the coupled steps: the convex resource allocation optimisation and the combinatorial UAV grouping optimisation. By exploiting the convex nature of the resource allocation optimisation problem, they obtain the optimal transmit power and computation allocation based on the KKT conditions and the idea of gradient descent method when considering a single TBS. Then, they adopt the simulated annealing to obtain the optimal UAV grouping and TBS selection based on the proposed resource allocation optimisation algorithm. Finally, simulation results show that the proposed joint optimisation of transmit power, computation resource allocation, and UAV grouping can effectively reduce the energy consumption of MEC-aware UAV communication system.

关键词： autonomous aerial vehicles convex programming vehicular ad hoc networks mobile computing telecommunication power management simulated annealing concave programming multi-access systems computation resource allocation convex resource allocation optimisation combinatorial UAV grouping optimisation resource allocation optimisation problem computation allocation optimal UAV grouping resource allocation optimisation algorithm joint optimisation energy consumption MEC-aware UAV communication system MEC-enabled UAV communication networks communication devices wireless communication systems high-quality service mobile edge computing-enabled UAV communication system nonorthogonal multiple access manner energy supply transmission energy computation energy computation capacity UAV transmit power

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Joint optimal power allocation and relay location for decode-and-forward multi-hop relaying over log-normal channel

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IET COMMUNICATIONS 2015年第18期9卷 2197-2207页

作者： Kundu, Chinmoy Bose, Ranjan Indian Inst Technol Bharti Sch Telecommun Technol & Management New Delhi 110016 India Indian Inst Technol Dept Elect Engn New Delhi 110016 India

A joint optimisation of power allocation (PA) and relay location is proposed for decode-and-forward relaying over multi-hop, independent, log-normal fading channels. Optimisation is carried out at high signal-to-noise ratio (SNR) and low SNR scenarios to minimise the outage probability with a constraint on total transmit power and end-to-end relaying distance. End-to-end average bit error rate is also minimised assuming the same constraints. Optimisation is carried out to find optimal PA (OPA) for a given relay location, optimal relay location (ORL) for a given PA and joint OPA and relay location. All the optimisation problems reformulated from the original problems are shown to be convex except relay location optimisation minimising outage probability at low SNR scenario. It is then solved using properties of concave minimisation. Optimal allocation factors do not depend on the instantaneous channel state information. It also does not depend on total available power in the system except allocation factors evaluated by optimising outage at high SNR. It is observed that OPA allocates more power to weaker links and ORL allocates less distance to weaker links. It is also observed that performance improvement increases with increase in link unbalance and distance-based allocation is most effective.

关键词： decode and forward communication relay networks (telecommunication) fading channels concave programming convex programming minimisation error statistics joint optimal power allocation optimisation joint optimal relay location optimisation decode-and-forward multihop relaying log-normal fading channels signal-to-noise ratio outage probability minimisation total transmit power end-to-end relaying distance end-to-end average bit error rate minimisation joint OPA ORL concave minimisation performance improvement link unbalance distance-based allocation

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Optimal power allocation for energy-efficient full-duplex cognitive relay networks under primary interference

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IET COMMUNICATIONS 2019年第19期13卷 3317-3325页

作者： Poornima, S. Babu, A. V. Natl Inst Technol Dept Elect & Commun Engn Calicut Kerala India

This study investigates optimal power allocation (OPA) for maximising the energy efficiency (EE) of dual-hop underlay full-duplex cognitive relay network, under the influence of interference from primary source. The OPA for the EE optimisation is constrained on the maximum transmit power of the secondary nodes and the interference threshold power which can be tolerated at the primary destination. The authors convert the initial non-convex optimisation problem to a concave fractional programming form and propose an iterative algorithm using parametric transformation to find the OPA vector. Further, they prove that the point of convergence of the proposed iterative algorithm is a Karush-Kuhn-Tucker point of the initial non-convex problem. They numerically demonstrate the EE improvement achieved by the proposed algorithms over equal power allocation strategy.

关键词： relay networks (telecommunication) optimisation concave programming cognitive radio energy conservation convex programming iterative methods optimal power allocation energy-efficient full-duplex cognitive relay networks primary interference energy efficiency dual-hop underlay full-duplex cognitive relay network primary source maximum transmit power interference threshold power primary destination nonconvex optimisation problem concave fractional programming form iterative algorithm OPA vector nonconvex problem equal power allocation strategy

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Design of spectrally compatible waveform with constant modulus for colocated multiple-input multiple-output radar

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IET RADAR SONAR AND NAVIGATION 2019年第8期13卷 1373-1388页

作者： Wang, Xinhai Zhang, Gong Zhang, Yu Wang, Qixia Leung, Henry Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn 29 Jiangjun Ave Nanjing 211100 Jiangsu Peoples R China Minist Educ Key Lab Radar Imaging & Microwave Photon 29 Jiangjun Ave Nanjing 211100 Jiangsu Peoples R China Univ Calgary Dept Elect & Comp Engn Calgary AB Canada

This study investigates the problem of designing unimodular waveform with spectral compatibility for multiple-input multiple-output radar in the presence of multiple targets and the signal-dependent interferences. A new approach is proposed to optimise the spectrally compatible radar waveform subject to not only the constant modulus constraint and the similarity constraint but also the signal-to-interference-plus-noise ratio (SINR) requirements for targets, aiming at suppressing the radar energy in some space-frequency areas occupied by other cooperative communication systems. However, the formulated optimisation problem is NP-hard because of the existence of the non-convex constraints. Based on the dual ascent framework, the authors develop an iterative algorithm to solve this challenging problem. The receive filter is obtained at the beginning of each iteration with the off-the-shelf technique and an innovative method termed phase-only dual ascent method is proposed to get the desired waveform. Additionally, they analyse the performance of the waveforms designed under the global SINR constraint and the local SINR constraint, respectively. Moreover, the convergence of the proposed algorithm is discussed concretely. Finally, the numerical simulations are provided to show the validity of the proposed approach.

关键词： radar signal processing MIMO radar iterative methods concave programming radar interference multiple-input multiple-output radar unimodular waveform spectral compatibility signal-dependent interferences constant modulus constraint signal-to-interference-plus-noise ratio requirements radar energy formulated optimisation problem desired waveform global SINR constraint local SINR constraint spectrally compatible radar waveform cooperative communication systems colocated MIMO radar

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Distributed optimisation design for solving the Stein equation with constraints

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IET CONTROL THEORY AND APPLICATIONS 2019年第15期13卷 2492-2499页

作者： Chen, Guanpu Zeng, Xianlin Hong, Yiguang Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China Chinese Acad Sci Acad Math & Syst Sci Key Lab Syst & Control Beijing 100190 Peoples R China Beijing Inst Technol Sch Automat Key Lab Intelligent Control & Decis Complex Syst Beijing 100081 Peoples R China

In this study, the authors consider distributed computation of the Stein equations with set constraints, where each agent or node knows a few rows or columns of coefficient matrices. By formulating an equivalent distributed optimisation problem, they propose a projection-based algorithm to seek least-squares solutions to the constrained Stein equation over a multi-agent system network. Then, they rigorously prove the convergence of the proposed algorithm to a least-squares solution for any initial condition, and moreover, provide a simplified distributed algorithm with an exponential convergence rate for the case without constraints.

关键词： least squares approximations gradient methods convergence matrix algebra concave programming multi-agent systems distributed optimisation design Stein equations set constraints rows columns coefficient matrices equivalent distributed optimisation problem projection-based algorithm least-squares solution constrained Stein equation multiagent system network simplified distributed algorithm

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