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BER Performance Analysis of OTFS Systems with Power Allocation

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China communications 2023年第1期20卷 24-35页

作者： Zhenduo Wang Zhipeng Liu Zhiguo Sun Xiaoyan Ning College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China

Orthogonal time frequency space(OTFS),as a novel 2-D modulation technique,has been proposed to achieve better BER performances over delayDoppler channels.In this paper,we propose two different power allocation(PA)algorithms in OTFS systems with zero forcing(ZF)or minimum mean square error(MMSE)equalization,where general formulas with PA are derived in advance under the condition of minimum BER(MBER)criterion.On one hand,a suboptimal MBER power allocation method is put forward to achieve better BER performances,and then analytical BER expressions are derived with proposed PA strategy.Considering the case of MMSE equalization,a combined subsymbol allocation(SA)and PA strategy is raised,where some subsymbols may be abandoned due to worse channel conditions,and then it is proven effectively to improve BER performances through theoretical and simulation results.Furthermore,BER performances with proposed joint SA and PA strategy are also investigated in delay-Doppler channels,where an improved message passing(MP)receiver based on equivalent channel matrix with PA is given.

关键词： OTFS PA ZF MMSE BER analysis

Construction of Software Design and Programming Practice Course in information and communication engineering

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国际计算机前沿大会会议论文集 2023年第1期 3-11页

作者： Zhigang Yang Yahui Shen Lin Hou Tao Chen Yuong Qiao College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China

Innovation and entrepreneurship education is becoming one of the important goals of higher education in China.According to the requirements of the Ministry of Education to deepen the reform of innovation and entrepreneur-ship education in colleges and universities,we propose a core principle of“from basis to comprehensiveness,and then to innovation”to construct the software design and programming practice course in the information and communication engineering discipline.We have integrated specialized knowledge teaching with innovation and entrepreneurship training,implemented a series of experimental projects that integrate theory with practice,and explored mixed teaching methods and diversiﬁed examination methods.In this paper,details about software design and programming practice course construction are shown from aspects of teaching content,teaching methods,and examination methods.These course construction experiences will beneﬁt teachers who engage in innovative practical courses in the information and communication engineering discipline.

关键词： Software design and programming practice Couse construction information and communication engineering Comprehensive practice Innovation and entrepreneurship

A complementary integrated Transformer network for hyperspectral image classification

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1288-1307页

作者： Diling Liao Cuiping Shi Liguo Wang college of communication and Electronic engineering Qiqihar UniversityQiqiharChina College of Information and Communication Engineering Dalian Nationalities UniversityDalianChina

In the past,convolutional neural network(CNN)has become one of the most popular deep learning frameworks,and has been widely used in Hyperspectral image classification tasks.Convolution(Conv)in CNN uses filter weights to extract features in local receiving domain,and the weight parameters are shared globally,which more focus on the highfrequency information of the image.Different from Conv,Transformer can obtain the long‐term dependence between long‐distance features through modelling,and adaptively focus on different regions.In addition,Transformer is considered as a low‐pass filter,which more focuses on the low‐frequency information of the image.Considering the complementary characteristics of Conv and Transformer,the two modes can be integrated for full feature extraction.In addition,the most important image features correspond to the discrimination region,while the secondary image features represent important but easily ignored regions,which are also conducive to the classification of HSIs.In this study,a complementary integrated Transformer network(CITNet)for hyperspectral image classification is proposed.Firstly,three‐dimensional convolution(Conv3D)and two‐dimensional convolution(Conv2D)are utilised to extract the shallow semantic information of the image.In order to enhance the secondary features,a channel Gaussian modulation attention module is proposed,which is embedded between Conv3D and Conv2D.This module can not only enhance secondary features,but suppress the most important and least important features.Then,considering the different and complementary characteristics of Conv and Transformer,a complementary integrated Transformer module is designed.Finally,through a large number of experiments,this study evaluates the classification performance of CITNet and several state‐of‐the‐art networks on five common datasets.The experimental results show that compared with these classification networks,CITNet can provide better classification performance.

关键词： complementary integrated Transformer module convolutional neural network Gaussian modulation Transformer

Joint Spectrum Sensing and Spectrum Access for Defending Massive SSDF Attacks:A Novel Defense Framework

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Chinese Journal of Electronics 2022年第2期31卷 240-254页

作者： XU Zhenyu SUN Zhiguo GUO Lili Muhammad Zahid Hammad Chintha Tellambura College of Information and Communication Engineering Harbin Engineering University Department of Electrical and Computer engineering University of Alberta

Multiple secondary users(SUs) perform collaborative spectrum sensing(CSS) in cognitive radio networks to improve the sensing performance. However,this system severely degrades with spectrum sensing data falsification(SSDF) attacks from a large number of malicious secondary users, i.e., massive SSDF attacks. To mitigate such attacks, we propose a joint spectrum sensing and spectrum access framework. During spectrum sensing,each SU compares the decisions of CSS and independent spectrum sensing(IndSS), and then the reliable decisions are adopted as its final decisions. Since the transmission slot is divided into several tiny slots, at the stage of spectrum access, each SU is assigned with a specific tiny time slot. In accordance with its independent final spectrum decisions, each node separately accesses the tiny time slot.Simulation results verify effectiveness of the proposed algorithm.

关键词： Collaborative spectrum sensing Spectrum sensing data falsification Spectrum access Generalized likelihood ratio test

PRI modulation recognition and sequence search under small sample prerequisite

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Journal of Systems engineering and Electronics 2023年第3期34卷 706-713页

作者： ZHANG Chunjie LIU Yuchen SI Weijian College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China Key Laboratory of Advanced Marine communication and information Technology Ministry of Industry and Information TechnologyHarbin Engineering UniversityHarbin 150001China

Pulse repetition interval(PRI)modulation recognition and pulse sequence search are significant for effective electronic support measures.In modern electromagnetic environments,different types of inter-pulse slide radars are highly confusing.There are few available training samples in practical situations,which leads to a low recognition accuracy and poor search effect of the pulse sequence.In this paper,an approach based on bi-directional long short-term memory(BiLSTM)networks and the temporal correlation algorithm for PRI modulation recognition and sequence search under the small sample prerequisite is proposed.The simulation results demonstrate that the proposed algorithm can recognize unilinear,bilinear,sawtooth,and sinusoidal PRI modulation types with 91.43% accuracy and complete the pulse sequence search with 30% missing pulses and 50% spurious pulses under the small sample prerequisite.

关键词： inter-pulse slide pulse repetition interval(PRI)modulation type bi-directional long short-term memory(BiLSTM)network sequence search

Quantum fireworks algorithm for optimal cooperation mechanism of energy harvesting cognitive radio

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Journal of Systems engineering and Electronics 2018年第1期29卷 18-30页

作者： GAO Hongyuan DU Yanan LI Chenwan College of Information and Communication Engineering Harbin Engineering University

For acquiring high energy efficiency and the maximal throughput, a new time slot structure is designed for energy harvesting(EH) cognitive radio(CR). Considering the CR system with EH and cooperative relay, a best cooperative mechanism(BCM)is proposed for CR with EH. To get the optimal estimation performance, a quantum fireworks algorithm(QFA) is designed to resolve the difficulties of maximal throughput and EH, and the proposed cooperative mechanism is called as QFA-BCM. The proposed QFA combines the advantages of quantum computation theory with the fireworks algorithm(FA). Thus the QFA is able to obtain the optimal solution and its convergence performance is proved. By using the new cooperation mechanism and computing algorithm, the proposed QFA-BCM method can achieve comparable maximal throughput in the new timeslot structure. Simulation results have proved that the QFA-BCM method is superior to previous non-cooperative and cooperative mechanisms.

关键词： cognitive radio(CR) energy harvesting(EH) quantum computing fireworks algorithm(FA) cooperative communication

Target threat estimation based on discrete dynamic Bayesian networks with small samples

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Journal of Systems engineering and Electronics 2022年第5期33卷 1135-1142页

作者： YE Fang MAO Ying LI Yibing LIU Xinrui College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China Key Laboratory of Advanced Marine communication and information Technology Ministry of Industry and Information TechnologyHarbin Engineering UniversityHarbin 150001China

The accuracy of target threat estimation has a great impact on command decision-making.The Bayesian network,as an effective way to deal with the problem of uncertainty,can be used to track the change of the target threat level.Unfortunately,the traditional discrete dynamic Bayesian network(DDBN)has the problems of poor parameter learning and poor reasoning accuracy in a small sample environment with partial prior information missing.Considering the finiteness and discreteness of DDBN parameters,a fuzzy k-nearest neighbor(KNN)algorithm based on correlation of feature quantities(CF-FKNN)is proposed for DDBN parameter learning.Firstly,the correlation between feature quantities is calculated,and then the KNN algorithm with fuzzy weight is introduced to fill the missing data.On this basis,a reasonable DDBN structure is constructed by using expert experience to complete DDBN parameter learning and reasoning.Simulation results show that the CF-FKNN algorithm can accurately fill in the data when the samples are seriously missing,and improve the effect of DDBN parameter learning in the case of serious sample missing.With the proposed method,the final target threat assessment results are reasonable,which meets the needs of engineering applications.

关键词： discrete dynamic Bayesian network(DDBN) parameter learning missing data filling Bayesian estimation

Image encryption based on a novel memristive chaotic system,Grain-128a algorithm and dynamic pixel masking

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Journal of Systems engineering and Electronics 2022年第3期33卷 534-550页

作者： HUANG Lilian SUN Yi XIANG Jianhong WANG Linyu College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China Key Laboratory of Advanced Marine communication and information Technology-Ministry of Industry and information Technology Harbin Engineering UniversityHarbin 150001China

In this paper,we first propose a memristive chaotic system and implement it by circuit simulation.The chaotic dynamics and various attractors are analysed by using phase portrait,bifurcation diagram,and Lyapunov exponents.In particular,the system has robust chaos in a wide parameter range and the initial value space,which is favourable to the security communication application.Consequently,we further explore its application in image encryption and present a new scheme.Before image processing,the external key is protected by the Grain-128a algorithm and the initial values of the memristive system are updated with the plain image.We not only perform random pixel extraction and masking with the chaotic cipher,but also use them as control parameters for Brownian motion to obtain the permutation matrix.In addition,multiplication on the finite field GF(2^(8))is added to further enhance the cryptography.Finally,the simulation results verify that the proposed image encryption scheme has better performance and higher security,which can effectively resist various attacks.

关键词： memristive chaotic system super-wide parameter range image encryption Grain-128a algorithm dynamic pixel masking

Antenna Selection and Power Allocation Design for 5G Massive MIMO Uplink Networks

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China communications 2019年第4期16卷 1-15页

作者： Hongyuan Gao Yumeng Su Shibo Zhang Ming Diao College of Information and Communication Engineering Harbin Engineering University

Massive MIMO is one of the key technologies in future 5G communications which can satisfy the requirement of high speed and large capacity. This paper considers antenna selection and power allocation design to promote energy conservation then provide good quality of service(QoS) for the whole massive MIMO uplink network. Unlike previous related works, hardware impairment, transmission efficiency, and energy consumption at the circuit and antennas are involved in massive MIMO networks. In order to ensure the QoS, we consider the minimum rate constraint for each user and the system, which increases the complexity of power allocation problem for maximizing energy and spectral efficiency in massive MIMO system. To this end, a quantum-inspired social emotional optimization(QSEO) algorithm is proposed to obtain the optimal power control strategy in massive MIMO uplink networks. Simulation results assess the great advantages of QSEO which previous strategies do not have.

关键词： 5G massive MIMO antenna selection power allocation quantum-inspiredsocial emotional optimization