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IEEE International Conference on Electro/Information Technology (EIT)

作者： Kanmani, M. Kannan, M. Anna Univ Madras Inst Technol Dept Elect Engn Chennai Tamil Nadu India

ISBN: (纸本)9781538653982

massive multiple input multiple output (MIMO) is considered to be one of the most emerging technologies to achieve high data rate and better efficiency compared to that of multiuser MIMO (MU-MIMO). The major challenge of this technique is the pilot contamination, which arises mainly due to non-orthogonal property of the pilot sequences. To reduce this pilot contamination and to accurately estimate the channel, we propose an adaptive statistical based channel estimator which estimates the channel statistics in consideration with mobility of the user. The system performance is evaluated in terms of normalized mean square error, energy efficiency and throughput. The simulation results shows that the proposed channel estimation achieves better performance with that of the existing channel estimation.

关键词： massive multiple input multiple output channel estimation Least Square estimation Minimum Mean Square Error estimation Channel Statistics Energy Efficiency

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Adaptive Statistical based Channel Estimation for massive multiple-input multiple-output system

Adaptive Statistical based Channel Estimation for Massive Mu...

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IEEE International Conference on Electro Information Technology

作者： M. KANMANI M. KANNAN Department of Electronics Engineering Anna University Chennai TamilNadu India

关键词： massive multiple input multiple output channel estimation Least Square estimation Minimum Mean Square Error estimation Channel Statistics Energy Efficiency

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The vector perturbation precoding for massive multiple-input multiple-output based on GMD

The vector perturbation precoding for massive multiple-input...

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The 6th International Symposium on Microwave,Antenna,Propagation,and Electromagnetic Compatibility Technologies(MAPE 2015)

作者： Wei Zhang Song Chen Jinbao Zhang Dong Liu School of Electronic and Information Engineering Beijing Jiaotong University

In this paper, we think about the massive multiple-input multiple-output system analysis of vector perturbation precoding based on channel matrix geometric mean decomposition employing the minimum mean square error criterion with instantaneous power constraints for broadcast channels. Our analysis assumes that the transmitter has the imperfect channel state information and the receivers are acquainted with a perfect channel-dependent transmit power normalization factor. We propose a descent method by iteration for searching the perturbation vector in the complex field. The performances of the devised precoding scheme with the large quantity of transmit antennas and singleantenna users are studied in respect to bit error rate analysis through simulations and the numerical results illustrate it appropriated for massive multiple-input multiple-output system both in terms of complexity and performance.

关键词： massive multiple input multiple output Geometric Mean Decomposition imperfect channel state information minimum mean square error

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Energy-Efficient Resource Allocation in Mobile Edge Computing Using NOMA and massive MIMO

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IEEE ACCESS 2025年 13卷 21456-21470页

作者： Alghazali, Qusay Al-Amaireh, Husam Cinkler, Tibor Budapest Univ Technol & Econ Dept Telecommun & Media Informat H-1111 Budapest Hungary Luminus Tech Univ Coll Sch Engn Amman 11118 Jordan ELKH BME Cloud Applicat Res Grp H-1111 Budapest Hungary Gdansk Univ Technol Dept Comp Commun PL-80222 Gdansk Poland

This work addresses the critical challenge of energy consumption in Mobile Edge Computing (MEC), a burgeoning field that extends cloud computing capabilities to the edge of cellular networks. Given the exponential growth of mobile devices and the resultant surge in energy demands, there is an urgent need for efficient energy management strategies to ensure sustainable development and operation of MEC infrastructures. This paper introduces a comprehensive framework for reducing energy consumption in MEC environments by leveraging advanced optimization techniques and energy-efficient resource allocation algorithms. We propose a novel approach that dynamically adjusts the computational resources based on the current network load and the type of services requested, thus minimizing unnecessary energy consumption. We derive and propose an optimized energy consumption for local processing. Then, we study the two network scenarios: Non-Orthogonal multiple Access (NOMA) and massive multiple-input multiple-output (mMIMO). We propose an optimized energy consumption algorithm in NOMA based on the derived processing resource requirements. Then, in mMIMO, we derive optimized power allocation algorithms. Simulations validate the effectiveness of our proposed framework, demonstrating significant energy savings.

关键词： Mobile edge computing non orthogonal multiple access capacity mobile energy massive multiple input multiple output Mobile edge computing non orthogonal multiple access capacity mobile energy massive multiple input multiple output

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Multilevel Modulated Chaotic Encryption and Belief Propagation Decoding

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JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS 2023年第4期68卷 454-459页

作者： Sakoda, K. Informat Technol Ctr Sports Sci Natl Inst Fitness & Sports Kanoya Kagoshima 8912311 Japan

Due to the increasing channel capacity of multiple input multiple output (MIMO) systems, we herein propose a multilevel modulated chaotic encryption method to allow belief propagation (BP) decoding in massive MIMO systems. The proposed scheme was reconstructed based on a previous scheme: binary modulated chaotic encryption for allowing BP decoding. In the encryption method of the proposed scheme, constellation points in general multilevel modulation were encrypted by rotating them by an arbitrary angle using chaos rules. Numerical results showed that the proposed scheme has high performance with regard to the bit error ratio and security. Thus, the proposed scheme could be practical and may also increase the channel capacity of massive MIMO systems using chaotic encryption.

关键词： chaotic encryption massive multiple input multiple output belief propagation multilevel modulation

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Secure Computation Efficiency Resource Allocation for massive MIMO-Enabled Mobile Edge Computing Networks

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China Communications 2024年第11期21卷 150-162页

作者： Sun Gangcan Sun Jiwei Hao Wanming Zhu Zhengyu Ji Xiang Zhou Yiqing School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China Beijing Key Laboratory of Mobile Computing and Pervasive Device and the Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China

In this article,the secure computation efficiency(SCE)problem is studied in a massive multipleinput multiple-output(mMIMO)-assisted mobile edge computing(MEC)*** first derive the secure transmission rate based on the mMIMO under imperfect channel state *** on this,the SCE maximization problem is formulated by jointly optimizing the local computation frequency,the offloading time,the downloading time,the users and the base station transmit *** to its difficulty to directly solve the formulated problem,we first transform the fractional objective function into the subtractive form one via the dinkelbach ***,the original problem is transformed into a convex one by applying the successive convex approximation technique,and an iteration algorithm is proposed to obtain the ***,the stimulations are conducted to show that the performance of the proposed schemes is superior to that of the other schemes.

关键词： eavesdropping massive multiple input multiple output mobile edge computing partial offloading secure computation efficiency

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Enhancing Connectivity in Rural Areas: Secure Spectrum Access in 6G Networks Using Advanced Encryption and Spectrum Sensing Techniques

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IT PROFESSIONAL 2024年第4期26卷 22-28页

作者： Deepanramkumar, P. Sharmila, A. Helen Radhakrishnan, Niranchana Sudheer, Devulapalli Devasia, Jeethu V. Reddy, Ch. Pradeep Yenduri, Gokul Jaisankar, N. VIT AP Univ Sch Comp Sci & Engn Amaravati 522237 Andhra Prades India Alliance Univ Bangalore 562106 India Vellore Inst Technol Sch Comp Sci & Engn Vellore 632014 Tamil Nadu India

The advancement of 6G cognitive radio networks aims to reduce latency in rural and remote areas. Very few studies have been conducted on this technology. Therefore, this study utilizes massive multiple-input, multiple-output (MIMO) technology for secure data transmission at 6G base stations. Blockchain technology authenticates IDs and maintains secure records for network users, with decentralization achieved through the chimp optimization algorithm. The availability of the spectrum is monitored using the Q-learning hidden sparse variate logistic regression model, and the channel-state information is predicted using the quasi-Newton iterative unscented Kalman filter algorithm. Additionally, beamforming is enhanced through cooperative strategies. Secure routing is facilitated by the golden eagle optimization-hyper elliptic curve cryptography algorithm, where data are routed according to paths determined by the Dijkstra algorithm. The MIMO-6G-cognitive radio-based Internet-of-Things framework performs better compared to existing methods.

关键词： Rural Areas 6 G Networks Spectrum Access Spectrum Sensing Connectivity In Rural Areas Communication Network Internet Of Things Data Transmission Base Station Internet Of Things Devices Cooperative Strategy Dijkstras Algorithm Network Routing massive multiple input multiple output Cognitive Radio Data Transmission Rate Unscented Kalman Filter Golden Eagle Secure Data Transmission 6 G Communication Encryption Time Encryption And Decryption Key Generation El Gamal Artificial Neural Network Resource Consumption Security Vulnerabilities Encryption Key Security Level Encryption System

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massive MIMO enabled joint unicast transmission to IoT devices and mobile terminals

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IET COMMUNICATIONS 2020年第13期14卷 2048-2059页

作者： Kumar, Chandan Kashyap, Salil IIT Guwahati Dept Elect & Elect Engn Gauhati 781039 Assam India

We investigate the viability of downlink (DL) unicast transmission from a base station (BS) with massive number of antennas jointly to support machine-centric communication among the internet-of-things (IoT) devices and human-centric communication among the mobile terminals. Specifically, we derive a new expression for the DL sum spectral efficiency (SE) for the IoT devices with maximum ratio precoding when channel estimates are acquired via the proposed distance-dependent grouping based hybrid pilot assignment strategy. We also derive a new DL sum SE expression for IoT devices based on non-orthogonal pilot assignment. We show that under statistical channel inversion based power control at the BS, the proposed strategy yields the highest sum SE and can serve the largest number of IoT devices when compared against orthogonal, non-orthogonal and distance-independent grouping based hybrid strategies. Furthermore, we also analyse the DL sum SE of mobile terminals in the presence of IoT devices when every mobile is given an orthogonal pilot and prove that the sum SE is independent of the pilot assignment strategy employed by the IoT devices. We also obtain the max-min rate for the IoT devices and prove that it is independent of the pilot assignment strategy used by the devices.

关键词： Internet of Things power control channel estimation MIMO communication antenna arrays precoding minimax techniques mobile radio radio spectrum management massive multiple input multiple output joint unicast transmission IoT devices mobile terminals Internet of Things devices DL sum SE expression DL sum spectral efficiency base station machine-centric communication channel estimates distance-dependent grouping hybrid pilot assignment strategy channel inversion power control downlink unicast transmission

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Secure Energy-Saving Resource Allocation on massive MIMO-MEC System

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IEEE ACCESS 2020年 8卷 137244-137253页

作者： Zhao, Wei Wang, Bin Bao, Hui Li, Baogang North China Elect Power Univ Baoding 071003 Peoples R China

Under the double threat of malicious user jamming attacks and eavesdropping, mobile edge computing (MEC) systems will have some information security issues, such as uplink offloading is hindered, user information leakage, and low system energy utilization. To address this problem, we propose to use physical layer security technology to prevent eavesdropping, and use massive multiple input multiple output (mMIMO) technology to reduce interference and improve system energy efficiency. In addition, under the conditions of limited delay, the user's total energy consumption is minimized by jointly optimizing the user's offloading data bits, transmission power, and offloading rate. For this non-convex multi-objective optimization problem, which can be decomposed into multiple sub-optimal sub-problems. First, the Lagrange multiplier method is used to obtain a closed expression of the user's offloading data bits, and then the iterative algorithm is used to obtain the user's optimal transmit power and maximum offloading rate. The simulation results show that, under the premise of ensuring information security, the system's total energy efficiency of antennas (M = 128) is improved 30% compared with antennas (M = 4) when the amount of data reaches 5 x 10(5) bits.

关键词： Mobile edge computing massive multiple input multiple output jamming attack eavesdropping energy consumption

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Co-Existing Preamble and Data Transmissions in Random Access for MTC With massive MIMO

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IEEE TRANSACTIONS ON COMMUNICATIONS 2021年第11期69卷 7576-7586页

作者： Choi, Jinho Ding, Jie Deakin Univ Sch Informat Technol Geelong Vic 3220 Australia

In this article, a Co-existing Preamble and Data (CoPD) random access approach for machine-type communications (MTC) is proposed and studied in massive multiple input multiple output (MIMO) systems. Unlike conventional grant-free random access in which preambles are time-multiplexed with data, the proposed approach enables CoPD transmissions by different groups of devices, which leverages favourable propagation of massive MIMO and successive interference cancellation (SIC) technique. To fully understand the performance behavior of the proposed approach, the error characteristics of channel estimation ( CE) due to SIC error propagation are investigated. To avoid the CE error variance growing arbitrarily with time that leads to data transmission failure, key conditions, with respect to preamble length L, traffic intensity lambda, and average number of data packets per active device (b) over bar , are derived. Under the conditions, we demonstrate that the throughput of the proposed CoPD approach cannot be arbitrarily high by increasing (b) over bar and lambda even though the antenna array size, denoted by M, grows arbitrarily in massive MIMO. Accordingly, its maximum throughput and success probability are theoretically obtained. Simulation results verify our analysis results and confirm that the maximum throughput of the proposed CoPD approach can be at least 4 times than that of the conventional one. Furthermore, its success probability approaches 1 when M -> infinity as long as the derived conditions are met.

关键词： Preamble transmissions machine-type communication massive multiple input multiple output

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