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Coupled Few-Mode Multicore Fiber With Low Differential Mode Delay Characteristics

JOURNAL OF LIGHTWAVE TECHNOLOGY 2017年第6期35卷 1222-1227页

作者： Sakamoto, Taiji Mori, Takayoshi Wada, Masaki Yamamoto, Takashi Yamamoto, Fumihiko Nakajima, Kazuhide Nippon Telegraph & Tel Corp Access Network Serv Syst Labs Tsukuba Ibaraki 3050805 Japan

We investigate a coupled few-mode multicore fiber (FM-MCF) design to realize an ultrahigh spatial density space division multiplexing (SDM) transmission line with low differential mode delay (DMD) characteristics. We describe a super-mode-based FM-MCF design that takes account of the DMD between modes in the inter-linearly polarized ( LP) mode group (e.g., between LP01- and LP11 - like super modes). We also show a randomly coupled FM-MCF design based on fiber bending and twisting to reduce the DMD between modes in the intra-LP mode group. We fabricated a coupled three-mode seven-core fiber and realized a low DMD value of less than 0.2 ns/km for allmodes where the intercore nonuniformity induced DMD was successfully suppressed owing to distributed random mode coupling. The fabricated fiber has 21 spatial modes within a 125 mu m cladding, and a relative core density of 21, which is the highest of any reported 125 mu m cladding SDM fiber.

关键词： Differential mode delay multi-core fiber multiple-input multiple-output super-mode

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Efficient Sphere Decoding Based on a Regular Detection Tree for Generalized Spatial Modulation MIMO Systems

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IEICE TRANSACTIONS ON COMMUNICATIONS 2018年第1期E101B卷 223-231页

作者： Yoon, Hye-Yeon Lee, Gwang-Ho Kim, Tae-Hwan Korea Aerosp Univ Sch Elect & Informat Engn 76 Hanggongdaehak Ro Goyang Si Gyeonggi Do South Korea

The generalized spatial modulation (GSM) is a new transmission technique that can realize high-performance multiple-input multiple-output (MIMO) communication systems with a low RF complexity. This paper presents an efficient sphere decoding method used to perform the symbol detection for the generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) systems. In the proposed method, the cost metric is modified so that it does not include the cancellation of the nonexistent interference. The modified cost metric can be computed by formulating a detection tree that has a regular structure representing the transmit antenna combinations as well as the symbol vectors, both of which are detected efficiently by finding the shortest path on the basis of an efficient tree search algorithm. As the tree search algorithm is performed for the regular detection tree to compute the modified but mathematically-equivalent cost metric, the efficiency of the sphere decoding is improved while the biterror rate performance is not degraded. The simulation results show that the proposed method reduces the complexity significantly when compared with the previous method: for the 6 +/- 6 64QAM GSM-MIMO system with two active antennas, the average reduction rate of the complexity is as high as 45.8% in the count of the numerical operations.

关键词： multiple-input multiple-output generalized spatial modulation sphere decoding symbol detection maximum likelihood

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Wideband MIMO antenna system with dual polarization for WiFi and LTE applications

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INTERNATIONAL JOURNAL OF MICROWAVE AND WIRELESS TECHNOLOGIES 2016年第3期8卷 643-650页

作者： Moradikordalivand, Alishir Leow, Chee Yen Abd Rahman, Tharek Ebrahimi, Sepideh Tien Han Chua Univ Teknol Malaysia Fac Elect Engn Wireless Commun Ctr Skudai 81310 Johor Malaysia Islamic Azad Univ Young Researchers & Elite Club Arak Branch Arak Iran Islamic Azad Univ Dept Engn Aligoudarz Branch Aligoudarz Iran

In this paper a wideband multi-input multi-output (MIMO) antenna system for WiFi-LTE wireless access point (WAP) application is proposed. The MIMO antenna system consists of two common element microstrip-fed monopole antennas with dual polarization. Physically closed integration of MIMO antenna elements requires a special technique to increase the isolation between the antennas. A novel structure of parasitic element is introduced to improve the isolation between the antennas. The proposed MIMO antenna system is simulated and optimized using CST Microwave Studio. The designed antenna system is fabricated and measured to verify the simulation results. Reflection coefficient of less than 210 dB and isolation more than 15 dB are achieved in the operating frequency range of 2.3-2.9 GHz which covers WiFi 2.4 GHz and LTE 2.6 GHz bands. The proposed system also provides dual polarization with 10 dB polarization diversity gain and envelope correlation coefficient less than 0.15. Each individual antenna has a gain of 5.1 dB and 68% efficiency.

关键词： Isolation Microstrip-fed multiple-input multiple-output Parasitic element Printed monopole antenna

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Parameter Estimation in PMCW MIMO Radar Systems With Few-Bit Quantized Observations

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2022年 70卷 810-821页

作者： Wu, Chao-Yi Zhang, Tianyi Li, Jian Wong, Tan F. Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

We consider the problem of target parameter estimation in phase modulated continuous wave (PMCW) multiple-input multiple-output (MIMO) radar systems with quantized observations. We derive the Cramer-Rao bound (CRB) for jointly estimating targets' amplitudes, time delays, Doppler shifts, and directions. The derived bound provides an efficient method to analyze the estimation performance achieved by different quantization schemes. We also devise the maximum likelihood (ML) estimator for the considered parameters, and a direct grid-based method (DGM) is introduced to obtain the ML estimates. To obtain the ML estimates more efficiently, a two-stage scheme is proposed. In the proposed scheme, we first formulate the estimation problem as a sparse signal recovery problem and modify the sparse learning via iterative minimization (SLIM) approach to solve it. Next, a RELAX-based iterative algorithm is proposed to refine the estimates. Simulation results show that the proposed scheme can approach the CRB. Simulation results also show that using quantized observations does not affect the estimation performance significantly when the targets' amplitudes are similar.

关键词： Quantization (signal) Radar Maximum likelihood estimation MIMO radar Radar imaging Standards Sensors Millimeter wave phase modulated continuous wave radar multiple-input multiple-output target parameter estimation sparse signal recovery Cramer-Rao bound

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Diversity Analysis on Transmit Antenna Selection for Spatial multiplexing Systems With ML Detection

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2013年第9期62卷 4653-4658页

作者： Jin, Xianglan Cho, Durkbin Dongguk Univ Seoul Dept Informat & Commun Engn Seoul 100715 South Korea Dongguk Univ Seoul Dept Math Seoul 100715 South Korea

In this paper, we analyze the diversity order of the optimal transmit antenna selection (TAS) for spatial multiplexing (SM) systems with maximum-likelihood (ML) detection. By deriving the upper and lower bounds on the diversity order, we prove that the optimal TAS of selecting L antennas among M transmit antennas in the SM system with M transmit antennas and N receive antennas obtains a diversity order of N(M -L + 1), which coincides with the well-known results of the respective diversity orders MN and N for the special cases when L = 1 and L = M. Monte Carlo simulations confirm our theoretical result.

关键词： Diversity order maximum likelihood (ML) multiple-input multiple-output spatial multiplexing (SM) transmit antenna selection (TAS)

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Complexity Reduction by Using QR-Based Scheme in Computing Capacity for Optimal Transmission

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WIRELESS PERSONAL COMMUNICATIONS 2011年第2期58卷 391-405页

作者： Pan, Chien-Hung Natl Chiao Tung Univ Dept Commun Engn Hsinchu 300 Taiwan

multiple-input-multiple-output (MIMO) technique is often employed to increase capacity in comparing to systems with single antenna. However, the computational complexity in evaluating channel capacity or transmission rate (data rate) grows proportionally to the number of employed antennas at both ends of the wireless link. Recently, the QR decomposition (QRD) based detection schemes have emerged as a low-complexity solution. After conducting QRD on a full channel matrix that results in a triangular matrix, we claim that computational complexity can be simplified by the following ways. First, to simplify channel capacity calculation, we prove that eigenvalues of the full channel matrix multiplication equals eigenvalues of the triangular channel matrix multiplication. Second, to simplify the calculation of the optimal transmission rate constrained constellation, we propose a simplistic multiplication of the resulted simple triangular matrix and a transmitted signal vector. Then, we also propose a modified mutual information calculation (MMIC) to achieve a quite low-complexity via the divided calculation. By using computer simulation and field- programmable gate array (FPGA) implementation, simulation results show that the proposed QRD-based schemes are capable of achieving conventional performance, but at a low-complexity level.

关键词： multiple-input multiple-output Channel capacity QR decomposition Eigenvalues Mutual information Field-programmable gate array

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Automatic Space-Time Block Code Recognition Using Convolutional Neural Network With Multi-Delay Features Fusion

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IEEE ACCESS 2021年 9卷 79994-80005页

作者： Zhang, Yuyuan Yan, Wenjun Zhang, Limin Ma, Ling Naval Aviat Univ Dept Informat Fus Yantai 264001 Peoples R China Naval Aviat Univ Coll Coastal Def Yantai 264001 Peoples R China

Automatic signal recognition (ASR) is becoming increasingly important in spectrum identification and cognitive radio, but most existing space-time block code (STBC) recognition algorithms are traditional ones and do not account for the complementarities between different features. To overcome these deficiencies, a multi-delay features fusion scheme for ASR of STBC using a convolutional neural network (CNN) is proposed in this study. The proposed scheme tries to fuse different time-delay features of received STBC signals to obtain more discriminating features. The dilated convolution of different dilation rates is applied to realize automated multi-delay feature extraction. Then, two fusion methods, i.e., max-correlation (MC) fusion and multi-delay average (MDA) fusion, are proposed to combine the features of different time delays, and a residual block is applied to achieve better representation of signals. Finally, the simulation results demonstrate the superior performance of the proposed method. It is notable that the recognition accuracy can reach 97.4% with a signal-to-noise ratio (SNR) of -5 dB. In addition, the proposed multi-delay features fusion CNN (MDFCNN) scheme does not need a priori information, i.e., modulation type, channel coefficients, and noise power, which is well suited to non-collaborative communication.

关键词： Convolution Delay effects Simulation Radio transmitters Feature extraction Encoding Robustness Automatic signal recognition multiple-input multiple-output space-time block code convolutional neural network features fusion

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Enhancing Spectrum Sharing Efficiency in Large-Scale MIMO Systems over Integration of Cognitive Radio and Reinforcement Learning

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TEHNICKI VJESNIK-TECHNICAL GAZETTE 2024年第5期31卷 1536-1543页

作者： Krishnamurthi, Madhan Kalimuthu, Vinoth Kumar Anna Univ Dept Elect & Commun Engn Reg Campus Madurai Madurai India Vivekanandha Coll Engn Women Autonomous Dept Elect & Commun Engn Tiruchengode India

Cognitive Radio Networks (CRNs) aim to optimize the limited frequency spectrum by enabling spectrum sharing among different networks and making use of unoccupied frequency bands. The combination of massive multiple-input multiple-output (mMIMO) and CRNs has the potential to greatly improve the efficiency of upcoming wireless communication networks. In our research, we introduce an innovative approach to spectrum sharing in cognitive radio, utilizing 3D spatial data acquisition and Deep Learning for learning and decision-making. We incorporate mMIMO structures into cognitive radio base stations (CRBS) to extract angular information from user equipment (UE) and estimate Direction of Arrival (DoA) using Iterative Hard Thresholding (IHT). Our method involves deploying two base stations per cell for comprehensive 3D spatial spectrum coverage during spectrum prediction. We employ advanced Deep Learning techniques for spectrum sensing instead of reinforcement learning, enhancing CRN performance. Our approach includes a two-fold spectrum scheduling strategy, one focused on maximizing CR coverage and the other on optimizing transmission rates in CRN mMIMO scenarios. By fine-tuning Deep Learning parameters, our model achieves significantly higher Average Aggregate Sum Rate (AASR) compared to previous CRN spectrum sharing methods, without relying on reinforcement learning for spectrum sensing. Our research underscores the effectiveness of integrating Deep Learning into cognitive radio networks, offering the potential for enhanced spectrum utilization and network performance. Additionally, we address energy efficiency using the Nakagami fading channel model and evaluate key metrics, including channel occupancy and energy efficiency, through experimental analysis.

关键词： cognitive radio networks direction of arrival iterative hard thresholding multiple-input multiple-output user equipment

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Double spatial media-based modulation with RF mirrors

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ANNALS OF TELECOMMUNICATIONS 2021年第11-12期76卷 813-825页

作者： Tsvaki, Ronald Pillay, Narushan Xu, Hongjun Univ KwaZulu Natal Sch Engn ZA-4041 Durban South Africa

Media-based modulation (MBM) is an attractive transmission technique that has been recently receiving increased research attention in the wireless communication domain. MBM employs the use of radio frequency mirrors to vastly improve the error performance and/or spectral efficiency of transmission schemes as compared to traditional source-based modulation techniques. Double spatial modulation (DSM) is a new multiple-input multiple-output transmission technique that aims to improve the spectral efficiency of conventional spatial modulation by increasing the number of active transmit antennas. In this study, DSM is extended to employ MBM, such as to improve error performance, and the scheme is termed double spatial media-based modulation (DSMBM). The theoretical average bit error probability of DSMBM is formulated and validated by Monte-Carlo simulation results. Lastly, coded channels are investigated. Typically, soft-output detection coupled with soft-input channel decoding yields a significant signal-to-noise ratio gain. Hence, the authors further propose soft-output maximum-likelihood detectors for the DSM and DSMBM systems.

关键词： Double spatial modulation (DSM) Media-based modulation (MBM) multiple-input multiple-output Radio frequency mirrors Soft-output maximum-likelihood detector Spatial modulation

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3x3 MIMO 60-GHz OFDM-RoF System With Long-Distance Wireless Transmission Enabled by MIMO Volterra Filtering

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JOURNAL OF LIGHTWAVE TECHNOLOGY 2022年第20期40卷 6860-6866页

作者： Wei, Chia-Chien Xie, Zhen-Xiong Ting, Pin-Hsuan Huang, Zheng-Wei Lin, Chun-Ting Natl Sun Yat Sen Univ Dept Photon Kaohsiung 804 Taiwan Natl Yang Ming Chiao Tung Univ Inst Photon Syst Tainan 711 Taiwan Natl Yang Ming Chiao Tung Univ Inst Imaging & Biomed Photon Tainan 711 Taiwan

A 3x3 60-GHz multiple-input multiple-output (MIMO) radio-over-fiber system with an MIMO Volterra filter was demonstrated. The main objective of the proposed scheme is to compensate for the nonlinear distortion caused by radio frequency (RF) power amplifiers (PAs) before the signals reaches the transmitter antennas-particularly when the PAs operate with a high input power to achieve a high output RF power for long-distance wireless transmission. When the required wireless transmission distance is only 7 m, the 3x3 MIMO system with careful control of the PA input power can achieve a data rate of 126 Gbps. However, the data rate decreases rapidly over a longer wireless distance because of the larger loss. By eliminating nonlinear distortion and interchannel interference simultaneously, MIMO Volterra filtering can significantly increase the achievable data rate of a long-distance system. When the required data rate is 90 Gbps (or 100 Gbps), the maximum wireless transmission distance is 118 m (or 70 m) with the aid of MIMO Volterra filtering, but it is only 74 m (or 40 m) without MIMO Volterra filtering.

关键词： MIMO communication Wireless communication Mixers OFDM Band-pass filters Radio frequency Nonlinear distortion Millimeter wave multiple-input multiple-output orthogonal frequency-division multiplexing radio-over-fiber sys- tem Volterra filtering

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