The Experts below are selected from a list of 47919 Experts worldwide ranked by ideXlab platform
Haixia Zhang - One of the best experts on this subject based on the ideXlab platform.
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signal shaping for generalized Spatial Modulation and generalized quadrature Spatial Modulation
IEEE Transactions on Wireless Communications, 2019Co-Authors: Haixia Zhang, Peng Zhang, Cong Liang, Shuping Dang, Mohamedslim AlouiniAbstract:This paper investigates the generic signal shaping methods for the multiple-data-stream generalized Spatial Modulation (GenSM) and the generalized quadrature Spatial Modulation (GenQSM). Three cases with different channel state information at the transmitter (CSIT) are considered, including no CSIT, statistical CSIT, and perfect CSIT. A unified optimization problem is formulated to find the optimal transmit vector set under size, power, and sparsity constraints. We propose an optimization-based signal shaping (OBSS) approach by solving the formulated problem directly and a codebook-based signal shaping (CBSS) approach by finding the sub-optimal solutions in discrete space. In the OBSS approach, we reformulate the original problem to optimize the signal constellations used for each transmit antenna combination (TAC). Both the size and the entry of all signal constellations are optimized. Specifically, we suggest the use of a recursive design for the size optimization. The entry optimization is formulated as a non-convex large-scale quadratically constrained quadratic programming (QCQP) problem and can be solved by the existing optimization techniques with rather high complexity. To reduce the complexity, we propose the CBSS approach using a codebook generated by the quadrature amplitude Modulation (QAM) symbols and a low-complexity selection algorithm to choose the optimal transmit vector set. The simulation results show that the OBSS approach exhibits the optimal performance in comparison with existing benchmarks. However, the OBSS approach is impractical for large-size signal shaping and adaptive signal shaping with instantaneous CSIT due to the demand of high computational complexity. As a low-complexity approach, the CBSS shows comparable performance and can be easily implemented in large-size systems.
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signal shaping for generalized Spatial Modulation and generalized quadrature Spatial Modulation
arXiv: Signal Processing, 2019Co-Authors: Haixia Zhang, Peng Zhang, Shuping Dang, Liang Cong, Mohamedslim AlouiniAbstract:This paper investigates generic signal shaping methods for multiple-data-stream generalized Spatial Modulation (GenSM) and generalized quadrature Spatial Modulation (GenQSM) based on the maximizing the minimum Euclidean distance (MMED) criterion. Three cases with different channel state information at the transmitter (CSIT) are considered, including no CSIT, statistical CSIT and perfect CSIT. A unified optimization problem is formulated to find the optimal transmit vector set under size, power and sparsity constraints. We propose an optimization-based signal shaping (OBSS) approach by solving the formulated problem directly and a codebook-based signal shaping (CBSS) approach by finding sub-optimal solutions in discrete space. In the OBSS approach, we reformulate the original problem to optimize the signal constellations used for each transmit antenna combination (TAC). Both the size and entry of all signal constellations are optimized. Specifically, we suggest the use of a recursive design for size optimization. The entry optimization is formulated as a non-convex large-scale quadratically constrained quadratic programming (QCQP) problem and can be solved by existing optimization techniques with rather high complexity. To reduce the complexity, we propose the CBSS approach using a codebook generated by quadrature amplitude Modulation (QAM) symbols and a low-complexity selection algorithm to choose the optimal transmit vector set. Simulation results show that the OBSS approach exhibits the optimal performance in comparison with existing benchmarks. However, the OBSS approach is impractical for large-size signal shaping and adaptive signal shaping with instantaneous CSIT due to the demand of high computational complexity. As a low-complexity approach, CBSS shows comparable performance and can be easily implemented in large-size systems.
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VTC Spring - Trellis Coded Generalized Spatial Modulation
2014 IEEE 79th Vehicular Technology Conference (VTC Spring), 2014Co-Authors: You Zhou, Dongfeng Yuan, Xiaotian Zhou, Haixia ZhangAbstract:In this paper, a novel trellis coded generalized Spatial Modulation (TCGSM) scheme is presented and analyzed. Similar to that of the traditional generalized Spatial Modulation (GSM), a subset of the entire transmit antennas is selected for transmission at each time slot. Nevertheless, in the proposed TCGSM scheme, the bits in the Spatial domain are first coded by the trellis encoder before antenna selection. The purpose is to combat the correlation of the MIMO channel and hence improve the system performance. We give the detailed system model as well as the trellis encoding/decoding algorithm for the proposed scheme. The performance of the scheme is evaluated through both theoretical analysis and simulations. The results indicate that the proposed scheme is spectral efficient and robust against the channel correlation.
R K Jeyachitra - One of the best experts on this subject based on the ideXlab platform.
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power efficient generalized Spatial Modulation mimo for indoor visible light communications
IEEE Photonics Technology Letters, 2017Co-Authors: Rajesh C Kumar, R K JeyachitraAbstract:In this letter, we propose an active-space, collaborative constellation-based generalized Spatial Modulation (GSM) multiple-input multiple-output encoding that can enhance the power efficiency of indoor visible-light communication compared with the conventional optical GSM. Simulation results verify that the proposed scheme can also achieve performance improvement compared with both Spatial Modulation and conventional GSM under the line-of-sight channel condition, particularly for higher values of spectral efficiency.
Peng Zhang - One of the best experts on this subject based on the ideXlab platform.
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signal shaping for generalized Spatial Modulation and generalized quadrature Spatial Modulation
IEEE Transactions on Wireless Communications, 2019Co-Authors: Haixia Zhang, Peng Zhang, Cong Liang, Shuping Dang, Mohamedslim AlouiniAbstract:This paper investigates the generic signal shaping methods for the multiple-data-stream generalized Spatial Modulation (GenSM) and the generalized quadrature Spatial Modulation (GenQSM). Three cases with different channel state information at the transmitter (CSIT) are considered, including no CSIT, statistical CSIT, and perfect CSIT. A unified optimization problem is formulated to find the optimal transmit vector set under size, power, and sparsity constraints. We propose an optimization-based signal shaping (OBSS) approach by solving the formulated problem directly and a codebook-based signal shaping (CBSS) approach by finding the sub-optimal solutions in discrete space. In the OBSS approach, we reformulate the original problem to optimize the signal constellations used for each transmit antenna combination (TAC). Both the size and the entry of all signal constellations are optimized. Specifically, we suggest the use of a recursive design for the size optimization. The entry optimization is formulated as a non-convex large-scale quadratically constrained quadratic programming (QCQP) problem and can be solved by the existing optimization techniques with rather high complexity. To reduce the complexity, we propose the CBSS approach using a codebook generated by the quadrature amplitude Modulation (QAM) symbols and a low-complexity selection algorithm to choose the optimal transmit vector set. The simulation results show that the OBSS approach exhibits the optimal performance in comparison with existing benchmarks. However, the OBSS approach is impractical for large-size signal shaping and adaptive signal shaping with instantaneous CSIT due to the demand of high computational complexity. As a low-complexity approach, the CBSS shows comparable performance and can be easily implemented in large-size systems.
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signal shaping for generalized Spatial Modulation and generalized quadrature Spatial Modulation
arXiv: Signal Processing, 2019Co-Authors: Haixia Zhang, Peng Zhang, Shuping Dang, Liang Cong, Mohamedslim AlouiniAbstract:This paper investigates generic signal shaping methods for multiple-data-stream generalized Spatial Modulation (GenSM) and generalized quadrature Spatial Modulation (GenQSM) based on the maximizing the minimum Euclidean distance (MMED) criterion. Three cases with different channel state information at the transmitter (CSIT) are considered, including no CSIT, statistical CSIT and perfect CSIT. A unified optimization problem is formulated to find the optimal transmit vector set under size, power and sparsity constraints. We propose an optimization-based signal shaping (OBSS) approach by solving the formulated problem directly and a codebook-based signal shaping (CBSS) approach by finding sub-optimal solutions in discrete space. In the OBSS approach, we reformulate the original problem to optimize the signal constellations used for each transmit antenna combination (TAC). Both the size and entry of all signal constellations are optimized. Specifically, we suggest the use of a recursive design for size optimization. The entry optimization is formulated as a non-convex large-scale quadratically constrained quadratic programming (QCQP) problem and can be solved by existing optimization techniques with rather high complexity. To reduce the complexity, we propose the CBSS approach using a codebook generated by quadrature amplitude Modulation (QAM) symbols and a low-complexity selection algorithm to choose the optimal transmit vector set. Simulation results show that the OBSS approach exhibits the optimal performance in comparison with existing benchmarks. However, the OBSS approach is impractical for large-size signal shaping and adaptive signal shaping with instantaneous CSIT due to the demand of high computational complexity. As a low-complexity approach, CBSS shows comparable performance and can be easily implemented in large-size systems.
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ICCC - Secure Spatial Modulation Based on Artificial Noise
2018 IEEE CIC International Conference on Communications in China (ICCC), 2018Co-Authors: Peng Zhang, Shuangshuang HanAbstract:A secure Spatial Modulation based on artificial noise (AN-SM) is proposed. Different from the traditional Spatial Modulation schemes, the legitimate channel state information is utilized to convey part of information bits instead of amplitude phase Modulation (APM) constellation. By this way, the normal transmit signals will become artificial noise to the eavesdropper, and it is impossible for the eavesdropper to know the legitimate channel state information. Consequently, the secrecy transmission could be achieved. Moreover, all transmit power is used to transmit the legitimate signals without any energy waste. The secrecy rate is analyzed, and the numerical results show that the new AN-SM scheme could achieve high secrecy rate.
You Zhou - One of the best experts on this subject based on the ideXlab platform.
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VTC Spring - Trellis Coded Generalized Spatial Modulation
2014 IEEE 79th Vehicular Technology Conference (VTC Spring), 2014Co-Authors: You Zhou, Dongfeng Yuan, Xiaotian Zhou, Haixia ZhangAbstract:In this paper, a novel trellis coded generalized Spatial Modulation (TCGSM) scheme is presented and analyzed. Similar to that of the traditional generalized Spatial Modulation (GSM), a subset of the entire transmit antennas is selected for transmission at each time slot. Nevertheless, in the proposed TCGSM scheme, the bits in the Spatial domain are first coded by the trellis encoder before antenna selection. The purpose is to combat the correlation of the MIMO channel and hence improve the system performance. We give the detailed system model as well as the trellis encoding/decoding algorithm for the proposed scheme. The performance of the scheme is evaluated through both theoretical analysis and simulations. The results indicate that the proposed scheme is spectral efficient and robust against the channel correlation.
Meng Zhang - One of the best experts on this subject based on the ideXlab platform.
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Virtual Spatial Modulation
IEEE Access, 2016Co-Authors: Miaowen Wen, Meng Zhang, Xiang ChengAbstract:In this paper, we propose a virtual Spatial Modulation (VSM) scheme that performs index Modulation on the virtual parallel channels resulting from the singular value decomposition of the multi-input-multi-output channels. The VSM scheme conveys information through both the indices of the virtual parallel channels and the $M$ -ary modulated symbols. We derive a closed-form upper bound on the average bit error probability (ABEP), which considers the impact of imperfect channel estimation. Moreover, the asymptotic ABEP is also studied, which characterizes the error floor under imperfect channel estimation and the resulting diversity order as well as the coding gain under perfect channel estimation. Computer simulations verify the analysis and show that the VSM scheme can outperform the existing pre-coding aided Spatial Modulation schemes under the same spectral efficiency.
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Differential Spatial Modulation in V2X
2015 9th European Conference on Antennas and Propagation (EuCAP), 2015Co-Authors: Meng Zhang, Xian Cheng, L Q YangAbstract:The rapid development of vehicle-to-vehicle and vehicle-to-infrastructure (V2X) communications calls for highly spectral efficient communication techniques under time-selective channels. Spatial Modulation (SM) facilitates flexible trade-off between spectral and energy efficiency. In this paper, we propose a novel Modulation technique based on SM for V2X, which discards the requirement of channel state information (CSI) at the receiver and exhibits enhanced robustness against time-selective fading and Doppler effects. Our proposed scheme tailors differential Modulation to SM and is named differential Spatial Modulation (DSM). Monte Carlo simulations are carried out to demonstrate the advantage of the new scheme in terms of bit error rate (BER) performance for both point-to-point and dual-hop amplify-and-forward (AF) relaying systems in V2X channels.
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GLOBECOM - Pre-Coding Aided Differential Spatial Modulation
2015 IEEE Global Communications Conference (GLOBECOM), 2014Co-Authors: Meng Zhang, Miaowen Wen, Xiang Cheng, Liuqing YangAbstract:In this paper, we propose a novel Multiple Input Multiple Output (MIMO) scheme based on Spatial Modulation (SM) and termed as Pre-coding aided Differential Spatial Modulation (PDSM). By mapping information to the receiver side space-time transmit blocks and conducting differential Modulation, the PDSM scheme achieves further reduced receiver side complexity in comparison with Pre-coding aided Spatial Modulation (PSM). A general upper bound on the Average Bit Error Probability (ABEP) achieved by the PDSM architecture with an arbitrary number of transmit antennas and two receive antennas is derived, and an exact closed-form ABEP expression is provided for BPSK signaling in Rayleigh fading environment. The PSM architecture with the same system configuration is chosen as a benchmark for performance comparisons. Simulation results validate the analysis and reveal a less-than-3dB Signalto- Noise power Ratio (SNR) penalty of the considered system in comparison with the benchmark.
