Low-Complexity Generalized Spatial Modulation Schemes Using Codebook-Assisted MIMO Detectors

Chen, Yeng; Cheng, Wen-Chun; Li, Chih-Peng; Haas, Zygmunt J.

doi:10.1109/tvt.2018.2871577

Cited by 5 publications

(4 citation statements)

References 12 publications

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“…antennas pairs (k, l) given by (6). After updating the TPC vector p, each iteration of the optimization algorithm uses (6) to select a single ED from (4) for each antenna pair. Together with the Nt EDs calculated from (5), the total number of EDs becomes  …”

Section: Reducing the Number Of Euclidean Distancesmentioning

confidence: 99%

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Reduced Complexity Spatial Modulation Transmit Precoding for PSK Constellation

2022

MSA Engineering Journal

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Spatial modulation (SM) conveys extra data by selecting the transmit antenna. This makes SM prone to channel irregularities like multipath Raleigh fading. Hence, employing and optimizing a transmit precoder (TPC) that matches the channel can enhance the SM bit error rate performance by increasing the Euclidean distance (ED) among all possible received vectors. However, it is common that optimization algorithms endure high complexity. Focusing on M-PSK constellation, and by reducing the number of Euclidean Distance constraints, we cut the complexity by nearly a factor of M. This is a significant reduction for high order constellations with a large value of M. This concept is shown to benefit any TPC optimization algorithm for SM and its variants. To further shrink the complexity, we introduce an optimization algorithm that minimizes the sum of the exponentials of negative EDs. The paper shows that the complexity can be reduced significantly without loss in performance.

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Section: Reducing the Number Of Euclidean Distancesmentioning

confidence: 99%

“…To circumvent this problem, transmit precoding is typically used [2] [4] [5]. A Transmit Precoder (TPC) may be selected from a predefined codebook that is known to both the transmitter and the receiver [6] [7]. Alternatively, the TPC can be optimized for the CSI, providing better performance.…”

Section: Introductionmentioning

confidence: 99%

Reduced Complexity Spatial Modulation Transmit Precoding for PSK Constellation

2022

MSA Engineering Journal

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“…3) Block Linear Detector Scheme: The linear detection schemes are supposed to solve the inverse operation for (3) and (4) that have the channel matrix H with size N r × N t . Therefore, we should solve an inverse of a N t × N t dimension matrix, and N r should at least be equal to N t to guarantee that H H H is of full rank.…”

Section: B Conventional Detection 1) ML Detector Schemesmentioning

confidence: 99%

“…However, this introduces the issue of multi-antenna interference, which needs to be mitigated at the receiver through a detection algorithm. Nevertheless, with appropriate detection techniques it is possible for a GSM system to achieve higher spectral efficiency and lower bit error rate than spatial multiplexing systems by utilizing only a fraction of the available RF chains [3], [4]. Based on the above, in this work, we explore the possibility of using deep neural networks (DNN) for signal detection in GSM.…”

Section: Introductionmentioning

confidence: 99%

Block Deep Neural Network-Based Signal Detector for Generalized Spatial Modulation

et al. 2020

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Generalized Spatial Modulation (GSM) is being considered for high capacity and energy-efficient networks of the future. However, signal detection due to inter channel interference among the active antennas is a challenge in GSM systems and is the focus of this letter. Specifically, we explore the feasibility of using deep neural networks (DNN) for signal detection in GSM. In particular, we propose a block DNN (B-DNN) based architecture, where the active antennas and their transmitted constellation symbols are detected by smaller sub-DNNs. After N-ordinary DNN detection, the Euclidean distance-based soft constellation algorithm is implemented. The proposed B-DNN detector achieves a BER performance that is superior to traditional block zero-forcing (B-ZF) and block minimum mean-squared error (B-MMSE) detection schemes and similar to that of classical maximum likelihood (ML) detector. Further, the proposed method requires less computation time and is more accurate than alternative conventional numerical methods.

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