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Relevant bibliographies by topics / Joint channel estimation and data detection

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Journal articles

Academic literature on the topic 'Joint channel estimation and data detection'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 January 2023

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Journal articles on the topic "Joint channel estimation and data detection"

1

Botsinis, Panagiotis, Dimitrios Alanis, Zunaira Babar, Soon Xin Ng, and Lajos Hanzo. "Joint Quantum-Assisted Channel Estimation and Data Detection." IEEE Access 4 (2016): 7658–81. http://dx.doi.org/10.1109/access.2016.2591903.

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2

Patil, Gajanan R., and Vishwanath K. Kokate. "Joint Channel Estimation and Data Detection for STBC MIMO-OFDM Wireless Communication System." Journal of Circuits, Systems and Computers 24, no. 04 (2015): 1550059. http://dx.doi.org/10.1142/s0218126615500590.

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This paper presents a joint channel estimation and data detection technique for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Initial estimate of the channel is obtained using semi-blind channel estimation (SBCE). The whitening rotation (WR)-based orthogonal pilot maximum likelihood (OPML) method is used to obtain the channel estimate. The estimate is further enhanced by extracting information through the received data symbols. The performance of the proposed estimator is studied under various channel models. The simulation study shows that thi

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3

Longoria-Gandara, Omar, Ramon Parra-Michel, Roberto Carrasco-Alvarez, and Eduardo Romero-Aguirre. "Iterative MIMO Detection and Channel Estimation Using Joint Superimposed and Pilot-Aided Training." Mobile Information Systems 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/3723862.

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This paper presents a novel iterative detection and channel estimation scheme that combines the effort of superimposed training (ST) and pilot-aided training (PAT) for multiple-input multiple-output (MIMO) flat fading channels. The proposed method, hereafter known as joint mean removal ST and PAT (MRST-PAT), implements an iterative detection and channel estimation that achieves the performance of data-dependent ST (DDST) algorithm, with the difference that the data arithmetic cyclic mean is estimated and removed from data at the receiver’s end. It is demonstrated that this iterative and cooper

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4

Tao Cui and C. Tellambura. "Joint data detection and channel estimation for OFDM systems." IEEE Transactions on Communications 54, no. 4 (2006): 670–79. http://dx.doi.org/10.1109/tcomm.2006.873075.

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5

Omidi, M. J., P. G. Gulak, and S. Pasupathy. "Parallel structures for joint channel estimation and data detection over fading channels." IEEE Journal on Selected Areas in Communications 16, no. 9 (1998): 1616–29. http://dx.doi.org/10.1109/49.737631.

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6

Cozzo, C., and B. L. Hughes. "Joint channel estimation and data detection in space-time communications." IEEE Transactions on Communications 51, no. 8 (2003): 1266–70. http://dx.doi.org/10.1109/tcomm.2003.815062.

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7

Jiang, Zhe, Xiaohong Shen, Haiyan Wang, and Zhi Ding. "Joint PSK Data Detection and Channel Estimation Under Frequency Selective Sparse Multipath Channels." IEEE Transactions on Communications 68, no. 5 (2020): 2726–39. http://dx.doi.org/10.1109/tcomm.2020.2975172.

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8

Yang, Ruo-Nan, Wei-Tao Zhang, and Shun-Tian Lou. "Joint Adaptive Blind Channel Estimation and Data Detection for MIMO-OFDM Systems." Wireless Communications and Mobile Computing 2020 (July 2, 2020): 1–9. http://dx.doi.org/10.1155/2020/2508130.

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In order to track a changing channel in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems, it is a priority to estimate channel impulse response adaptively. In this paper, we propose an adaptive blind channel estimation method based on parallel factor analysis (PARAFAC). We used an exponential window to weigh the past observations; thus, the cost function can be constructed via a weighted least squares criterion. The minimization of the cost function is equivalent to the decomposition of a third-order tensor, which consists of the weighted OFDM data

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9

Mohammadian, Amirhossein, and Chintha Tellambura. "Joint Channel and Phase Noise Estimation and Data Detection for GFDM." IEEE Open Journal of the Communications Society 2 (2021): 915–33. http://dx.doi.org/10.1109/ojcoms.2021.3073348.

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10

Sharma, Sanjay, Sanjay Attri, and R. C. Chauhan. "Joint channel estimation and data detection under fading on reconfigurable fabric." Integration 37, no. 3 (2004): 177–89. http://dx.doi.org/10.1016/j.vlsi.2004.01.006.

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