Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/660290
Title: Joint Quantum-Assisted Channel Estimation and Data Detection
Authors: Panagiotis Botsinis;Dimitrios Alanis;Zunaira Babar;Soon Xin Ng;Lajos Hanzo
subject: quantum computing|orthogonal frequency division multiplexing|repeated weighted boosting search|Dürr-Høyer algorithm|Grover’s quantum search algorithm|Channel estimation|multiuser detection|computational complexity|prediction filter
Year: 2016
Publisher: IEEE
Abstract: Joint channel estimation (CE) and multi-user detection (MUD) have become a crucial part of iterative receivers. In this paper, we propose a quantum-assisted repeated weighted boosting search (QRWBS) algorithm for CE and we employ it in the uplink of multiple-input multiple-output orthogonal frequency division multiplexing systems, in conjunction with the maximum a posteriori probability (MAP) MUD and a near-optimal quantum-assisted MUD (QMUD). The performance of the QRWBS-aided CE is evaluated in rank-deficient systems, where the number of receive antenna elements (AEs) at the base station (BS) is lower than the number of supported users. The effect of the channel impulse response prediction filters, of the power delay profile of the channels, and of the Doppler frequency on the attainable system performance is also quantified. The proposed QRWBS-aided CE is shown to outperform the RWBS-aided CE, despite requiring a lower complexity, in systems where iterations are invoked between the MUD, the CE, and the channel decoders at the receiver. In a system, where U = 7 users are supported with the aid of P = 4 receive AEs, the joint QRWBS-aided CE and QMUD achieves a 2-dB gain, when compared with the joint RWBS-aided CE and MAP MUD, despite imposing 43% lower complexity.
Description: 
URI: http://localhost/handle/Hannan/146853
http://localhost/handle/Hannan/660290
ISSN: 2169-3536
volume: 4
Appears in Collections:2016

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Title: Joint Quantum-Assisted Channel Estimation and Data Detection
Authors: Panagiotis Botsinis;Dimitrios Alanis;Zunaira Babar;Soon Xin Ng;Lajos Hanzo
subject: quantum computing|orthogonal frequency division multiplexing|repeated weighted boosting search|Dürr-Høyer algorithm|Grover’s quantum search algorithm|Channel estimation|multiuser detection|computational complexity|prediction filter
Year: 2016
Publisher: IEEE
Abstract: Joint channel estimation (CE) and multi-user detection (MUD) have become a crucial part of iterative receivers. In this paper, we propose a quantum-assisted repeated weighted boosting search (QRWBS) algorithm for CE and we employ it in the uplink of multiple-input multiple-output orthogonal frequency division multiplexing systems, in conjunction with the maximum a posteriori probability (MAP) MUD and a near-optimal quantum-assisted MUD (QMUD). The performance of the QRWBS-aided CE is evaluated in rank-deficient systems, where the number of receive antenna elements (AEs) at the base station (BS) is lower than the number of supported users. The effect of the channel impulse response prediction filters, of the power delay profile of the channels, and of the Doppler frequency on the attainable system performance is also quantified. The proposed QRWBS-aided CE is shown to outperform the RWBS-aided CE, despite requiring a lower complexity, in systems where iterations are invoked between the MUD, the CE, and the channel decoders at the receiver. In a system, where U = 7 users are supported with the aid of P = 4 receive AEs, the joint QRWBS-aided CE and QMUD achieves a 2-dB gain, when compared with the joint RWBS-aided CE and MAP MUD, despite imposing 43% lower complexity.
Description: 
URI: http://localhost/handle/Hannan/146853
http://localhost/handle/Hannan/660290
ISSN: 2169-3536
volume: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7515148.pdf17.34 MBAdobe PDFThumbnail
Preview File
Title: Joint Quantum-Assisted Channel Estimation and Data Detection
Authors: Panagiotis Botsinis;Dimitrios Alanis;Zunaira Babar;Soon Xin Ng;Lajos Hanzo
subject: quantum computing|orthogonal frequency division multiplexing|repeated weighted boosting search|Dürr-Høyer algorithm|Grover’s quantum search algorithm|Channel estimation|multiuser detection|computational complexity|prediction filter
Year: 2016
Publisher: IEEE
Abstract: Joint channel estimation (CE) and multi-user detection (MUD) have become a crucial part of iterative receivers. In this paper, we propose a quantum-assisted repeated weighted boosting search (QRWBS) algorithm for CE and we employ it in the uplink of multiple-input multiple-output orthogonal frequency division multiplexing systems, in conjunction with the maximum a posteriori probability (MAP) MUD and a near-optimal quantum-assisted MUD (QMUD). The performance of the QRWBS-aided CE is evaluated in rank-deficient systems, where the number of receive antenna elements (AEs) at the base station (BS) is lower than the number of supported users. The effect of the channel impulse response prediction filters, of the power delay profile of the channels, and of the Doppler frequency on the attainable system performance is also quantified. The proposed QRWBS-aided CE is shown to outperform the RWBS-aided CE, despite requiring a lower complexity, in systems where iterations are invoked between the MUD, the CE, and the channel decoders at the receiver. In a system, where U = 7 users are supported with the aid of P = 4 receive AEs, the joint QRWBS-aided CE and QMUD achieves a 2-dB gain, when compared with the joint RWBS-aided CE and MAP MUD, despite imposing 43% lower complexity.
Description: 
URI: http://localhost/handle/Hannan/146853
http://localhost/handle/Hannan/660290
ISSN: 2169-3536
volume: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7515148.pdf17.34 MBAdobe PDFThumbnail
Preview File