Vol. 12, No. 7, July 30, 2018
10.3837/tiis.2018.07.003,
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Abstract
Massive (large-scale) MIMO (multiple-input multiple-output) is one of the key technologies in next-generation wireless communication systems. This paper proposes a high-performance low-complexity turbo receiver for SC-FDMA (single-carrier frequency-division multiple access) based MMIMO (massive MIMO) systems. Because SC-FDMA technology has the desirable characteristics of OFDMA (orthogonal frequency division multiple access) and the low PAPR (peak-to-average power ratio) of SC transmission schemes, the 3GPP LTE (long-term evolution) has adopted it as the uplink transmission to meet the demand high data rate and low error rate performance. The complexity of computing will be increased greatly in base station with massive MIMO (MMIMO) system. In this paper, a low-complexity adaptive turbo equalization receiver based on normalized minimal symbol-error-rate for MMIMO SC-FDMA system is proposed. The proposed receiver is with low complexity than that of the conventional turbo MMSE (minimum mean square error) equalizer and is also with better bit error rate (BER) performance than that of the conventional adaptive turbo MMSE equalizer. Simulation results confirm the effectiveness of the proposed scheme.
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Cite this article
[IEEE Style]
Y. Chang, F. Ueng, B. Tsai, "A Novel Adaptive Turbo Receiver for Large-Scale MIMO Communications," KSII Transactions on Internet and Information Systems, vol. 12, no. 7, pp. 2998-3017, 2018. DOI: 10.3837/tiis.2018.07.003.
[ACM Style]
Yu-Kuan Chang, Fang-Biau Ueng, and Bo-Yi Tsai. 2018. A Novel Adaptive Turbo Receiver for Large-Scale MIMO Communications. KSII Transactions on Internet and Information Systems, 12, 7, (2018), 2998-3017. DOI: 10.3837/tiis.2018.07.003.
[BibTeX Style]
@article{tiis:21804, title="A Novel Adaptive Turbo Receiver for Large-Scale MIMO Communications", author="Yu-Kuan Chang and Fang-Biau Ueng and Bo-Yi Tsai and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2018.07.003}, volume={12}, number={7}, year="2018", month={July}, pages={2998-3017}}