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Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems

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Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majitar 737136, Sikkim, India
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Department of Electrical and Electronics Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majitar 737136, Sikkim, India
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Department of Electrical Engineering, Muffakham Jah College of Engineering and Technology, Hyderabad 500034, India
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Instituto de Telecomunicações, Universidade da Beira Interior, 6201-001 Covilhã, Portugal
*
Author to whom correspondence should be addressed.
Information 2020, 11(6), 301; https://doi.org/10.3390/info11060301
Received: 29 April 2020 / Revised: 25 May 2020 / Accepted: 30 May 2020 / Published: 4 June 2020
(This article belongs to the Special Issue 5G and Wireless Networks Communications)
Massive multi-input-multi-output (MIMO) systems are the future of the communication system. The proper design of the MIMO system needs an appropriate choice of detection algorithms. At the same time, Lattice reduction (LR)-aided equalizers have been well investigated for MIMO systems. Many studies have been carried out over the Korkine–Zolotareff (KZ) and Lenstra–Lenstra–Lovász (LLL) algorithms. This paper presents an analysis of the channel capacity of the massive MIMO system. The mathematical calculations included in this paper correspond to the channel correlation effect on the channel capacity. Besides, the achievable gain over the linear receiver is also highlighted. In this study, all the calculations were further verified through the simulated results. The simulated results show the performance comparison between zero forcing (ZF), minimum mean squared error (MMSE), integer forcing (IF) receivers with log-likelihood ratio (LLR)-ZF, LLR-MMSE, KZ-ZF, and KZ-MMSE. The main objective of this work is to show that, when a lattice reduction algorithm is combined with the convention linear MIMO receiver, it improves the capacity tremendously. The same is proven here, as the KZ-MMSE receiver outperforms its counterparts in a significant margin. View Full-Text
Keywords: MIMO; ZF; MMSE; LLR-ZF; LLR-MMSE; KZ-ZF; KZ-MMSE; capacity MIMO; ZF; MMSE; LLR-ZF; LLR-MMSE; KZ-ZF; KZ-MMSE; capacity
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MDPI and ACS Style

Sur, S.N.; Bera, R.; Kumar Bhoi, A.; Shaik, M.; Marques, G. Capacity Analysis of Lattice Reduction Aided Equalizers for Massive MIMO Systems. Information 2020, 11, 301.

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