Low-complexity lattice reduction algorithm for MIMO detectors with tree searching

Hyunsub Kim; Hyukyeon Lee; Jihye Koo; Jaeseok Kim

doi:10.1186/s13638-016-0756-4

Low-complexity lattice reduction algorithm for MIMO detectors with tree searching

Hyunsub Kim, Hyukyeon Lee, Jihye Koo, Jaeseok Kim

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

In this paper, we propose a low-complexity lattice reduction (LR) algorithm for multiple-input multiple-output (MIMO) detectors with tree searching. Whereas conventional approaches are based exclusively on channel characteristics, we focus on joint optimisation by employing an early termination criterion in the context of MIMO detection. In this regard, incremental LR (ILR) was previously proposed. However, the ILR is limited to LR-aided successive interference cancellation (SIC) detectors which have considerable bit-error-rate (BER) performance degradation compared to optimal detectors. Hence, in this paper, we extend the conventional ILR to be applicable to the LR-aided detectors with near-optimal performance. Furthermore, we perform the hypothetical analysis and several novel modifications to handle the obstacles for the application of the ILR to LR-aided detectors other than the LR-aided SIC detectors. The simulation results demonstrate that the computational complexity is considerably reduced, with BER performance degradation of 10⁻⁵.

Original language	English
Article number	17
Journal	Eurasip Journal on Wireless Communications and Networking
Volume	2017
Issue number	1
DOIs	https://doi.org/10.1186/s13638-016-0756-4
Publication status	Published - 2017 Dec 1

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (No. NRF-2015R1A2A2A01004883).

Publisher Copyright:
© 2016, The Author(s).

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Science Applications
Computer Networks and Communications

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10.1186/s13638-016-0756-4

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title = "Low-complexity lattice reduction algorithm for MIMO detectors with tree searching",

abstract = "In this paper, we propose a low-complexity lattice reduction (LR) algorithm for multiple-input multiple-output (MIMO) detectors with tree searching. Whereas conventional approaches are based exclusively on channel characteristics, we focus on joint optimisation by employing an early termination criterion in the context of MIMO detection. In this regard, incremental LR (ILR) was previously proposed. However, the ILR is limited to LR-aided successive interference cancellation (SIC) detectors which have considerable bit-error-rate (BER) performance degradation compared to optimal detectors. Hence, in this paper, we extend the conventional ILR to be applicable to the LR-aided detectors with near-optimal performance. Furthermore, we perform the hypothetical analysis and several novel modifications to handle the obstacles for the application of the ILR to LR-aided detectors other than the LR-aided SIC detectors. The simulation results demonstrate that the computational complexity is considerably reduced, with BER performance degradation of 10−5.",

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AU - Kim, Jaeseok

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N2 - In this paper, we propose a low-complexity lattice reduction (LR) algorithm for multiple-input multiple-output (MIMO) detectors with tree searching. Whereas conventional approaches are based exclusively on channel characteristics, we focus on joint optimisation by employing an early termination criterion in the context of MIMO detection. In this regard, incremental LR (ILR) was previously proposed. However, the ILR is limited to LR-aided successive interference cancellation (SIC) detectors which have considerable bit-error-rate (BER) performance degradation compared to optimal detectors. Hence, in this paper, we extend the conventional ILR to be applicable to the LR-aided detectors with near-optimal performance. Furthermore, we perform the hypothetical analysis and several novel modifications to handle the obstacles for the application of the ILR to LR-aided detectors other than the LR-aided SIC detectors. The simulation results demonstrate that the computational complexity is considerably reduced, with BER performance degradation of 10−5.

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Low-complexity lattice reduction algorithm for MIMO detectors with tree searching

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