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Low-Complexity Subcarrier-Wise Detection for MIMO-OFDM With Index Modulation

Authors: Zeng Hu; Shaoe Lin; Beixiong Zheng; Fangjiong Chen; Qingyang Wang; Yao Wei;

Low-Complexity Subcarrier-Wise Detection for MIMO-OFDM With Index Modulation

Abstract

Multiple-input multiple-output orthogonal frequency division multiplexing with index modulation (MIMO-OFDM-IM) is a relatively new multicarrier transmission technique for the MIMO systems to achieve both energy and spectral efficiency. However, due to the dependence of subcarrier symbols introduced by the index modulation, existing MIMO detection techniques cannot be applied in MIMO-OFDM-IM as it will lead to erroneous detection on index information of the active subcarriers and further deteriorate the system performance. In this paper, we first develop an optimal detection algorithm with reduced complexity for MIMO-OFDM-IM by performing the subcarrier-wise detection under the constraint on the legal subcarrier combination within each OFDM-IM subblock. To further reduce the computational complexity, we then propose a low-complexity subcarrier-wise algorithm based on the deterministic sequential Monte Carlo technique to achieve near-optimal detection for MIMO-OFDM-IM. Specifically, the near-optimal detector applies the QR decomposition to generate an upper triangular structure and draw antenna-wise samples at the subcarrier level. Computational simulations and complexity analysis show that the proposed algorithms provide similar performance to optimal one with reduced computational complexity.

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Keywords

OFDM with index modulation (OFDM-IM), multiple-input multiple-output (MIMO), Electrical engineering. Electronics. Nuclear engineering, sequential Monte Carlo (SMC), maximum <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">a posteriori</italic> (MAP), TK1-9971

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
gold