Impact of CSI Uncertainty on MCIK-OFDM: Tight Closed-Form Symbol Error Probability Analysis

This paper proposes a novel framework to analyze the symbol error probability (SEP) for multicarrier index keying orthogonal frequency-division multiplexing (MCIK-OFDM) systems. Considering two different types of detections such as the maximum likelihood (ML) and low-complexity greedy detectors (GD)...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on vehicular technology 2018-02, Vol.67 (2), p.1272-1279
Main Authors: Van Luong, Thien, Ko, Youngwook
Format: Article
Language:English
Subjects:
Closed form solutions
Codes
Complexity theory
Detectors
Error analysis
Error probability
Exact solutions
Frequency division multiplexing
Greedy detection
imperfect CSI
index modulation
Indexes
Keying
Mathematical analysis
MICK-OFDM
Modulation
OFDM
OFDM-IM
Orthogonal Frequency Division Multiplexing
symbol error probability
Uncertainty
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposes a novel framework to analyze the symbol error probability (SEP) for multicarrier index keying orthogonal frequency-division multiplexing (MCIK-OFDM) systems. Considering two different types of detections such as the maximum likelihood (ML) and low-complexity greedy detectors (GD), we derive tight closed-form expressions for the average SEPs of MCIK-OFDM in the presence of channel state information (CSI) uncertainty. We undertake an asymptotic performance analysis with respect to three CSI conditions, which ensures to provide a comprehensive insight into the achievable diversity and coding gains as well as the impact of various CSI uncertainties on the SEP performance. The SEP performance comparison between the ML and GD is obtained under different CSI uncertainties. This interestingly reveals that the GD can achieve nearly optimal error performance as the M-ary modulation size is large or even outperforms the ML under certain CSI conditions. Finally, the theoretical and asymptotic analysis are verified via simulation results, obtaining the high accuracy of the derived SEP.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2017.2753402