Information-Theoretic Analysis of OFDM With Subcarrier Number Modulation

With the prevalence of orthogonal frequency-division multiplexing (OFDM) in many standards, e.g., IEEE 802.11, IEEE 802.16, DVB-T, and DVB-T2, a number of variant modulation schemes based on OFDM have been proposed, which resort to signal sparsity to further enhance spectral efficiency and mitigate...

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Bibliographic Details
Published in:IEEE transactions on information theory 2021-11, Vol.67 (11), p.7338-7354
Main Authors: Dang, Shuping, Guo, Shuaishuai, Shihada, Basem, Alouini, Mohamed-Slim
Format: Article
Language:English
Subjects:
Channel capacity
channel-dependent coding
Coding
Communications systems
Constellations
Decoding
Huffman codes
Huffman coding
Information theory
information-theoretic analysis
Iterative algorithms
Iterative methods
Modulation
Mutual information
OFDM
Orthogonal Frequency Division Multiplexing
Orthogonal frequency-division multiplexing (OFDM)
Pattern analysis
Peak to average power ratio
subcarrier number modulation (SNM)
Subcarriers
Transmitters
Upper bounds
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Summary:With the prevalence of orthogonal frequency-division multiplexing (OFDM) in many standards, e.g., IEEE 802.11, IEEE 802.16, DVB-T, and DVB-T2, a number of variant modulation schemes based on OFDM have been proposed, which resort to signal sparsity to further enhance spectral efficiency and mitigate the high peak-to-average ratio (PAPR) problem. Among these variants, OFDM with subcarrier number modulation (OFDM-SNM) has been proven to be efficient for simple communication systems with low constellation modulation orders and limited decoding capability. To rigorously verify the performance advantages of OFDM-SNM, we present the study of OFDM-SNM in this paper from the information-theoretic perspective. In particular, we determine an upper bound on the mutual information of OFDM-SNM in closed form by using the log sum inequality. Also, we analyze the optimal pattern utilization probabilities (PUPs) for OFDM-SNM by channel-dependent coding and propose an easy-to-implement iterative algorithm to approach the optimal PUPs. Moreover, considering the practical achievability, we propose a Huffman coding based achievable PUP vector construction scheme to obtain the achievable PUPs and the corresponding achievable rate. We carry out numerical simulations to verify the effectiveness of this study and illustrate the efficiency of the obtained PUPs in comparison with several benchmarks.
ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2021.3111036