Sparse Zero Correlation Zone Arrays for Training Design in Spatial Modulation Systems

This paper presents a novel training matrix design for spatial modulation (SM) systems, by introducing a new class of two-dimensional (2D) arrays called sparse zero correlation zone (SZCZ) arrays. An SZCZ array is characterized by a majority of zero entries and exhibits the zero periodic auto- and c...

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Published in:IEEE transactions on communications Vol. 73; no. 11; pp. 10277 - 10289
Main Authors: Pai, Cheng-Yu, Liu, Zilong, Chen, Chao-Yu
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Arrays
Boolean functions
Broadband antennas
Channel estimation
Channels
Controllability
Cross correlation
Delays
Interference
Kernel
Modulation
restricted extended generalized Boolean function (REGBF)
restricted generalized Boolean function (RGBF)
Selective fading
Simulation
Sparse matrices
Sparse zero correlation zone (SZCZ) arrays
spatial modulation (SM)
Training
training matrix design
Zero correlation zone
ISSN:0090-6778, 1558-0857
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Abstract This paper presents a novel training matrix design for spatial modulation (SM) systems, by introducing a new class of two-dimensional (2D) arrays called sparse zero correlation zone (SZCZ) arrays. An SZCZ array is characterized by a majority of zero entries and exhibits the zero periodic auto- and cross-correlation zone properties across any two rows. With these unique properties, we show that SZCZ arrays can be effectively used as training matrices for SM systems. Additionally, direct constructions of SZCZ arrays with large ZCZ widths and controllable sparsity levels based on 2D restricted extended generalized Boolean functions (REGBFs) are proposed. Compared with existing training schemes, the proposed SZCZ-based training matrices have larger ZCZ widths, thereby offering greater tolerance for delay spread in multipath channels. Simulation results demonstrate that the proposed SZCZ-based training design exhibits superior channel estimation performance over frequency-selective fading channels compared to existing alternatives.
AbstractList This paper presents a novel training matrix design for spatial modulation (SM) systems, by introducing a new class of two-dimensional (2D) arrays called sparse zero correlation zone (SZCZ) arrays. An SZCZ array is characterized by a majority of zero entries and exhibits the zero periodic auto- and cross-correlation zone properties across any two rows. With these unique properties, we show that SZCZ arrays can be effectively used as training matrices for SM systems. Additionally, direct constructions of SZCZ arrays with large ZCZ widths and controllable sparsity levels based on 2D restricted extended generalized Boolean functions (REGBFs) are proposed. Compared with existing training schemes, the proposed SZCZ-based training matrices have larger ZCZ widths, thereby offering greater tolerance for delay spread in multipath channels. Simulation results demonstrate that the proposed SZCZ-based training design exhibits superior channel estimation performance over frequency-selective fading channels compared to existing alternatives.
Author Pai, Cheng-Yu
Liu, Zilong
Chen, Chao-Yu
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SubjectTerms Arrays
Boolean functions
Broadband antennas
Channel estimation
Channels
Controllability
Cross correlation
Delays
Interference
Kernel
Modulation
restricted extended generalized Boolean function (REGBF)
restricted generalized Boolean function (RGBF)
Selective fading
Simulation
Sparse matrices
Sparse zero correlation zone (SZCZ) arrays
spatial modulation (SM)
Training
training matrix design
Zero correlation zone
Title Sparse Zero Correlation Zone Arrays for Training Design in Spatial Modulation Systems
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