Binary Sequence Set Optimization for CDMA Applications via Mixed-Integer Quadratic Programming

Yang, Alan Hao; Mina, Tara; Gao, Grace Xingxin

doi:10.1109/icassp49357.2023.10095359

Cited by 4 publications

(7 citation statements)

References 22 publications

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“…Coordinate descent and BCD methods have been proposed to optimize sets of binary sequences for multiple-input multiple-output (MIMO) radar systems [15,[26][27][28][29]. Like the spreading codes for navigation systems, the binary sequences used in those applications are required to have low auto-and cross-correlation.…”

Section: Related Workmentioning

confidence: 99%

“…However, the aforementioned works only optimize over either a single binary variable at a time, or a small number (e.g., four), using an exhaustive search. In contrast, by using branchand-bound to perform the BCD updates [15,16,30], we can efficiently optimize over large blocks of binary variables, e.g., 25, during each BCD iteration. This approach is particularly effective for designing LEO satellite spreading codes due to the relatively small code lengths and large family sizes.…”

Section: Related Workmentioning

confidence: 99%

“…In Sect. 2.3, we discuss how the problem may be reformulated as a MICP and how the resulting convex structure may be exploited [15,16].…”

Section: Spreading Code Optimization Problemmentioning

confidence: 99%

“…Our method is based on the recently proposed mixed-integer convex program (MICP) approach to spreading code optimization [14][15][16], which has shown promising results for optimizing spreading codes for MEO applications. In that approach, the spreading code optimization problem is formulated as a mixed-integer convex program (MICP).…”

mentioning

confidence: 99%

“…Unlike the prior works [15,16], we focus on the LEO setting, where the number of codes is relatively large. In this regime, the choice of the subset of binary variables to optimize over in each iteration of BCD is an important consideration.…”

mentioning

confidence: 99%

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Spreading code optimization for low-earth orbit satellites via mixed-integer convex programming

Yang,

Mina,

Gao

2024

EURASIP J. Adv. Signal Process.

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Optimizing the correlation properties of spreading codes is critical for minimizing inter-channel interference in satellite navigation systems. By improving the codes’ correlation sidelobes, we can enhance navigation performance while minimizing the required spreading code lengths. In the case of low-earth orbit (LEO) satellite navigation, shorter code lengths (on the order of a hundred) are preferred due to their ability to achieve fast signal acquisition. Additionally, the relatively high signal-to-noise ratio in LEO systems reduces the need for longer spreading codes to mitigate inter-channel interference. In this work, we propose a two-stage block coordinate descent (BCD) method which optimizes the codes’ correlation properties while enforcing the autocorrelation sidelobe zero property. In each iteration of the BCD method, we solve a mixed-integer convex program over a block of 25 binary variables. Our method is applicable to spreading code families of arbitrary sizes and lengths, and we demonstrate its effectiveness for a problem with 66 length-127 codes and a problem with 130 length-257 codes.

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