Increasing Capacity of Multi-cell Cooperative Cellular Networks with Coprime Deployment

Liang, Hao; Liang, Qilian

doi:10.1007/978-981-10-3229-5_29

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…An extended Sparse Convolutional Array (3,3) as shown in Fig. 2 and a Sparse Convolutional Array (3,5) are constructed so that the total number of the physical sensors are identical. As a comparison, a nested array is performed, as illustrated in [4].…”

Section: Sparse Convolutional Arraymentioning

confidence: 99%

Sparse convolutional array for DOA estimation

Wang

Liu

Song

et al. 2022

EURASIP J. Adv. Signal Process.

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Array signal processing plays an important role in many areas. Besides the Uniform Linear Array, there are many sparse array that have been proposed, for example, Minimum-redundancy array, Co-prime array, nested array, etc. However, most of the array structures have certain disadvantages. A new type of nonlinear sparse sensor array called sparse convolutional array is illustrated which can reduce the number of physical sensors while remain a decent performance in DOA estimation. The sparse convolutional array contains three groups of physical sensors and is able to form a hole-free difference co-array. By adding sensors on two sides instead of the center, the proposed array shows improved performance compared to some other approaches while reminds few physical sensors. The array geometrical structure is illustrated, and the numerical result is provided. We also extended this array structure to two-dimensional case, and the performance is illustrated.

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Section: Sparse Convolutional Arraymentioning

confidence: 99%

Sparse convolutional array for DOA estimation

Wang

Liu

Song

et al. 2022

EURASIP J. Adv. Signal Process.

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show abstract

“…Nested array is then been widely studied. In [6], nested array is applied to increase the capacity of multi-cell cooperative cellular networks. In [7], the authors studied nested and co-prime based underwater nonuniform sensor array networks (UWSANs) for underwater DOA estimation.…”

Section: Introductionmentioning

confidence: 99%

Sparse Convolutional Array for DOA Estimation

Wang

Liu

Song

et al. 2022

Preprint

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Array signal processing plays an important role in many areas. Besides the Uniform Linear Array, their are many sparse array that have been proposed, for example, Minimum-redundancy array, Co-prime array, nested array, etc. However, most of the array structures have certain disadvantages. A new type of non-linear sparse sensor array called sparse convolutional array is illustrated which can reduce the number of physical sensors while remain a decent performance in DOA estimation. The sparse convolutional array contains three groups of physical sensors and is able to form a hole-free difference co-array. By adding sensors on two sides instead of the center, the proposed array shows improved performance compares to some other approaches while reminds few physical sensors. The array geometrical structure is illustrated and the numerical result is provided. We also extended this array structure to two-dimension case and the performance is illustrated.

show abstract

Increasing Capacity of Multi-cell Cooperative Cellular Networks with Coprime Deployment

Cited by 2 publications

References 5 publications

Sparse convolutional array for DOA estimation

Sparse convolutional array for DOA estimation

Sparse Convolutional Array for DOA Estimation

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