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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.17483 |
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| _version_ | 1866914050524315648 |
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| author | Li, Qianqian Li, Lintao Liu, Lixiang Yang, Lei Gong, Caihong Li, Hua Hao, Shiya Dai, Xiaoming |
| author_facet | Li, Qianqian Li, Lintao Liu, Lixiang Yang, Lei Gong, Caihong Li, Hua Hao, Shiya Dai, Xiaoming |
| contents | This paper investigates the design of the capacity-achieving input distribution for the discrete-time Poisson channel (DTPC) under dark current effects with low-precision analog-to-digital converters (ADCs). This study introduces an efficient optimization algorithm that integrates the Newton-Raphson and Blahut-Arimoto (BA) methods to determine the capacity-achieving input distribution and the corresponding amplitudes of input mass points for the DTPC, subject to both peak and average power constraints. Additionally, the Karush-Kuhn-Tucker (KKT) conditions are established to provide necessary and sufficient conditions for the optimality of the obtained capacity-achieving distribution. Simulation results illustrate that the proposed algorithm attains $72\%$ and $83\%$ of the theoretical capacity at 5 dB for 1-bit and 2-bit quantized DTPC, respectively. Furthermore, for a finite-precision quantized DTPC (i.e., ${\log _2}K$ bits), the capacity can be achieved by a non-uniform discrete input distribution with support for $K$ mass points, under the given power constraints. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_17483 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On the Design of Capacity-Achieving Distributions for Discrete-Time Poisson Channel with Low-Precision ADCs Li, Qianqian Li, Lintao Liu, Lixiang Yang, Lei Gong, Caihong Li, Hua Hao, Shiya Dai, Xiaoming Signal Processing Performance This paper investigates the design of the capacity-achieving input distribution for the discrete-time Poisson channel (DTPC) under dark current effects with low-precision analog-to-digital converters (ADCs). This study introduces an efficient optimization algorithm that integrates the Newton-Raphson and Blahut-Arimoto (BA) methods to determine the capacity-achieving input distribution and the corresponding amplitudes of input mass points for the DTPC, subject to both peak and average power constraints. Additionally, the Karush-Kuhn-Tucker (KKT) conditions are established to provide necessary and sufficient conditions for the optimality of the obtained capacity-achieving distribution. Simulation results illustrate that the proposed algorithm attains $72\%$ and $83\%$ of the theoretical capacity at 5 dB for 1-bit and 2-bit quantized DTPC, respectively. Furthermore, for a finite-precision quantized DTPC (i.e., ${\log _2}K$ bits), the capacity can be achieved by a non-uniform discrete input distribution with support for $K$ mass points, under the given power constraints. |
| title | On the Design of Capacity-Achieving Distributions for Discrete-Time Poisson Channel with Low-Precision ADCs |
| topic | Signal Processing Performance |
| url | https://arxiv.org/abs/2509.17483 |