Various applications of molecular communications (MC) are event-triggered, and, as a consequence, the prevalent Shannon capacity may not be the right measure for performance assessment. Thus, in this paper, we motivate and establish the identification capacity as an alternative metric. In particular, we study deterministic identification (DI) for the discrete-time Poisson channel (DTPC), subject to an average and a peak power constraint, which serves as a model for MC systems employing molecule counting receivers. It is established that the codebook size for this channel scales as $2^{(n\log n)R}$, where $n$ and $R$ are the codeword length and coding rate, respectively. Lower and upper bounds on the DI capacity of the DTPC are developed. The obtained large capacity of the DI channel sheds light on the performance of natural DI systems such as natural olfaction, which are known for their extremely large chemical discriminatory power in biology. Furthermore, numerical simulations for the empirical miss-identification and false identification error rates are provided for finite length codes. This allows us to quantify the scale of error reduction in terms of the codeword length.
Deterministic Identification over Additive Gaussian Channels
Technical University of Munich(慕尼黑工业大学);BMFTR Research Hub 6G-life(德国巴伐利亚未来基金会技术研究中心 6G-life);Munich Center for Quantum Science and Technology (MCQST)(慕尼黑量子科学与技术中心);Munich Quantum Valley (MQV)(慕尼黑量子谷)
Commitment over Gaussian channels with deterministic identification codes
Technische Universität München(慕尼黑工业大学);Technische Universität Braunschweig(布伦瑞克工业大学);BMFTR Research Hub 6G-life(6G-life研究枢纽);Technische Universität Dresden(德累斯顿工业大学);Munich Quantum Valley(慕尼黑量子谷);Munich Center for Quantum Science and Technology(慕尼黑量子科学与工程中心);Universität zu Köln(科隆大学);ICREA(加泰罗尼亚高级研究院)
Reliability-Dependent Scaling Laws of Deterministic Identification over Binary Symmetric Channels
School of Mathematics, Sichuan University(四川大学数学学院);Academy of Mathematics and Systems Science, University of Chinese Academy and Sciences(中国科学院数学与系统科学研究院,中国科学院大学)