Previously, dynamic-assignment Blahut-Arimoto (DAB) was used to find capacity-achieving probability mass functions (PMFs) for binomial channels and molecular channels. As it turns out, DAB can efficiently identify capacity-achieving PMFs for a wide variety of channels. This paper applies DAB to power-constrained (PC) additive white Gaussian Noise (AWGN) Channels and amplitude-constrained (AC) AWGN Channels.This paper modifies DAB to include a power constraint and finds low-cardinality PMFs that approach capacity on PC-AWGN Channels. While a continuous Gaussian PDF is well-known to be capacity-achieving on the PC-AWGN channel, DAB identifies low-cardinality PMFs within 0.01 bits of the mutual information provided by a Gaussian PDF. Recall the results of Ozarow and Wyner requiring a constellation cardinality of ⌈2 ^ (C+1) ⌉ to approach capacity C to within the asymptotic shaping loss of 1.53 dB at high SNR. PMF's found by DAB approach capacity with essentially no shaping loss with cardinality less than 2 ^ (C+1.2) . As expected, DAB's numerical approach identifies PMFs with better mutual information vs. SNR performance than the analytical approaches to finite-support constellations examined by Wu and Verdu. This paper also uses DAB to find capacity-achieving PMFs with small cardinality support sets for AC-AWGN Channels. The resulting evolution of capacity-achievingmore »
This content will become publicly available on October 30, 2023
Optimizing Write Voltages for Independent, Equal-Rate Pages in Flash Memory
This paper uses a mutual-information maximization paradigm to optimize the voltage levels written to cells in a Flash memory. To enable low-latency, each page of Flash memory stores only one coded bit in each Flash memory cell. For example, three-level cell (TL) Flash has three bit channels, one for each of three pages, that together determine which of eight voltage levels are written to each cell. Each Flash page is required to store the same number of data bits, but the various bits stored in the cell typically do not have to provide the same mutual information. A modified version of dynamic-assignment Blahut- Arimoto (DAB) moves the constellation points and adjusts the probability mass function for each bit channel to increase the mutual information of a worst bit channel with the goal of each bit channel providing the same mutual information. The resulting constellation provides essentially the same mutual information to each page while negligibly reducing the mutual information of the overall constellation. The optimized constellations feature points that are neither equally spaced nor equally likely. However, mod- ern shaping techniques such as probabilistic amplitude shaping can provide coded modulations that support such constellations.
- Award ID(s):
- 1911166
- Publication Date:
- NSF-PAR ID:
- 10398493
- Journal Name:
- 2022 56th Asilomar Conference on Signals, Systems, and Computers
- Sponsoring Org:
- National Science Foundation
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