Moment Converging Enabled Parametric Mapping for Channel Model Substitution
Channel model substitution (CMS) is an analytical technique aiming to replace a computationally complex channel model with a simpler substitute. The utility of CMS is affected by the parametric relations between the original channel model and its substitute. In this letter, we propose a moment converging criterion to enable parametric mapping for a general CMS problem. Instead of solving an equation system to yield the analytical solutions by moment matching, we formulate and minimize the moment mean squared error (MMSE) between the original channel model and its substitute to obtain parametric mapping relations. The moment converging enabled parametric mapping approach offers a surrogate way to enable parametric mapping for CMS, which is, in particular, helpful when the moment matching equation system is too cumbersome to solve and/or has no feasible solution. Taking three CMS applications as examples, the effectiveness and efficiency of the moment converging enabled parametric mapping for CMS are verified.
Authors
- Rong Yang (ORCID: https://orcid.org/0000-0002-6983-4682)
- Shuping Dang (ORCID: https://orcid.org/0000-0002-0018-815X)
- Peng Wang (ORCID: https://orcid.org/0000-0002-2736-0300)
- Jia Ye (ORCID: https://orcid.org/0000-0002-7242-6065)
Institutions
- Chongqing University (CN)
- University of Bristol (GB)
Publication Details
- Journal
- IEEE Communications Letters
- Published
- 2024-08-29
- DOI
- https://doi.org/10.1109/lcomm.2024.3451510
- Citations
- 3
- Primary Topic
- Advanced Numerical Methods in Computational Mathematics
- Type
- article
- Field-Weighted Citation Impact
- 1.12
Funders
- National Natural Science Foundation of China