Machine Learning for Model Order Selection in MIMO OFDM Systems

Autor:	Boas, Brenda Vilas, Zirwas, Wolfgang, Haardt, Martin
Rok vydání:	2021
Předmět:	Electrical Engineering and Systems Science - Signal Processing Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	A variety of wireless channel estimation methods, e.g., MUSIC and ESPRIT, rely on prior knowledge of the model order. Therefore, it is important to correctly estimate the number of multipath components (MPCs) which compose such channels. However, environments with many scatterers may generate MPCs which are closely spaced. This clustering of MPCs in addition to noise makes the model order selection task difficult in practice to currently known algorithms. In this paper, we exploit the multidimensional characteristics of MIMO orthogonal frequency division multiplexing (OFDM) systems and propose a machine learning (ML) method capable of determining the number of MPCs with a higher accuracy than state of the art methods in almost coherent scenarios. Moreover, our results show that our proposed ML method has an enhanced reliability. Comment: to be published
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2106.11633 Zobrazit plný text záznamu View this record from Arxiv