Compressed Sensing for Feedback Generation in OFDM Based LiFi Systems
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
In this paper, we evaluate the effectiveness of compressed-sensing-based channel estimation in LiFi orthogonal frequency-division multiplex (OFDM) systems with multiple-input multiple-output (MIMO). The sparseness of LiFi channels suggests that it is beneficial to utilize compressed sensing which has been investigated also for radio communications. In this paper, we formulate the mathematical problem of compressed-sensing for feedback generation in OFDM-based LiFi systems. We use well-known algorithms for both, sparse pilot design and sparse recovery and apply them to LiFi OFDM channels. We evaluate the effectiveness of these algorithms by measuring the achievable mean squared error (MSE) and vary the total numbers of subcarriers as well as the number of pilot subcarriers.
Details
| Original language | English |
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| Title of host publication | 2023 IEEE Wireless Communications and Networking Conference, WCNC 2023 - Proceedings |
| Number of pages | 6 |
| ISBN (electronic) | 978-1-6654-9122-8 |
| Publication status | Published - 2023 |
| Peer-reviewed | Yes |
External IDs
| Scopus | 85159789189 |
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Keywords
ASJC Scopus subject areas
Keywords
- LiFi, MIMO, OFDM, channel estimation, compressed sensing