Dynamic Threshold Detection Using Clustering in the Presence of Channel Mismatch and Additive Noise
Kees A. Immink, Kui Cai
IEEE Access · 2020
doi:10.1109/access.2020.2968945 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
We report on the feasibility of k-means clustering techniques for the dynamic threshold detection of encoded q-ary symbols transmitted over a noisy channel with partially unknown channel parameters. We first assess the performance of k-means clustering technique without dedicated constrained coding. We apply constrained codes which allows a wider range of channel uncertainties so improving the detection reliability.
Abstract licence: CC BY-NC-ND
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.