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Sum-MSE Gain of DFT-Based Channel Estimator Over Frequency-Domain LS One in Full-Duplex OFDM Systems
- Source :
- IEEE Systems Journal. 13:1231-1240
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- In this paper, we make an investigation on the sum-mean-square-error (Sum-MSE) performance gain in full-duplex orthogonal frequency-division multiplexing (OFDM) systems in the presence of colored interference-plus-noise (IPN). This gain is defined as the ratio of Sum-MSE of frequency-domain least-square (LS) channel estimator to that of DFT-based LS one. The closed-form formula of the gain is derived. And, its simple upper and lower bounds are given using inequalities of matrix eigenvalues. The exact value of Sum-MSE gain depends heavily on the correlation factor of the IPN covariance matrix. More importantly, we also find that the Sum-MSE performance gain grows from 1 to $N/L$ as the correlation factor gradually decreases from 1 to 0, where $N$ and $L$ denote the number of total subcarrier and the length of cyclic prefix, respectively. Also, via theoretical analysis, the exact Sum-MSE gain degenerates into 1 and $N/L$ in two extreme scenarios: fully-correlated and white, respectively. The former 1 means there is no performance gain, while the latter $N/L$ corresponds to the maximum Sum-MSE performance gain achievable. Numerical simulation further validates the above results. Additionally, the derived lower bound is shown to be closer to the exact value of Sum-MSE gain compared to the upper bound.
- Subjects :
- 021103 operations research
Computer Networks and Communications
Covariance matrix
Orthogonal frequency-division multiplexing
0211 other engineering and technologies
Estimator
02 engineering and technology
Upper and lower bounds
Subcarrier
Computer Science Applications
Cyclic prefix
Matrix (mathematics)
Control and Systems Engineering
Applied mathematics
Electrical and Electronic Engineering
Eigenvalues and eigenvectors
Computer Science::Information Theory
Information Systems
Mathematics
Subjects
Details
- ISSN :
- 23737816 and 19328184
- Volume :
- 13
- Database :
- OpenAIRE
- Journal :
- IEEE Systems Journal
- Accession number :
- edsair.doi...........6d9e1168262dde0eafd1d2046e2bad20
- Full Text :
- https://doi.org/10.1109/jsyst.2018.2850934