Abstract
The communication systems for Poisson channels require long pilot for channel estimation and may result in large percentage of overhead due to the signal-dependent noise of Poisson-distributed signal, i.e., both signal part and noise part experience random processes. In this paper, both blind and semi-blind channel estimation methods are studied to shorten the overhead and increase the transmission efficiency for Poisson channels. First, fractionally spaced equalizers are proposed based on modified constant modulus algorithm (CMA) and subspace (SS). Second, a data-aided iterative channel estimation (ICE) is designed and analyzed in terms of its asymptotic unbiasedness and convergence. The proposed methods are evaluated based on both a constant channel scenario and a varying channel scenario. Numerical simulation results show that the modified CMA has the worst bit-error rate performance but requires the lowest computational complexity. Besides, both SS based channel estimation and ICE have negligible overhead and comparable bit-error rate performances with respect to the conventional periodic pilot based channel estimation having 50% overhead.
| Original language | English |
|---|---|
| Pages (from-to) | 5930-5946 |
| Number of pages | 17 |
| Journal | IEEE Transactions on Wireless Communications |
| Volume | 21 |
| Issue number | 8 |
| DOIs | |
| State | Published - 1 Aug 2022 |
Keywords
- Blind channel estimation
- constant modulus algorithm
- data-aided iterative channel estimation
- poisson channel
- semi-blind channel estimation
- subspace based channel estimation
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