Abstract
Communications over power lines (PLC) is a promising technology for a variety of applications. The use of a single network for power and data transmission with PLC provides weight, space, and cost savings for vehicular communications. Current work focuses on broadband PLC (BPL) systems compliant with the IEEE 1901 standard. Given that transmissions occur on a physical medium not designed for data communication, the channel and noise characteristics are mostly unfavorable. To deal with these conditions, turbo codes have been widely employed due to their high performance. However, their performance strongly depends on the accuracy of the noise estimation. This work addresses the estimation of the noise power spectral density (PSD) to perform soft-decoding. A general background noise (GBN) model and a narrowband interference (NBI) model is considered. To the best of our knowledge, this is the first work that analyzes the effects of the NBI leakage on noise estimation when it is performed during the reception of the data frame. We propose the use of the frame control (FC) symbol to reduce interference leakage on noise estimation. In addition, we investigate the use of payload symbols to further reduce spectral leakage. Finally, we show that system performance considerably improves by using the FC-based estimation in soft-decoding procedures.
Highlights
Data communication over power lines is a promising technology for a variety of applications
Technical advances in broadband power line communications (PLC) (BPL) systems enable a variety of applications besides Automatic Meter Reading (AMR) due to its higher data rate compared to older PLC systems
OFDM TRANSCEIVER We evaluate the impact of spectral leakage and noise estimation on a PLC system using a transceiver conformant with the IEEE 1901 standard
Summary
Data communication over power lines is a promising technology for a variety of applications. Another way to mitigate NBI in OFDM systems is to perform noise cancellation within the received signal This technique requires prior knowledge of the interference model and estimation of its parameters in either the time or the frequency domains (e.g. amplitude, phase and frequency for a single-tone interferer) [24], [25]. Instead of canceling the interference, a different approach proposes to include the current NBI power into the log-likelihood ratio (LLR) computation at the receiver side [19], [34] This sort of weighting of soft-decisions relies on the ability of coding schemes to limit the influence of interfering signals. Other signal processing blocks such as automatic gain control (AGC) and sampling frequency offset correction are present, out of the scope of this work as they are not relevant to noise PSD estimation. Throughout this work we assume that the channel frequency response (CFR) remains constant during a frame interval
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