A Novel Carrier Loop Algorithm Based on Maximum Likelihood Estimation (MLE) and Kalman Filter (KF) for Weak TC-OFDM...

Area of Science:

• Electrical Engineering
• Signal Processing
• Wireless Communications

Background:

• Digital broadcasting signals offer potential for indoor positioning.
• Time & Code Division-Orthogonal Frequency Division Multiplexing (TC-OFDM) is a key technology for this.
• Weak signal strength degrades TC-OFDM receiver carrier loop performance and tracking sensitivity.

Purpose of the Study:

• To propose a novel carrier loop algorithm for TC-OFDM receivers.
• To address limitations in tracking sensitivity under weak signal conditions in complex indoor environments.
• To enhance the performance of TC-OFDM based indoor positioning systems.

Main Methods:

• Developed a new carrier loop algorithm combining Maximum Likelihood Estimation (MLE) and Kalman Filter (KF).
• Replaced the existing discriminator with an MLE discriminator function derived using the Levenberg-Marquardt (LM) algorithm.
• Utilized KF to smooth MLE results, incorporating carrier phase, angular frequency, and rate as state vectors.

Main Results:

• The proposed algorithm significantly improves the tracking sensitivity of TC-OFDM receivers.
• Achieved an effective improvement of 2⁻4 dB in tracking sensitivity compared to current algorithms.
• Demonstrated superior performance in real-world indoor environments.

Conclusions:

• The novel MLE and KF-based carrier loop algorithm enhances TC-OFDM receiver performance.
• The algorithm effectively overcomes limitations posed by weak signals in indoor positioning.
• This advancement contributes to more reliable and sensitive indoor positioning using digital broadcasting signals.