Robust channel estimation and ISI cancellation for OFDM systems with suppressed features
A feature-suppressed orthogonal frequency-division multiplexing (OFDM) system and the corresponding channel estimation and intersymbol interference (ISI) mitigation techniques are investigated in this paper. Cyclic prefix (CP) and pilot tones, which are commonly used in civilian OFDM systems for ISI mitigation and channel estimation, create distinctive waveform features that can be easily used for synchronization and channel estimation purposes by intercepting receivers. As a result, CP and pilot tones are eliminated in the proposed feature suppressed OFDM system to reduce the interception probability. Instead, a set of specially designed OFDM symbols, driven by different pseudorandom sequences, are employed as preambles to avoid unique spectral signature. These preambles are inserted into the OFDM data symbol stream periodically and in a round-robin manner. In addition, a random frequency offset is introduced to each preamble to further mask the multicarrier signature. New challenges arising from these feature suppression efforts are studied, including robust channel estimation and demodulation techniques in the presence of frequency offset and severe interference. Based on our interference analysis, an iterative ISI and intercarrier interference (ICI) estimation-cancellation-based technique is proposed for both channel estimation and OFDM data demodulation. Our channel estimator performs joint frequency offset and channel impulse response estimation based on the maximum-likelihood (ML) principle. To reduce its complexity, we employ a number of techniques, which include approximation of the ML metrics, as well as fast Fourier transform pruning. The performances and feasibility of the proposed feature suppressed OFDM system and the channel estimator are analyzed and verified through numerical simulations.