Quasi-static Multipath Channel Research Articles

FTN-Based Non-Orthogonal Signal Detection Technique With Machine Learning in Quasi-Static Multipath Channel

FTN-Based Non-Orthogonal Signal Detection Technique With Machine Learning in Quasi-Static Multipath Channel

Performance Analysis of SIMO–OFDM Systems With Pilot-Aided Channel Estimation

Pilot symbols are commonly modulated on uniformly spaced subcarriers to aid channel estimation, thereby facilitating data demodulation in practical orthogonal frequency-division multiplexing (OFDM) systems operating over quasi-static multipath channels, where the channel frequency response (CFR) remains static within one block. Aided by uniformly spaced pilot symbols, the direct least-square CFR estimation can enable reliable symbol-by-symbol data demodulation within the same OFDM block, based on the principle of generalized likelihood ratio test (GLRT). Such GLRT-based OFDM can be easily incorporated with single-input multiple-output (SIMO) antenna technique to enhance data demodulation over quasi-static channels exhibiting random multipaths. In this article, an upper bound to the average bit error probability (BEP) is analytically derived for this GLRT-based SIMO–OFDM system over quasi-static random multipath channels. The analysis is generally applicable to arbitrary two-dimensional component modulations when the quasi-static SIMO channel consists of independent but not necessarily identically distributed random channel paths with Rician or Rayleigh distributed path response magnitudes. The BEP upper bound facilitates the error performance characterization of the GLRT-based SIMO–OFDM system with respect to data-to-noise power ratio, data-to-pilot power ratio, antenna diversity, pilot density, and pilot power allocation.

Spectrally Efficient OFDM Pilot Waveform for Channel Estimation

Pilot-aided channel estimation is essential to orthogonal frequency division multiplexing systems and standards. Under the system setup that data and pilot waveforms are processed individually for enhancing the spectral efficiency of the composite waveform, pilot patterns are designed here to jointly optimize channel estimation on quasistatic multipath channels and provide extremely high spectral compactness by suppressing spectral sidelobes. Specifically, a general constraint on pilot pattern is developed to endow the pilot waveform with very small spectral sidelobes and thus compact spectrum. Using the constraint, systematic multiple-stage design procedures are proposed to develop the desired pilot patterns achieving Cramer Rao bound for channel estimation on quasistatic multipath channels while providing fast decaying spectral sidelobes. Among the demonstrated pilot patterns achieving optimum channel estimation, the pilot waveforms using $\mathcal {A}_{I}$ - and $\mathcal {B}_{I}$ -typed pilot patterns developed from the procedures are shown to exhibit higher spectral compactness than conventional pilot waveforms. Besides, $\mathcal {C}_{I}$ -typed pilot pattern that exploits extremely high spectral compactness without resort to channel estimation optimization is also developed. By sacrificing a slight loss in channel estimation, the pilot waveforms using $ \mathcal {C}_{I}$ -typed pilot pattern are shown to exhibit spectrums approaching the Nyquist spectrum.

SNR Improvement for Energy Detection of Narrow Band Signal in OFDM System

For orthogonal frequency division multiplexing (OFDM) based cognitive systems, the narrow band signal of the primary users (PU) is difficult to detect when it straddles the boundaries of two adjacent subcarriers. In this paper, we propose a novel energy detection (ED) method with time domain noise smoothing to improve the performance of the conventional ED of the OFDM system under the quasi-static multipath channel for detecting the narrow band primary signals. The effect of noise smoothing of the proposed ED method is analyzed. The close-form solution of probability of detection for OFDM system under quasi-static multipath channel is derived and verified by simulations. Simulations show that the proposed ED method can achieve the expected high signal-to-noise ratio (SNR) gain.