Modeling and Estimation of Phase Noise in Oscillators with Colored Noise Sources
The continuous increase in demand for higher data rates due to applications with massive number of users motivates the design of faster and more spectrum efficient communication systems. In theory, the current communication systems must be able to operate close to Shannon capacity bounds. However, the real systems perform below capacity limits, mainly due to channel estimation error and hardware impairments that have been neglected by idealistic or simplistic assumptions on the imperfections.
Oscillator phase noise is one of the hardware impairments that is becoming a limiting factor in high data rate digital communication systems. Phase noise severely limits the performance of systems that employ dense constellations. Moreover, the level of phase noise (at a given off-set frequency) increases with carrier frequency which means that the problem of phase noise may be even more severe in systems with high carrier frequency.
The focus of this thesis is on finding accurate statistical models of phase noise, as well as the design of efficient algorithms to mitigate the effect of this phenomenon on the performance of modern communication systems. First we derive the statistics of phase noise with white and colored noise sources in free-running and phase-locked-loop-stabilized oscillators. We investigate the relation between real oscillator phase noise measurements and the performance of communication systems by means of the proposed model. Our findings can be used by hardware and frequency generator designers to better understand the effect of phase noise with different sources on the system performance and optimize their design criteria respectively.
Then, we study the design of algorithms for estimation of phase noise with colored noise sources. A soft-input maximum a posteriori phase noise estimator and a modified soft-input extended Kalman smoother are proposed. The performance of the proposed algorithms is compared against that of those studied in the literature, in terms of mean square error of phase noise estimation, and symbol error rate of the considered communication system. The comparisons show that considerable performance gains can be achieved by designing estimators that employ correct knowledge of the phase noise statistics. The performance improvement is more significant in low-SNR or low-pilot density scenarios.
Phase Noise Model
Bayesian Cramer-Rao Bound
Extended Kalman Filter/Smoother
Maximum a Posteriori Estimator
Colored Phase Noise
Oscillator Phase Noise
Mean Square Error.