Bounds on Phase, Frequency, and Timing Synchronization in Fully Digital Receivers With 1-bit Quantization and Oversampling

• Published in: IEEE transactions on communications Vol. 68; no. 10; pp. 6499 - 6513
• Main Authors: Schluter, Martin, Dorpinghaus, Meik, Fettweis, Gerhard P.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 1-bit quantization; Algorithms; Bandwidth; Bandwidths; Closed form solutions; Colored noise; Cramer-Rao bounds; Cramér–Rao bounds; Dithering; Energy consumption; Exact solutions; Linearity; Lower bounds; Mathematical analysis; Measurement; Noise; Nonlinearity; Oversampling; Parameter estimation; Quantization (signal); Receivers; Signal to noise ratio; Synchronism; Timing; White noise
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2020.3005738

Digital receivers based on 1-bit quantization and oversampling w.r.t. the transmit signal bandwidth promise lower energy consumption. However, since 1-bit quantization is a highly non-linear operation, standard receiver algorithms cannot be applied. Thus, we derive performance bounds for phase, timing, and frequency estimation in order to gain a deeper insight into the impact of 1-bit quantization and oversampling. We identify uniform phase and sample dithering as crucial to combat the effect of the non-linearity introduced by 1-bit quantization. Since oversampling results in noise correlation, a closed form of the likelihood function is not available. Thus, we study a system model with white noise by adapting the receive filter bandwidth to the sampling rate. Considering the aforementioned dithering, we obtain very tight closed form lower bounds on the Cramér-Rao lower bound (CRLB) in the large sample regime. We show that with uniform phase and sample dithering, all large sample properties of the CRLB of the unquantized receiver are preserved under 1-bit quantization, except for an signal-to-noise ratio (SNR) dependent performance loss that can be decreased by oversampling. Numerical computations show that the properties of the CRLB for white noise still hold for colored noise except that the performance loss due to 1-bit quantization is reduced.