TY - GEN
T1 - Hardware-Limited Task-Based Quantization
AU - Shlezinger, Nir
AU - Eldar, Yonina C.
AU - Rodrigues, Miguel R.D.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Quantization plays a critical role in digital signal processing systems. Quantizers are typically designed to obtain an accurate digital representation of the input signal, operating independently of the system task, and are commonly implemented using scalar analog-to-digital converters (ADCs). In this work, we study hardware-limited task-based quantization, where a system utilizing a serial scalar ADC is designed to provide a suitable representation in order recover a parameter vector underlying the input signal. We propose hardware-limited task-based quantization systems for a fixed and finite quantization resolution, and characterize their achievable distortion. Our results illustrate that properly designed hardware-limited systems can approach the optimal performance achievable with vector quantizers, and that by taking the underlying task into account, the quantization error can be made negligible with a relatively small number of bits.
AB - Quantization plays a critical role in digital signal processing systems. Quantizers are typically designed to obtain an accurate digital representation of the input signal, operating independently of the system task, and are commonly implemented using scalar analog-to-digital converters (ADCs). In this work, we study hardware-limited task-based quantization, where a system utilizing a serial scalar ADC is designed to provide a suitable representation in order recover a parameter vector underlying the input signal. We propose hardware-limited task-based quantization systems for a fixed and finite quantization resolution, and characterize their achievable distortion. Our results illustrate that properly designed hardware-limited systems can approach the optimal performance achievable with vector quantizers, and that by taking the underlying task into account, the quantization error can be made negligible with a relatively small number of bits.
KW - Analog-to-digital conversion
KW - Quantization
UR - http://www.scopus.com/inward/record.url?scp=85072328100&partnerID=8YFLogxK
U2 - 10.1109/SPAWC.2019.8815422
DO - 10.1109/SPAWC.2019.8815422
M3 - Conference contribution
AN - SCOPUS:85072328100
T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
BT - 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019
PB - Institute of Electrical and Electronics Engineers
T2 - 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019
Y2 - 2 July 2019 through 5 July 2019
ER -