Multiple Parameter Estimation With Quantized Channel Output

2010/10/26 by Amine Mezghani, Mezghani, Amine, Felix Antreich +3 · 1 citation
Computer Science · Engineering · #Control Systems and Identification #Direction-of-Arrival Estimation Techniques #FOS: Computer and information sciences #Information Theory (cs.IT) #Sparse and Compressive Sensing Techniques

paper · doi:10.48550/arxiv.1010.5532

openalex publication_date 2010/10/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We present a general problem formulation for optimal parameter estimation based on quantized observations, with application to antenna array communication and processing (channel estimation, time-of-arrival (TOA) and direction-of-arrival (DOA) estimation). The work is of interest in the case when low resolution A/D-converters (ADCs) have to be used to enable higher sampling rate and to simplify the hardware. An Expectation-Maximization (EM) based algorithm is proposed for solving this problem in a general setting. Besides, we derive the Cramer-Rao Bound (CRB) and discuss the effects of quantization and the optimal choice of the ADC characteristic. Numerical and analytical analysis reveals that reliable estimation may still be possible even when the quantization is very coarse.

Cited by

• Enabling low-power massive MIMO with ternary ADCs for AIoT sensing

Related

• DOA Parameter Estimation with 1-bit Quantization - Bounds, Methods and the Exponential Replacement
• MCRB for Parameter Estimation from One-Bit Quantized and Oversampled Measurements
• Investigation of Channel Estimation Techniques with 1-bit Quantization and Oversampling for Multiple-Antenna Systems
• Bayesian Massive MIMO Channel Estimation with Parameter Estimation Using Low-Resolution ADCs
• Belief Propagation based MIMO Detection Operating on Quantized Channel Output