Reliable OFDM Receiver with Ultra-Low Resolution ADC

Abstract

The use of low-resolution analog-to-digital converters (ADCs) can significantly reduce power consumption and hardware cost. However, their resulting severe nonlinear distortion makes reliable data transmission challenging. For orthogonal frequency division multiplexing (OFDM) transmission, the orthogonality among subcarriers is destroyed. This invalidates conventional OFDM receivers relying heavily on this orthogonality. In this study, we move on to quantized OFDM (Q-OFDM) prototyping implementation based on our previous achievement in optimal Q-OFDM detection. First, we propose a novel Q-OFDM channel estimator by extending the generalized Turbo (GTurbo) framework formerly applied for optimal detection. Specifically, we integrate a type of robust linear OFDM channel estimator into the original GTurbo framework and derive its corresponding extrinsic information to guarantee its convergence. We also propose feasible schemes for automatic gain control, noise power estimation, and synchronization. Combined with the proposed inference algorithms, we develop an efficient Q-OFDM receiver architecture. Furthermore, we construct a proof-of-concept prototyping system and conduct over-the-air (OTA) experiments to examine its feasibility and reliability. This is the first work that focuses on both algorithm design and system implementation in the field of low-resolution quantization communication. The results of the numerical simulation and OTA experiment demonstrate that reliable data transmission can be achieved.

arXiv comment14 pages, 17 figures; accepted by IEEE Transactions on Communications

References in corpus (19)

• Expectation-Maximization Gaussian-Mixture Approximate Message Passing
• Capacity Analysis of One-Bit Quantized MIMO Systems with Transmitter Channel State Information
• Bayes-Optimal Joint Channel-and-Data Estimation for Massive MIMO with Low-Precision ADCs
• Uplink Achievable Rate for Massive MIMO with Low-Resolution ADC
• A Field Guide to Forward-Backward Splitting with a FASTA Implementation
• Massive MIMO with 1-bit ADC
• Mixed-ADC Massive MIMO Detectors: Performance Analysis and Design Optimization
• Supervised-Learning-Aided Communication Framework for MIMO Systems with Low-Resolution ADCs
• Mixed-ADC Massive MIMO Uplink in Frequency-Selective Channels
• Bayesian Optimal Data Detector for mmWave OFDM System with Low-Resolution ADC
• Generalized Turbo Signal Recovery for Nonlinear Measurements and Orthogonal Sensing Matrices
• FASTA: A Generalized Implementation of Forward-Backward Splitting
• Joint Channel-Estimation/Decoding with Frequency-Selective Channels and Few-Bit ADCs
• Channel Estimation and Data Equalization in Frequency-Selective MIMO Systems with One-Bit Quantization
• A General Framework for Low-Resolution Receivers for MIMO Channels
• Low-Complexity Multiuser QAM Detection for Uplink 1-bit Massive MIMO
• Belief Propagation based MIMO Detection Operating on Quantized Channel Output
• Uplink Multiuser Massive MIMO Systems with Low-Resolution ADCs: A Coding-Theoretic Approach
• Generalized Expectation Consistent Signal Recovery for Nonlinear Measurements

Cited by in corpus (4)

• On Minimizing Symbol Error Rate Over Fading Channels with Low-Resolution Quantization
• Dynamic Metasurface Antennas for MIMO-OFDM Receivers with Bit-Limited ADCs
• Implementation and Performance Analysis of a Low Resolution OFDM System Prototype With Low Cost Hardware
• On the Capacity-Achieving Input of the Gaussian Channel with Polar Quantization