Bayesian Optimal Data Detector for Hybrid mmWave MIMO-OFDM Systems with Low-Resolution ADCs

Abstract

Hybrid analog-digital precoding architectures and low-resolution analog-to-digital converter (ADC) receivers are two solutions to reduce hardware cost and power consumption for millimeter wave (mmWave) multiple-input multiple-output (MIMO) communication systems with large antenna arrays. In this study, we consider a mmWave MIMO-OFDM receiver with a generalized hybrid architecture in which a small number of radio-frequency (RF) chains and low-resolution ADCs are employed simultaneously. Owing to the strong nonlinearity introduced by low-resolution ADCs, the task of data detection is challenging, particularly achieving a Bayesian optimal data detector. This study aims to fill this gap. By using generalized expectation consistent signal recovery technique, we propose a computationally efficient data detection algorithm that provides a minimum mean-square error estimate on data symbols and is extended to a mixed-ADC architecture. Considering particular structure of MIMO-OFDM channel matirx, we provide a lowcomplexity realization in which only FFT operation and matrixvector multiplications are required. Furthermore, we present an analytical framework to study the theoretical performance of the detector in the large-system limit, which can precisely evaluate the performance expressions such as mean-square error and symbol error rate. Based on this optimal detector, the potential of adding a few low-resolution RF chains and high-resolution ADCs for mixed-ADC architecture is investigated. Simulation results confirm the accuracy of our theoretical analysis and can be used for system design rapidly. The results reveal that adding a few low-resolution RF chains to original unquantized systems can obtain significant gains.

15 pages,8 figures, to appear in IEEE Journal of Selected Topics in Signal Processing

References in corpus (6)

• Massive MIMO with Non-Ideal Arbitrary Arrays: Hardware Scaling Laws and Circuit-Aware Design
• Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices
• Massive MIMO with 1-bit ADC
• Resolution-Adaptive Hybrid MIMO Architectures for Millimeter Wave Communications
• Bayesian Optimal Data Detector for mmWave OFDM System with Low-Resolution ADC
• Generalized Expectation Consistent Signal Recovery for Nonlinear Measurements

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