Near Maximum-Likelihood Detector and Channel Estimator for Uplink Multiuser Massive MIMO Systems With One-Bit ADCs

By Junil Choi, Jianhua Mo, Robert W. Heath. IEEE Transactions on Communications, 2015

455 citations recorded by the source corpus.

In massive multiple-input multiple-output (MIMO) systems, it may not be power efficient to have a pair of high-resolution analog-to-digital converters (ADCs) for each antenna element. In this paper, a near maximum likelihood (nML) detector for uplink multiuser massive MIMO systems is proposed where each antenna is connected to a pair of one-bit ADCs, i.e., one for each real and imaginary component of the baseband signal. The exhaustive search over all the possible transmitted vectors required in the original maximum likelihood (ML) detection problem is relaxed to formulate an ML estimation problem. Then, the ML estimation problem is converted into a convex optimization problem which can be efficiently solved. Using the solution, the base station can perform simple symbol-by-symbol detection for the transmitted signals from multiple users. To further improve detection performance, we also develop a two-stage nML detector that exploits the structures of both the original ML and the proposed (one-stage) nML detectors. Numerical results show that the proposed nML detectors are efficient enough to simultaneously support multiple uplink users adopting higher-order constellations, e.g., 16 quadrature amplitude modulation. Since our detectors exploit the channel state information as part of the detection, an ML channel estimation technique with one-bit ADCs that shares the same structure with our proposed nML detector is also developed. The proposed detectors and channel estimator provide a complete low power solution for the uplink of a massive MIMO system.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/1e9db4c07a1c48d3ef51f2eca4d45a3439496046

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Citations in the corpus

Channel Estimation in Broadband Millimeter Wave MIMO Systems With Few-Bit ADCs (2016, background): “In previous work [6], [7], the variance of the channel was assumed to be known to avoid this issue.”
Channel Estimation and Performance Analysis of One-Bit Massive MIMO Systems (2016, methodology): “Least Squares estimator is from [21] and nML estimator is from [25].”
Uplink Performance of Wideband Massive MIMO With One-Bit ADCs (2016, background): “For example, a near-maximum-likelihood detector for onebit quantized signals was proposed in [3], while [4] and [6] studied the use of linear detection.”