Litcius/Paper detail

Performance Analysis and Optimization of NOMA-Based Cell-Free Massive MIMO for IoT

Jiayi Zhang, Jingyi Fan, Jing Zhang, Derrick Wing Kwan Ng, Qiang Sun, Bo Ai

2021IEEE Internet of Things Journal53 citationsDOI

Abstract

This article investigates the performance of nonorthogonal multiple access (NOMA)-based cell-free massive multiple-input–multiple-output (mMIMO) for the Internet of Things (IoT) considering spatially correlated Rician fading channels. The exact closed form of downlink spectral efficiency (SE) and energy efficiency expressions is derived with three estimators and the maximum ratio transmission by taking the impacts of imperfect successive interference cancellation and pilot contamination into account. Subsequently, the performance of a local-MMSE precoder with the three aforementioned estimators is analyzed. Then, a large-scale fading-based user pairing scheme is proposed to further analyze the system SE. Besides, we formulate the optimum power control design as a max–min problem and a computational efficient suboptimal algorithm is proposed based on the successive convex approximation. Furthermore, our results reveal that the magnitude of the spatial correlation negligibly effects the SE in spatially correlated Rician fading channels. Then, numerical results confirm the positive effect of the proposed power control scheme. Also, our results further illustrate that NOMA-based cell-free mMIMO for IoT provides significant performance gain compared with its counterpart deploying conventional orthogonal multiple-access schemes.

Topics & Concepts

Rician fadingComputer scienceNomaTelecommunications linkMIMOFadingPower controlSpectral efficiencySingle antenna interference cancellationTransmitter power outputEstimatorAlgorithmMathematical optimizationPower (physics)Computer networkMathematicsChannel (broadcasting)StatisticsTransmitterPhysicsQuantum mechanicsDecoding methodsAdvanced MIMO Systems OptimizationAdvanced Wireless Communication TechnologiesEnergy Harvesting in Wireless Networks