4 research outputs found

    CFO Estimation for OFDM-based Massive MIMO Systems in Asymptotic Regime

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    Massive multiple input multiple output (MIMO) plays a pivotal role in the fifth generation (5G) wireless networks. However, the carrier frequency offset (CFO) estimation is a challenging issue in the uplink of multi-user massive MIMO systems. In fact, frequency synchronization can impose a considerable amount of computational complexity to the base station (BS) due to a large number of BS antennas. In this paper, thanks to the properties of massive MIMO in the asymptotic regime, we develop a simple synchronization technique and derive a closed form equation for CFO estimation. We show that the phase information of the covariance matrix of the received signals is solely dependent on the users’ CFOs. Hence, if a real-valued pilot is chosen, the CFO values can be straightforwardly calculated from this matrix. Hence, there is no need to deal with a complex optimization problem like the other existing CFO estimation techniques in the literature. Our simulation results testify the efficacy of our proposed CFO estimation technique. As we have shown, the performance of our method does not deteriorate as the number of users increases

    Phase-Noise Compensation for OFDM Systems Exploiting Coherence Bandwidth: Modeling, Algorithms, and Analysis

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    Phase-noise (PN) estimation and compensation are crucial in millimeter-wave (mmWave) communication systems to achieve high reliability. The PN estimation, however, suffers from high computational complexity due to its fundamental characteristics, such as spectral spreading and fast-varying fluctuations. In this paper, we propose a new framework for low-complexity PN compensation in orthogonal frequency-division multiplexing systems. The proposed framework also includes a pilot allocation strategy to minimize its overhead. The key ideas are to exploit the coherence bandwidth of mmWave systems and to approximate the actual PN spectrum with its dominant components, resulting in a non-iterative solution by using linear minimum mean squared-error estimation. The proposed method obtains a reduction of more than 2.5x in total complexity, as compared to the existing methods. Furthermore, we derive closed-form expressions for normalized mean squared-errors (NMSEs) as a function of critical system parameters, which help in understanding the NMSE behavior in low and high signal-to-noise ratio regimes. Lastly, we study a trade-off between performance and pilot-overhead to provide insight into an appropriate approximation of the PN spectrum.Comment: To appear in IEEE Transactions on Wireless Communication
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