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arxiv: 1611.04846 · v1 · pith:SGEZJY6Znew · submitted 2016-11-15 · 💻 cs.IT · math.IT

Information Theoretic Performance of Periodogram-based CFO Estimation in Massive MU-MIMO Systems

classification 💻 cs.IT math.IT
keywords estimatorperiodogram-basedinformationmassiveperformancesystemstheoreticachieved
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In this paper, we study the information theoretic performance of the modified time-reversal maximum ratio combining (TR-MRC) receiver (presented in [9]) with the spatially averaged periodogram-based carrier frequency offset (CFO) estimator (proposed in [7]) in multi-user massive MIMO systems. Our analysis shows that an $\mathcal{O}(\sqrt{M})$ array gain is achieved with this periodogram-based CFO estimator, which is same as the array gain achieved in the ideal/zero CFO scenario ($M$ is the number of base station antennas). Information theoretic performance comparison with the correlation-based CFO estimator for massive MIMO systems (proposed in [6]) reveals that this periodogram-based CFO estimator is more energy efficient in slowly time-varying channels.

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