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  • 1.
    Özdogan, Özgecan
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Massive MIMO With Spatially Correlated Rician Fading Channels2019In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 67, no 5, p. 3234-3250Article in journal (Refereed)
    Abstract [en]

    This paper considers multi-cell massive multiple-input multiple-output systems, where the channels are spatially correlated Rician fading. The channel model is composed of a deterministic line-of-sight path and a stochastic non-line-of-sight component describing a practical spatially correlated multipath environment. We derive the statistical properties of the minimum mean squared error (MMSE), element-wise MMSE, and least-square channel estimates for this model. Using these estimates for maximum ratio combining and precoding, rigorous closed-form uplink (UL) and downlink (DL) achievable spectral efficiency (SE) expressions are derived and analyzed. The asymptotic SE behavior, when using the different channel estimators, are also analyzed. The numerical results show that the SE is higher when using the MMSE estimator than that of the other estimators, and the performance gap increases with the number of antennas.

  • 2.
    Özdogan, Özgecan
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Uplink Spectral Efficiency of Massive MIMO with Spatially Correlated Rician Fading2018In: 2018 IEEE 19TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), IEEE , 2018, p. 216-220Conference paper (Refereed)
    Abstract [en]

    This paper considers the uplink (UL) of a multicell Massive MIMO (multiple-input multiple-output) system with spatially correlated Rician fading channels. The channel model is composed of a deterministic line-of-sight (LoS) path and a stochastic non-line-of-sight (NLoS) component describing a spatially correlated multipath environment. We derive the statistical properties of the minimum mean squared error (MMSE) and least-square (LS) channel estimates for this model. Using these estimates for maximum ratio (MR) combining, rigorous closed-form UL spectral efficiency (SE) expressions are derived. Numerical results show that the SE is higher when using the MMSE estimator than the LS estimator, and the performance gap increases with the number of antennas. Moreover, Rician fading provides higher achievable SEs than Rayleigh fading since the LoS path improves the sum SE.

  • 3.
    Özdogan, Özgecan
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Zhang, Jiayi
    Beijing Jiaotong Univ, Peoples R China.
    Cell-Free Massive MIMO with Rician Fading: Estimation Schemes and Spectral Efficiency2018In: 2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, IEEE , 2018, p. 975-979Conference paper (Refereed)
    Abstract [en]

    As the cell sizes in cellular networks shrink, the inter-cell interference becomes more of an issue. Instead of operating each cell autonomously, we can connect all the access points (APs) together to form a cell-free massive MIMO (multiple-input multiple-output) system that can alleviate interference by spatial processing. Previous studies have focused on Rayleigh fading channels, but in densely deployed systems, it is likely that some of the users will have line-of-sight (LoS) propagation to some of the APs. In this paper, we model this by arbitrarily distributed Rician fading channels. Two types of channel estimators are considered: a classical least-square (LS) estimator and a Bayesian minimum mean square error (MMSE) estimator. We derive closed-form spectral efficiency (SE) expressions for the uplink (UL) and downlink (DL) when using each of these estimators for maximum ratio (MR) processing. The performance difference is evaluated numerically to figure out under which conditions it is beneficial to know the channel statistics when estimating a channel.

  • 4.
    Özdogan, Özgecan
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Zhang, Jiayi
    Beijing Jiaotong Univ, Peoples R China.
    Performance of Cell-Free Massive MIMO With Rician Fading and Phase Shifts2019In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 18, no 11, p. 5299-5315Article in journal (Refereed)
    Abstract [en]

    In this paper, we study the uplink (UL) and downlink (DL) spectral efficiency (SE) of a cell-free massive multiple-input-multiple-output (MIMO) system over Rician fading channels. The phase of the line-of-sight (LoS) path is modeled as a uniformly distributed random variable to take the phase-shifts due to mobility and phase noise into account. Considering the availability of prior information at the access points (APs), the phase-aware minimum mean square error (MMSE), non-aware linear MMSE (LMMSE), and least-square (LS) estimators are derived. The MMSE estimator requires perfectly estimated phase knowledge whereas the LMMSE and LS are derived without it. In the UL, a two-layer decoding method is investigated in order to mitigate both coherent and non-coherent interference. Closed-form UL SE expressions with phase-aware MMSE, LMMSE, and LS estimators are derived for maximum-ratio (MR) combining in the first layer and optimal large-scale fading decoding (LSFD) in the second layer. In the DL, two different transmission modes are studied: coherent and non-coherent. Closed-form DL SE expressions for both transmission modes with MR precoding are derived for the three estimators. Numerical results show that the LSFD improves the UL SE performance and coherent transmission mode performs much better than non-coherent transmission in the DL. Besides, the performance loss due to the lack of phase information depends on the pilot length and it is small when the pilot contamination is low.

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