Browsing by Author "Jungnickel, V."

Now showing 1 - 3 of 3
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    Analysis of synchronization impairments for cooperative base stations using OFDM
    (2015) Manolakis, K.; Oberli Graf, Christian Robert; Jungnickel, V.; Rosas, F.
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    Analytical models for channel aging and synchronization errors for base station cooperation
    (IEEE, 2013) Manolakis, K.; Oberli Graf, Christian Robert; Herrera Pereira, Lurys; Jungnickel, V.
    Base station cooperation is a powerful technique for eliminating inter-cell interference and enhancing spectral efficiency in cellular networks. However, impairment effects due to channel time variance, channel estimation, feedback quantization and imperfect synchronization among base stations are limiting the potential gains. In this paper, we present a comprehensive signal model for multi-user multi-cellular systems with cooperating base stations, which includes those essential impairments. The effect of each impairment is captured by its mean square error (MSE), for which exact analytical expressions and accurate approximations are derived and numerically verified. Those MSE expressions can be used for link-layer abstraction, system-level evaluation and signal to interference ratio (SIR) analysis. We evaluate the spectral efficiency of cooperative networks considering a real-world scenario and find that channel aging has the largest impact on performance degradation.
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    Random matrices and the impact of imperfect channel knowledge on cooperative base stations
    (IEEE, 2013) Manolakis, K.; Oberli Graf, Christian Robert; Jungnickel, V.
    Base station cooperation is a very promising technique for reducing inter-cell interference and enhancing spectral efficiency in next generation cellular systems. However, imperfect precoding at the base stations is limiting the potential gains. In this paper, we present a downlink signal model with impaired zero-forcing precoding and analyze self-user signal and inter-user interference. Properties of Wishart-distributed random matrices are used for calculating the average inverse eigenvalues. We provide closed-form expressions for signal to interference ratio (SIR) bounds, which are found inversely proportional to the mean square error of the base station's channel knowledge. Further, it is found that the SIR increases with the ratio of number of base stations to number of users. Numerical evaluation agrees with analytical results.