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[Keyword] system level simulation(2hit)

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  • Cell-Specific Association for Heterogeneous Networks with Interference Control

    Yinghong WEN  Yuan CAO  Wei XU  Hideo NAKAMURA  

     
    PAPER-Wireless Communication Technologies

      Vol:
    E98-B No:4
      Page(s):
    653-660

    This paper focuses on system level simulation of heterogeneous networks (HetNet). Aiming at the imbalance offloading of macro cell and pico cell under the macro-pico coexistence case, we propose an adaptive cell-specific association strategy for HetNet to ensure that users can be served equitably by both macro cell and pico cell. The traditional cell range expansion (CRE) scheme with bias-based cell association has fixed bias values for all pico cells. Our proposal, on the other hand, sets different thresholds of attached users for all MeNB (macro enhanced node B) and PeNBs (pico enhanced node B), and all cell-specific biases are obtained by the proposed adaptive association strategy according to different cell-specific predefined thresholds. With this strategy, the load imbalance between MeNB and different PeNBs is well alleviated, and hence the entire network performance is elevated. Moreover, due to the newly deployed low-power nodes in HetNets, the achieved spectral efficiency of users, especially for cell edge users, is also affected by the downlink inter-cell interference. The idea we put forward is to combine the frequency and power coordination, and so suppress the inter-cell interference. Finally in this paper, we present some numerical results to verify the effectiveness of our proposed approach.

  • Link Performance Modeling of Interference Rejection Combining Receiver in System Level Evaluation for LTE-Advanced Downlink

    Yousuke SANO  Yusuke OHWATARI  Nobuhiko MIKI  Akihito MORIMOTO  Yukihiko OKUMURA  

     
    PAPER

      Vol:
    E95-B No:12
      Page(s):
    3739-3751

    The interference rejection combining (IRC) receiver, which can suppress inter-cell interference, is effective in improving the cell-edge user throughput. The IRC receiver is typically based on the minimum mean square error (MMSE) criteria, and requires a covariance matrix including the interference signals, in addition to a channel matrix from the serving cell. Therefore, in order to clarify the gain from the IRC receiver, the actual estimation error of these matrices should be taken into account. In a system performance evaluation, the link performance modeling of the IRC receiver, i.e., the output signal-to-interference-plus-noise power ratio (SINR) after IRC reception including the estimation errors, is very important in evaluating the actual performance of the IRC receiver in system level simulations. This is because these errors affect the suppression of the interference signals for the IRC receiver. Therefore, this paper investigates and proposes IRC receiver modeling schemes for the covariance matrix and channel estimation errors. As the modeling scheme for the covariance matrix, we propose a scheme that averages the conventional approximation using the complex Wishart distribution in the frequency domain to address issues that arise in a frequency selective fading channel. Furthermore, we propose a modeling scheme for the channel estimation error according to the ideal channel response of all cells and a channel estimation filter to address channel fading fluctuations. The results of simulations assuming the LTE/LTE-Advanced downlink with two transmitter and receiver antenna branches show that the proposed modeling scheme for the covariance matrix estimation error accurately approximates the performance of a realistic IRC receiver, which estimates the covariance matrix and channel matrix of the serving cell based on the demodulation reference signal (DM-RS), even in a frequency selective fading channel. The results also show that the proposed modeling scheme for the channel estimation error is a robust scheme in terms of the r.m.s. delay spread of a channel model compared to the scheme using the mean square error (MSE) statistic of the estimated channel coefficients based on a channel estimation filter.

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