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Hybrid Lower-Complexity Wiener Filter for Pilot-Based Channel Estimation for C-RS in LTE-A DL System

With Throughput Evaluation Using 3GPP LTE-A Test Cases

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Abstract

This paper presents a pilot-based lower complexity channel estimation for Long Term Evolution Advanced (LTE-A) Cell-specific Reference Signals (C-RS). The proposed system is a hybrid one, based on using 2 × 1-D Wiener filter for noise filtering at pilot locations only with cubic spline interpolation for data symbol locations, with accuracy that almost matches the 2-D Wiener filter and Wiener interpolation under certain channel and noise conditions, and at reduced computational complexity. The performance of the proposed scheme is evaluated in terms of Mean Squared Error (MSE) under various channel conditions. Complexity analysis show that the proposed scheme requires 8.8% of the number of computations needed by 2-D Wiener filtering with Wiener interpolation, while still matching its performance up till specific noise and channel conditions. In addition, 2 × 1-D Wiener filter performance is proven to be sub-optimal when compared with the performance of 2-D Wiener filter. The obtained results show that the best noise filtering method is a combination of both moving average and Wiener filtering, where the lower bound is a function of both Symbol-to-Noise-Ratio (SNR) and the channel statistics. Simulations in real-life LTE-A scenarios confirms the feasibility of the proposed channel estimation scheme. Analytical results wherever possible and, in general, simulation results are presented.

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Authors and Affiliations

  1. Electrical and Computer Engineering, University of Western Ontario, London, ON, Canada

    Mohammed Zourob & Raveendra Rao

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  1. Mohammed Zourob
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  2. Raveendra Rao
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Correspondence to Mohammed Zourob.

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Zourob, M., Rao, R. Hybrid Lower-Complexity Wiener Filter for Pilot-Based Channel Estimation for C-RS in LTE-A DL System. Mobile Netw Appl 23, 921–939 (2018). https://doi.org/10.1007/s11036-017-0964-0

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  • DOI: https://doi.org/10.1007/s11036-017-0964-0

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