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An Improvement of Channel Estimation for Up-link NOMA Systems | IEEE Conference Publication | IEEE Xplore

An Improvement of Channel Estimation for Up-link NOMA Systems


Abstract:

It is predicted that IoT (Internet of Things) will be developed rapidly and then every variety of information will be gathered to central processing systems using wireles...Show More

Abstract:

It is predicted that IoT (Internet of Things) will be developed rapidly and then every variety of information will be gathered to central processing systems using wireless systems. In next Generation mobile communications systems, a base station must deal with a huge number of signals transmitted from IoT devices. In addition, some applications require low latency communication for control systems such as auto driving systems. We, therefore, have researched contention based communication methods so that both massive connection and low latency communication can be realized. We have developed the system and evaluated its performance using not only computer simulation but also experiments in real environments. And then, we confirmed that our system could work well in the real environments. In the paper, in order to further enhance the system reliability, we propose the method that improves bit error rate (BER) performance of the system. The paper organized as follows. First, we illustrate our system regarding the sub-frame structure and the signal processing procedure and the basic channel estimation methods. Secondly, we propose how to improve the accuracy of channel estimation. We propose that the Kaiser filter and window function are employed to extract the channel impulse response (CIR). Finally, we evaluated the proposed technique by computer simulation and confirmed that BER performance could be improved. The proposed method could make BER reduce by less than one-tenth even though CIR estimation conditions were severe.
Date of Conference: 25-28 November 2018
Date Added to IEEE Xplore: 13 May 2019
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Conference Location: Chiang Rai, Thailand

References

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