In recent years, wireless communication systems have a high demand for high data throughput, high quality and spectrum efficiency. Massive MIMO is one of the new ideas in 5G. The idea is to expand the conventional MIMO system by installing large number of antennas in the base station to make better use of spatial diversity in order to provide higher throughput while using the same spectrum. However, in order to separate users and data streams and eliminate interference, an effective channel estimation technique with minimum overhead is crucial. In this paper, we propose a channel estimation technique to estimate the channel state information based on Kalman Filter. The received predetermined data is used by Kalman filter to estimate the channel, which is then used to detect the following data symbols in the same frame. The effectiveness of the proposed scheme is compared to the well-known Least square (LS) and Minimum Mean square Error (MMSE) schemes. The performance of the proposed scheme is assessed using computer simulation, and the obtained results for the proposed channel estimation demonstrate improved bit error rate performance in time-varying Rayleigh fading channels.

Abstract: A topological space is said to be epi -regular if a coarser topology

on exists such that

is

-regular. In this article we introduce and implement this property and give some examples to

show the relationships between epi -regular, epiregular, epinormal, submetrizable semiregular and Almost -

normal (almost -normal)..

Keywords: Epiregular, Epi -regular, Epinormal, Semiregular, Submetrizable, and Almost -normal (almost

-normal).

A novel non-blind audio watermarking algorithm, using chirp z-transform in combination with discrete wavelet transform and singular value decomposition, is presented in this paper. In the proposed method, a watermark audio signal (about 13 seconds in length) is hidden into an original audio signal (about 51 seconds in length) by applying discrete wavelet transform, chirp z-transform, and singular value decomposition. The effectiveness of the proposed algorithm has been tested using signal-to-noise ratio, objective difference grade (ODG), and normalised cross- correlation of watermarked audio signal under various common audio attacks. Experimental results demonstrate that the algorithm has a high capacity (352.8 kbps), without significant perceptual distortion (ODG > -0.29) and provides good robustness against common audio attacks, including: re-sampling, echo addition, MP3 compression, additive white Gaussian noise, re- quantisation, cutting, and low-pass filtering. This algorithm has a high capacity and excellent audio quality compared with other audio watermarking algorithms.

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