Ultra Reliable and Low Latency Communications (URLLC) play a key role in 5G vertical markets, but pose many technical challenges especially when sharing the spectrum with Enhanced Mobile Broadband (eMBB) customers. This study aims to overcome the spectrum inefficiency issue of fully separate (FS) approach and the contention issue of the fully overlap (FO) approach. We present a user-initiated probability elastic resource (UPER) approach by dynamically adjusting the probability of using the shared spectrum for eMBB and URLLC traffic based on the current success and failure status of packet transmission status. The probabilities of successful transmission are derived for UPER, FS, and FO and partially overlap (PO) sharing spectrum approaches. We find that the successful transmission probability of UPER approach is 28% and 46% higher than FS and FO approaches, respectively. We further evaluate the reliability and throughput performance of URLLC and eMBB. When the URLLC packet load is low, the UPER method can almost achieve the best performance of the FS method. When the URLLC packet load is high, we show that UPER can improve the reliability performance up to 54% compared with other methods. Index Terms-Spectrum management, ultra reliable and low latency communications, coexisting systems. I. INTRODUCTIONU LTRA-RELIABLE and low latency communications (URLLC) of the fifth generation (5G) wireless communications aim for providing time-critical machine-to-machine or human-to-machine vertical applications, such as factory automation, vehicular communications, and augmented reality, etc., [1]-[4]. Most URLLC services require 99.999% reliability performance within 1 msec latency in the data plane [5], [6]. Remote monitoring of patient's the vital signals is an important human-to-machine URLLC applications use case. On the other hand, intelligent transportation systems is an important machine-to-human URLLC use case [7], where

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Signal-to-noise ratio (SNR) estimation is an important proposed estimator is unbiased at low and high SNRs. The technique in receiver design for wireless communications. In the transmission and receiving system model of our estimator is receivers, many algorithms require SNR information to achieve depicted in Section II. In Section III, four existing SNR optimal performance. In this paper, an autocorrelation based p~~~~ẽstimators are reviewed. One is iterative maximum SNR estimator is proposed. This method utilizes the correlation estimator. One is iterate maximu properties of symbol sequence and noise sequence to distinguish likelihood SNR estimator. The others are based on method the signal power from the noise power. According to the of moments. Our proposed estimator is also introduced in simulation results, mean and normalized mean-square-error this section. Section IV shows the simulation results of the performance of the proposed SNR estimator is better than that of mean and mean-square-error performance of the proposed the conventional SNR estimators.estimator. Finally, in Section V, conclusion is drawn.

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A subspace-based blind channel estimation algorithm with cyclic prefix is proposed in this paper. A systematic approach is used to construct a new signal matrix in the proposed algorithm. Compared with conventional blind channel estimation algorithm, the proposed algorithm has lower computational complexity and higher probability of full row rank for the corresponding signal matrix. In addition, fewer OFDM symbols can be used to satisfy the necessary condition for achieving a full-row-rank signal matrix. Simulation results show that the proposed algorithm outperforms conventional methods in mean-squared error and bit error rate under static channel. Even with a smaller number of received OFDM symbols, the proposed algorithm can perform well. I. INTRODUCTION Orthogonal frequency division multiplexing (OFDM) [1]is a popular transmission technique in wireless communication systems due to its advantages of high spectrum efficiency and high transmitted data rate. In an OFDM system, it is robust to frequency selective fading because a wideband spectrum can be divided into many narrowband subchannels by subcarriers. The fading effects on each subcarrier can be regarded as frequency non-selective. In addition, a guard interval is usually added to OFDM symbols. If the guard interval is larger than the maximum channel delay, OFDM signal can avoid inter-symbol interference (ISI).To obtain better performance in OFDM systems, coherent demodulation and accurate estimation of the channel impulse response (CIR) are required. Therefore, channel estimation is mandatory and important in OFDM systems. The channel estimation can be categorized into two kinds by training signals existing or not. Training-based channel estimation algorithms [2], [3] need extra pilot tones or pilot symbols. On the other side, blind channel estimation algorithms need not any additional training signal. The blind channel estimation algorithms can also be divided into non-subspace-based [4] or subspace-based [5], [6]. In this paper, we only focus on subspace-based blind channel estimation methods. Recently,