In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval CHANNEL by applying the approach of statistical energy analysis. Correct ESTIMATION of sound transmission loss in an air conditioning CHANNEL is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound ESTIMATION.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning CHANNELs according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped CHANNELs stretched in different lengths.

In this paper optimization of frequency offset ESTIMATION technique based on CHANNEL ESTIMATION, which is desirable for frequency selective CHANNELs and hasfast convergence speed, for using in HF CHANNEL is addressed. Because of time variations coherence time in HF CHANNEL is short, which leads to a severe degradation in the performance of above technique in this CHANNEL. An optimization of said technique is proposed in which after removing coarse frequency offset ESTIMATION and knowing residual frequency offset range, incorrect ESTIMATIONs can be removed and others can be averaged to give final correct estimate. Simulation is conducted underCHANNEL parameters with respect to MIL-STD-188-110B. the results show that proposed optimization result in improved performance of frequency offset ESTIMATION technique based on CHANNEL ESTIMATION.

In order to exploit the advantages of the massive MIMO systems, it is vital to apply the CHANNEL ESTIMATION task. The huge number of antennas at the base station of a massive MIMO system produces a large set of CHANNEL paths which requires to be estimated. Therefore, the CHANNEL ESTIMATION in such systems is more troublesome. In this paper, we propose to leverage the temporal joint sparsity of the massive MIMO CHANNELs to offer a more accurate CHANNEL ESTIMATION. To attain this goal, we would model the problem to exploit the spatial correlation among different antennas of the BS as well as the inter-user similarity of the CHANNEL supports. In addition, by assuming a slow time-varying CHANNEL, the supports of the CHANNEL matrices of various snapshots would be equal which enables us to impose the temporal joint sparsity on the CHANNEL submatrices. The simulation results validate the efficiency and superiority of the suggested scheme over its rivals.

This paper proposes a novel approach based on the copula models for estimating Millimeter-Wave CHANNEL parameters with Rician fading in a correlated MIMO system. Even though the use of these waves faces numerous challenges, having an accurate ESTIMATION of their parameters would be a crucial notion for the improved performance of this CHANNEL. Since the considered system in this paper is a MIMO system with nearby transmitter antennas, the components of the received signals are correlated. However, a general model is not available for this kind of correlation. By taking into account the correlation, this model enables a precise Joint Probability Density Function (JPDF) by employing copula models for the received signals in the antennas. We also obtain more precise CHANNEL parameter estimates using this density function. The multi-path fading parameters in a MIMO system and the correlation coefficients between the transmitter and receiver antennas are both presented in this paper. Some simulations are employed to assess the validity and reliability of estimating Millimeter-Wave CHANNEL parameters in a MIMO system.

Since a secure voice or data session is very important in military HF communication, it needs a HF modem designed with cipher capability. Whereas multipath and Doppler affection are very adverse in HF sky-wave mode, so the production of a robust modem is essential for military application to compensate CHANNEL distortion. Then CHANNEL ESTIMATION block is very important and this paper proposes an enhanced method for CHANNEL ESTIMATION. The OFDM pilot based CHANNEL ESTIMATION with wiener filtering is a robust method that estimates CHANNEL excellently with minimum pilot density. The result show that proposed method can increase bit rate with decrement in pilot density, which allows use of a stronger CHANNEL coding and subsequently a lower bit error rate. Simulation shows that the bit-error rate of the proposed method passes the American military standards.

Millimeter wave communication (mmWC) is a promising volunteer for 5G communication systems with high data rates. To subdue the CHANNEL propagation characteristics in this frequency band, high dimensional antenna arrays need to be deployed at transceiver. Employing such a deployment, prevents to use of ADC or RF chain in each branch of MIMO system because of power constraints. Thus, Such systems impose to have a hybrid analog/digital precoding/combining architecture. Hence, CHANNEL ESTIMATION revision seems to be essential. This paper propose new algorithms to estimate the mmW CHANNEL by exploiting the sparse nature of the CHANNEL and finding the subspace of received signal vectors based on MUSIC. By combining the multiple measurement vector (MMV) concept, MISIC, subspace augmentation (SA) and two-stage orthogonal subspace matching pursuit (TOSMP) approaches, we try to recover the indices of non-zero elements of an unknown CHANNEL matrix accurately even under the defective-rank condition. These indices are called support in the context. Simulation results indicate MUSIC-based approaches offer lower ESTIMATION error and higher sum rates compared with conventional MMV solutions.

Time Reversal (TiR) technique mitigates the complexity of receiver in UWB indoor CHANNELs, but is very sensitive to the CHANNEL ESTIMATION error. The effect of CHANNEL imperfection on TiR technique is considered in this paper. At first, the Bit Error Probability (BEP) of the TiR-UWB communication system under the assumptions of the simple Matched Filter (MF) receiver with the CHANNEL ESTIMATION errors is derived in closed-form. Moreover, based on optimal MMSE estimator receiver, a pre-filter is calculated in closed-form to improve the performance of the TiR-UWB system in an imperfect CSI scenario. Furthermore, a two stage iteration-based algorithm is developed at transmitter to calculate a pre-filter in MF receiver. This improved algorithm causes the CHANNEL ESTIMATION error tends to zero in some steps for the TiR-UWB system with MF. The initial value for this iteration-based improved algorithm is considered to be closed form pre-filter calculated in TiR-UWB system with optimal MMSE estimator. Finally, exhaustive simulations are done to demonstrate the performance advantage attained by the improved algorithm.

Massive Multiple-Input Multiple-Output (mMIMO) is a promising approach for the next generation wireless telecommunication systems. In these systems, having a suitable approach for CHANNEL ESTIMATION is mandatory in order to increase the data rate and spectral efficiency. Distributed Compressed Sensing (DCS) is prominent in extracting joint sparse CHANNEL state information (CSI). Here, we have utilized Alternating Direction Method of Multipliers (ADMM) approach to generate quasi-orthogonal pilot sequences, in order to improve the CHANNEL ESTIMATION approach based on DCS approach. In simulation results, it is represented that ADMM-based pilot sequences are very powerful in extracting CSI of the joint sparse CHANNEL ensembles.