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In this paper, an efficient approach is proposed to track the double-selected multipath channel for a Multiple-Input-Multiple-Output Orthogonal-Frequency-Division-Multiplexing (MIMO-OFDM) system in the existence of both Gaussian and non-Gaussian noises interfering with reference signals. Using nonlinear complex Multiple Support Vector Machine Regression (M-SVR) methodology, fast-fading multipath channel...
In this paper the impact of exponential correlation model on massive multiple input multiple output (MIMO) channel estimation is analyzed using a large number of antennas in the base station (BS) and a user terminal. We consider pilot-based channel estimation in the UL channel. The Linear minimum mean square error (LMMSE) estimator is used to investigate the effect of correlation factor on the average...
In millimeter-wave massive multiple-input multiple-output systems, to decrease the large training overhead of traditional channel estimation techniques, compressive sensing (CS) is advocated for channel estimation by exploiting the channels' sparse nature. However, existing CS-based channel estimation (CSCE) methods have to deal with a large-size reconstruction problem for sparse channel recovery,...
MIMO-OFDM is commonly used for communication system because it provides high data rates and fading effect which is introduced by multipath propagation; the system is robust against it. In MIMO-OFDM, channel estimation is a crucial technique for the estimation of the transmitted signal bits upon the received signal bits. Designing pilot pattern is an important step to realize PSA-OFDM. For channel...
In this paper we assess the performance of Support Vector Machine Regression (SVR) based on Radial Basis Function (RBF) and Artificial Neural Network (ANN) based on Scaled Conjugate Gradient Backpropagation (SCG) algorithms to estimate the channel variations using the reference signal structure standardized for LTE Downlink system. Complex SVR and ANN where applied to estimate real channel environment...
Single Input Multiple Output (SIMO) Blind Channel Identification (BCI) using Subspace-based Methods, notably the Cross-Relations (CR) and Noise-Subspace (SS) Methods, are sensitive to selection of the channel order. Previous work on model order selection shows that at low SNR, accurate selection is not always possible, and in some cases, there is difficulty obtaining good estimates using any order...
Now-a-days, secure communication is a significant characteristic that should be proficient to accommodate increasing demand of wireless communication. The fundamental principle of secure communication is the extraction of secret key and keeping this secret. In this paper, we propose innovative approach for secret key extraction and reconciliation. We exploit channel reciprocity through relative calibration...
Massive MIMO systems, where base stations are equipped with hundreds of antennas, are an attractive way to handle the rapid growth of data traffic. As the number of users increases, the initial access and handover in contemporary networks will be flooded by user collisions. In this work, we propose a random access procedure that resolves collisions and also performs timing, channel, and power estimation...
We derive for the first time closed-form expressions for the Cramér-Rao lower bounds (CRLBs) of the joint channel phase, and carrier frequency offset (CFO) estimates from turbo-coded (TC) Pulse-amplitude modulation (PAM) and rectangular-QAM (RQAM) modulated signals over flat-fading channels. After wisely exploiting the properties of Gray mapping, we are able to simplify the log-likelihood...
In this paper, we have proposed an iterative space alternating generalized expectation maximization (SAGE) based semi-blind channel estimation technique for massive multiple-input multiple-output (MIMO) system in multi-cell pilot contamination prone scenario. The benefits of massive MIMO depend largely on the accuracy of channel state information (CSI) available at the base station (Transmitter)....
New waveform candidates are being investigated for the fifth generation wireless systems. Among the promising candidates, generalized frequency division multiplexing (GFDM) offers the flexibility to address a wide range of requirements (e.g. low latency, coarse synchronization, etc.). Due to the non- orthogonality of GFDM, the transmit signal subjects to inter-symbol and inter-carrier interference...
This paper presents an OFDMA channel estimation technique that jointly considers the effects of coarse timing error and multipath propagation. Many conventional approaches only consider an optimistic scenario where timing synchronization is perfect and each of the channel delays is an integer number of system samples. In realistic scenarios, timing offsets and echo delays are not integer multiples...
In this paper we consider a constant envelope pilot signal based carrier frequency offset (CFO) estimation in massive multiple-input multiple-output (MIMO) systems. The proposed algorithm performs spatial averaging on the periodogram of the received pilots across the base station (BS) antennas. Our study reveals that the proposed algorithm has complexity only linear in (the number of BS antennas)...
In this paper, two novel channel parameter estimation algorithms are proposed under the "wideband assumption" (WBA), where a wavefront varies significantly when traversing through the sensors of an array. The first is a covariance-based algorithm that utilizes the cross-covariance matrix between two subvectors of the received signal vector and its singular value decomposition to reconstruct...
This paper presents sparse Bayesian learning (SBL)-based estimation schemes for an approximately sparse wireless multipath channel impulse response (MCIR) in a space-time trellis coded (STTC) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. The proposed schemes consider space-time trellis encoding over consecutive OFDM symbols and employ the multiple...
We consider a remote estimation system formed by two sensors that access dependent observations and a remote estimator. Each sensor observes a private and a common random variable and must decide whether to attempt to transmit them to the estimator, which seeks to produce estimates of the private measurements of both sensors and the common observation. Information is transmitted from the sensors to...
In this paper a high performance least square solver is presented which use recursive Cholesky decomposition. Wireless communication systems require solving least square equations in order to obtain taps weights of the FIR filter. It is thus about to develop a fast and efficient algorithm for computation pseudo-inverse matrices. This paper also presents the recursive way to calculate the correlation...
In this paper, the estimation of a narrowband time-varying channel under the practical assumptions of finite block length and finite transmission bandwidth is investigated. It is shown that the signal, after passing through a time-varying narrowband channel reveals a particular parametric low-rank structure that can be represented as a bilinear form. To estimate the channel, we propose two structured...
This work investigates the impact of imperfect statistical information in the uplink of massive MIMO systems. In particular, we first show why covariance information is needed and then propose two schemes for covariance matrix estimation. A lower bound on the spectral efficiency (SE) of any combining scheme is derived, under imperfect covariance knowledge, and a closed-form expression is computed...
There has been growing interest in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems, which would likely employ hybrid analog-digital precoding with large-scale analog arrays deployed at wide bandwidths. Primary challenges here are how to efficiently estimate the large-dimensional frequency-selective channels and customize the wideband hybrid analog-digital precoders and combiners...
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