Channel Estimation

The problem of detecting signals in a Rayleigh fading channel is a constant challenge for conventional communication receivers. Traditional maximum likelihood (ML) detectors rely on precise mathematical models of the channel, which are affected by actual fading. This paper presents a new signal detector using a CNN which classifies the symbols directly from the image of the constellation diagram at the receiver. Both binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) modulations are tested over a Rayleigh fading channel and additive white Gaussian noise (AWGN) over an SNR range of 0 to 30 dB. The CNN classifier is given the following two inputs as follows: the received signal constellation diagram (RSCD) and the channel-equalized signal constellation diagram (CED). In this work, three image resolutions were considered: 30×30, 50×50 and 100×100 pixels. Input normalization impact on the bit error rate (BER) is also explored. For both BPSK and QPSK modulations, results indicate that CNN Scenarios II (50×50) and III (100×100) provide BER performance similar to that of the ML detector. Normalization decreases the dispersion of pixels in the constellation diagram and always enhances the classification rate. The results validate the feasibility of image-based CNN classification over a fading wireless channel for replacing the traditional ML detection.

First unequal error protection (UEP) proposals date back to the 1960's (Masnick and Wolf; 1967), but now with the introduction of scalable video, UEP develops to a key concept for the transport of multimedia data. The paper presents an overview of some new approaches realizing UEP properties in physical transport, especially multicarrier modulation, or with LDPC and Turbo codes. For multicarrier modulation, UEP bit-loading together with hierarchical modulation is described allowing for an arbitrary number of classes, arbitrary SNR margins between the classes, and arbitrary number of bits per class. In Turbo coding, pruning, as a counterpart of puncturing is presented for flexible bit-rate adaptations, including tables with optimized pruning patterns. Bit- and/or check-irregular LDPC codes may be designed to provide UEP to its code bits. However, irregular degree distributions alone do not ensure UEP, and other necessary properties of the parity-check matrix for providing UEP are...

An underdetermined system of linear equation has infinitely number of answers. To find a specific solution, regularization method is used. For this propose, we define a cost function based on desired features of the solution and that answer with the best matches to these function is selected as the desired solution. In case of sparse solution, zero-norm function is selected as the cost function. In many engineering cases, there is side information which are omitted because of the zero-norm function. Finding a way to conquer zero-norm function limitation, will help to improve estimation of the desired parameter. In this regard, we utilize maximum a posterior (MAP) estimation and modify the prior information such that both sparsity and side information are utilized. As a consequence, a framework to utilize side information into sparse representation algorithms is proposed. We also test our proposed framework in orthogonal frequency division multiplexing (OFDM) sparse channel estimation problem which indicates, by utilizing our proposed system, the performance of the system improves and fewer resources are required for estimating the channel.

Optimized positioning of antenna to obtain the best beam forming solution is adopted in this research. Non-uniform linear array-based beamforming algorithms have the challenge of placing the array of antennas in positions that would implement best beamforming outputs. This paper attempts to obtain the optimized beam forming by tuning the sparse Bayesian learning based algorithm. The parameters used for tuning involve choosing the hybrid basis vector for creating the steering vector while at the same time developing the optimized position of the antennas. Basis vectors are the building blocks of the steering vector developed for the beamforming algorithm that finds the angle of arrival in antennas. Reconfiguration of antennas is carried out using particle swarm optimization (PSO) algorithm and the basis vectors are generated using two different ways. One by cumulating similar basis vectors and another by cumulating two different basis vectors. The performance of accurate detection of angle of arrival in the beamforming algorithm is analyzed and results are discussed. This basis vector and antenna distance optimization is adopted on the sparse Bayesian learning paradigm. Performance evaluation of these optimizations in the algorithm is realised by validating the mean square error (MSE) versus signal to noise ratio (SNR) graphs for both the cumulative basis vector and hybrid basis vector cases.

Orthogonal frequency division multiplexing (OFDM) is a transmission system that uses multiple orthogonal carriers that are sent out at the same time. OFDM is a technique for mobile and wireless communication that has high-efficient frequency utilization, high data-rate transmission, simple and efficient implementation using the fast Fourier transform (FFT) and the inverse fast Fourier transform (IFFT), and reduces inter symbol interference (ISI) by inserting cyclic prefix (CP). One of the most important approaches in an OFDM system is channel estimation. In this paper, the orthogonal frequency division multiplexing system with the Rayleigh channel module is analyzed for different areas. The proposed approach used large numbers of subcarriers to transmit the signals over 64-QAM modulation with pilot add channel estimation. The accuracy of the OFDM system is shown in the measuring of the relationships of peak power to the noise ratio and bit error rate.

In this paper the angular power spectrum exhibited under a three-dimensional (3-D) Gaussian scatter distribution at fixed observation points in space is investigated. Typically, these correspond to the mobile and base units respectively. Unlike other spatial channel models, the derived model accounts for the distance to each scatterer from the observation point and transforms distances into power values under the assumption of free-space propagation. The proposed 3-D spatial channel model follows a non-central approach in terms of the scatter distribution in space, which means that the angular power field at the base unit need not be due to a scatter distribution centered exactly at the mobile. Derivations are provided for the angular and power domains and as shown by conditioning the distance, the angular field reduces to the von-Mises Fisher distribution. Most importantly, this work undertakes the problem of a Gaussian angular power spectrum observed in radio propagation channel measurements and provides a formal theoretical framework of the experimental investigations found in literature. The proposed model denotes that a Gaussian scatterer distribution in space gives rise to a Gaussian angular power spectrum and a Gaussian angular power density in the azimuth and elevations fields. The proposed 3-D spatial channel model might be used for evaluating the performance of current and future multi-element wireless communication networks.

In this paper, a Virtual Drive Testing (VDT) methodology for a MIMO LTE Vehicle to Infrastructure (V2I) urban scenario is proposed and compared with actual road drive tests. We have developed a unique and generic radio performance analysis process based on 3D ray traced channel models, theoretic or measured antenna patterns, RF channel emulation and hardware-in-the-loop radio measurements. A 3D ray-tracing channel model is used to predict the spatial and temporal multipath ray components of the radio propagation channel between an LTE BS and the vehicle. Measured LTE vehicular antenna patterns were then applied using a spatial and polarimetric convolution process. The resulting channels were streamed into a Keysight PropSim F8 channel emulator, which was programmed to communicate with the multi-channel LTE BSs emulator and a Samsung S5 mobile client performing a handover procedure. The VDT emulation method proposed in this paper is shown to be reliable and repeatable and the accuracy of the emulated throughput agreed well with real measurements for MIMO operation.

In this paper the angular power spectrum exhibited under a three-dimensional (3-D) Gaussian scatter distribution at fixed observation points in space is investigated. Typically, these correspond to the mobile and base units respectively. Unlike other spatial channel models, the derived model accounts for the distance to each scatterer from the observation point and transforms distances into power values under the assumption of free-space propagation. The proposed 3-D spatial channel model follows a non-central approach in terms of the scatter distribution in space, which means that the angular power field at the base unit need not be due to a scatter distribution centered exactly at the mobile. Derivations are provided for the angular and power domains and as shown by conditioning the distance, the angular field reduces to the von-Mises Fisher distribution. Most importantly, this work undertakes the problem of a Gaussian angular power spectrum observed in radio propagation channel measurements and provides a formal theoretical framework of the experimental investigations found in literature. The proposed model denotes that a Gaussian scatterer distribution in space gives rise to a Gaussian angular power spectrum and a Gaussian angular power density in the azimuth and elevations fields. The proposed 3-D spatial channel model might be used for evaluating the performance of current and future multi-element wireless communication networks.

A demand for high speed mobile wireless communications is quickly mounting. Wireless communication is the key part of research with growing demand of high data rate applications at a low cost. Orthogonal Frequency Division Multiplexing (OFDM) is a promising answer for this problem. It is a multi-carrier modulation and as well as a multiplexing technique proposed for 3G, 4G, LTE; a systems to support high data rate applications in a fading environment. There are many problems linked with the multicarrier transmission like phase variations, timing offset, large peak to average power ratio (PAPR), frequency offset etc. in which Carrier Frequency Offset (CFO) is one of the major issues. This frequency offset breaks the orthogonality among the sub-carriers and hence causes inter-carrier interference (ICI) in the OFDM symbol, which seriously degrades the overall system performance. In this thesis; we have studied and analyzed CFO upon signal to noise ratio (SNR), different techniques to estimate CFO and its effect in detailed for OFDM symbol. The estimation techniques cover both domains; time and frequency for OFDM system. The three types of CFO methods as: CP, Moose, and Classen are compared in MATLAB simulation. In Cyclic Prefix (CP) method, the CFO can be found from the phase angle of the product of CP and corresponding rear part of the OFDM symbol. In CFO estimation using Classen method, the CFO estimation range can be increased by reducing the distance between two blocks of samples for correlation. This was made possible using training symbol that are repetitive with shorter period. The principles of the eight different methods are reviewed; but among these, three methods has been compared in term of Mean Square Error (MSE) which is verified through MATLAB simulation. From simulation results, the Classen method has best performance and CP method has worst performance because of easy implementation and no loss of bandwidth efficiency. Although, Moose method has similar performance as Classen method in terms of MSE.

In this paper, we present two Data-Aided channel estimators for Continuous Phase Modulation (CPM) in the case of transmissions over doubly-selective channels. They both capitalize on the Basis Expansion Model (BEM), widely used for OFDM systems and for Single Carrier transmission with linear modulation. However, in the case of CPM signals, we need to work on a over-sampled received signal (fractionallyspaced representation) as the equalization techniques are also working on the over-sampled received signal. The first one is a classical Least Squares (LS) estimation of the BEM parameters whereas the second channel estimator introduces first a parametric dependence on the paths delays. Indeed, in the case where those delays are known (by estimation or by geometrical consideration as for the aeronautical channel by satellite), the second LS estimation on the BEM parameters is improved and less computationally demanding. Simulations results are provided and show good performance of our parametric LS estimation.

In this paper, we present a generalized polyphase representation for Continuous Phase Modulation (CPM) signals suited to the detection over frequency-selective channels. We first develop two different equalizers based on this representation and relate them to the State of Art. We also derive a Least Squares (LS) channel estimation and an improved LS estimation using a priori on the channel. Simulation results show the equivalence between existing equalizers and also show that our channel estimation leads only to a small degradation in term of Bit Error Rate (BER) in the case of an aeronautical communication over a satellite link.