Pilot-Aided Sequential Monte Carlo Estimation of Phase Distortions and Transmitted Symbols in Multicarrier Systems

We address the challenging problem of the joint estimation of transmitted symbols and phase distortions in standardized multicarrier systems, including pilot or virtual subcarriers. These subcarriers create time correlation on the useful transmitted OFDM signal that we propose to take into account by an autoregressive model. Because the phase distortions are nonlinear, we set the joint estimation algorithm on the framework of the Sequential Monte Carlo methods. Simulation results are provided in terms of bit error rate (BER) and mean square error (MSE); they highlight the efficiency and the robustness of the estimator.Peer Reviewe

IR-UWB Cognitive Radio System Based on the M-OAM Modulations

Communication systems plays decisive role in the evolution of the transport field, and during the last years, requests to have the safest and most efficient transport modes has been expressed by users. The use of the ultra-wideband (UWB) technique can satisfy such a need. UWB offers numerous advantages such as: the large offered bandwidth, the signal flexibility, the quality of service, the transmission power and the limited cost. In this paper, a new system dedicated to the domain of transport, based on UWB technology is presented. The implementation of the new modulation M-OAM (Orthogonal Amplitude Modulation) which is based on the use of original mathematical tools called Modified Gegenbauer functions (MGF), derived from orthogonal polynomials, increases the data rate flow and enhances the robustness ensured by UWB communication for multimedia and transport applications. With the purpose of improving the functioning of the communication system and ensuring the very high data rate, this work consists in combination of UWB and cognitive radio technologies in order to develop an adapted and efficient universal receiver. This receiver is able to detect the signal arrival and identify the coding parameters used in the transmission so as to be adapted to them automatically. The receiver requires intelligent capacities of observation, learning and decision, therefore, our conception is based on the concept of the cognitive radio which is characterized with the ability to detect the presence of the signal. In this paper, we present the principle of the modulation M-OAM, the waveforms used in our system, and the method which allows the receiver to identify the type of the used modulation

Particle Filter With Hybrid Importance Function For Joint Symbol Detection And Phase Tracking

In digital communication, phase distortions introduced by local oscillators is one of the major concerns in designing low-cost high frequency wireless communication systems. Hence, for phase tracking and symbol detection, we propose an original algorithm which performs both phase tracking and symbol detection by a particle filtering based on the hybrid importance function. Performances of this algorithm are analyzed and compared to phaselocked loop performances in terms of bit error rate and mean square error. Asymptotic posterior Cramer-Rao bound is also derived to show performances of the optimum receiver

Pilot-Aided Sequential Monte Carlo Estimation of Phase Distortions and Transmitted Symbols in Multicarrier Systems

We address the challenging problem of the joint estimation of transmitted symbols and phase distortions in standardized multicarrier systems, including pilot or virtual subcarriers. These subcarriers create time correlation on the useful transmitted OFDM signal that we propose to take into account by an autoregressive model. Because the phase distortions are nonlinear, we set the joint estimation algorithm on the framework of the Sequential Monte Carlo methods. Simulation results are provided in terms of bit error rate (BER) and mean square error (MSE); they highlight the efficiency and the robustness of the estimator

Non-Pilot-Aided Sequential Monte Carlo Method to Joint Signal, Phase Noise, and Frequency Offset Estimation in Multicarrier Systems

We address the problem of phase noise (PHN) and carrier frequency offset (CFO) mitigation in multicarrier receivers. In multicarrier systems, phase distortions cause two effects: the common phase error (CPE) and the intercarrier interference (ICI) which severely degrade the accuracy of the symbol detection stage. Here, we propose a non-pilot-aided scheme to jointly estimate PHN, CFO, and multicarrier signal in time domain. Unlike existing methods, non-pilot-based estimation is performed without any decision-directed scheme. Our approach to the problem is based on Bayesian estimation using sequential Monte Carlo filtering commonly referred to as particle filtering. The particle filter is efficiently implemented by combining the principles of the Rao-Blackwellization technique and an approximate optimal importance function for phase distortion sampling. Moreover, in order to fully benefit from time-domain processing, we propose a multicarrier signal model which includes the redundancy information induced by the cyclic prefix, thus leading to a significant performance improvement. Simulation results are provided in terms of bit error rate (BER) and mean square error (MSE) to illustrate the efficiency and the robustness of the proposed algorithm

A novel multi-view pedestrian detection database for collaborative intelligent transportation systems

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