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Yayın Maximum likelihood blind channel estimation for space-time coding systems(Hindawi Publishing Corporation, 2002-05) Çırpan, Hakan Ali; Panayırcı, Erdal; Çekli, ErdinçSophisticated signal processing techniques have to be developed for capacity enhancement of future wireless communication systems, In recent years, space-time coding is proposed to provide significant capacity gains over the traditional communication systems in fading wireless channels. Space-time codes are obtained by combining channel coding, modulation, transmit diversity, and optional receive diversity in order to provide diversity at the receiver and coding gain without sacrificing the bandwidth. In this paper, we consider the problem of blind estimation of space-time coded signals along with the channel parameters. Both conditional and unconditional maximum likelihood approaches are developed and iterative solutions are proposed. The conditional maximum likelihood algorithm is based on iterative least squares with projection whereas the unconditional maximum likelihood approach is developed by means of finite state Markov process modelling. The performance analysis issues of the proposed methods are studied. Finally, some simulation results are presented.Yayın A sequential Monte Carlo method for blind phase noise estimation and data detection(IEEE, 2005) Panayırcı, Erdal; Çırpan, Hakan Ali; Moeneclaey, MarcIn this paper, a computationally efficient algorithm is presented for blind phase noise estimation and data detection jointly, based on a sequential Monte Carlo method. The basic idea is to treat the transmitted symbols as " missing data" and draw samples sequentially of them based on the observed signal samples up to time t. This way, the Bayesian estimates of the phase noise and the incoming data are obtained through these samples, sequentially drawn, together with their importance weights. The proposed receiver structure is seen to be ideally suited for high-speed parallel implementation using VLSI technology.Yayın Linear expansions for frequency selective channels in OFDM(Elsevier GMBH, 2006) Şenol, Habib; Çırpan, Hakan Ali; Panayırcı, ErdalModeling the frequency selective fading channels as random processes, we employ a linear expansion based on the Karhumen-Loeve (KL) series representation involving a complete set of orthogonal deterministic vectors with a corresponding uncorrelated random coefficients. Focusing on OFDM transmissions through frequency selective fading, this paper pursues a computationally efficient, pilot-aided linear minimum mean square error (MMSE) uncorrelated KL series expansion coefficients estimation algorithm. Based on such an expansion, no matrix inversion is required in the proposed MMSE estimator. Moreover, truncation in the linear expansion of channel is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We first exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE. We also provide performance analysis results studying the influence of the effect of SNR and correlation mismatch on the estimator performance. Simulation results confirm our theoretical results and illustrate that the proposed algorithm is capable of tracking fast fading and improving performance.Yayın Frequency selective fading channel estimation in OFDM systems using KL expansion(IEEE, 2005) Şenol, Habib; Çırpan, Hakan Ali; Panayırcı, ErdalThis paper proposes a computationally efficient, linear minimum mean square error (MMSE) channel estimation algorithm based on KL series expansion for OFDM systems. Based on such expansion, no matrix inversion is required in the proposed MMSE estimator. Moreover, truncation in the linear expansion of channel is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We provide performance analysis results studying the influence of the effect of SNR and correlation mismatch on the estimator performance. Simulation results confirm our theoretical results and illustrate that the proposed algorithm is capable of tracking fast fading and improving performance.Yayın Blind channel estimation for space-time coding systems with Baum-Welch algorithm(IEEE, 2002) Çırpan, Hakan Ali; Panayırcı, ErdalIn recent years, space-time coding is proposed to provide significant capacity gains over the traditional communication systems in fading wireless channels. In this paper, we consider the problem of blind estimation of the channel parameters along with space-time coded signals. Our proposed approach exploits the finite alphabet property of the space-time coded signals and is based on the unconditional signal model by treating the information sequence as stochastic I.I.D. sequences. The iterative Baum-Welch algorithm is then adapted to solve resulting unconditional ML optimization cost function. Finally, some simulation results are presented.Yayın Pilot-aided bayesian MMSE channel estimation for OFDM systems: Algorithm and performance analysis(IEEE, 2004) Şenol, Habib; Çırpan, Hakan Ali; Panayırcı, ErdalThis paper proposes a computationally efficient, pilot-aided minimum mean square error (MMSE) channel estimation algorithm for OFDM systems. The proposed approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and estimates uncorrelated series expansion coefficients. Moreover, optimal rank reduction is achieved in the proposed approach by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We first consider the stochastic Cramer-Rao bound and derive the closed-form expression for the random KL coefficients. We then exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE.
