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Yayın Cooperative strategies and achievable rates for two user OFDMA channels(IEEE-INST Electrical Electronics Engineers Inc, 2011-12) Bakım, İsmail Sezi; Kaya, OnurWe propose three encoding strategies for a two user cooperative Orthogonal Frequency Division Multiple Access (OFDMA) system, based on block Markov superposition encoding (BMSE). We obtain the expressions for the resulting achievable rate regions for all three encoding strategies. We show that, by allowing for re-partitioning and re-encoding of the cooperative messages across subchannels, it is possible to better exploit the diversity created by OFDMA, and higher rates can be achieved. We demonstrate potential rate gains attained by cooperative OFDMA, through simulations.Yayın Power control for fading cooperative multiple access channels(IEEE, 2007-08) Kaya, Onur; Ulukuş, ŞennurFor a fading Gaussian multiple access channel with user cooperation, we obtain the power allocation policies that maximize the average rates achievable by block Markov superposition coding, subject to average power constraints. The optimal policies result in a coding scheme that is simpler than the one for a general multiple access channel with generalized feedback. This simpler coding scheme also leads to the possibility of formulating an otherwise non-concave optimization problem as a concave one. Using the perfect channel state information available at the transmitters to adapt the powers, we demonstrate gains over the achievable rates for existing cooperative systems.Yayın Incremental construction of classifier and discriminant ensembles(Elsevier Science Inc, 2009-04-15) Ulaş, Aydın; Semerci, Murat; Yıldız, Olcay Taner; Alpaydın, Ahmet İbrahim EthemWe discuss approaches to incrementally construct an ensemble. The first constructs an ensemble of classifiers choosing a subset from a larger set, and the second constructs an ensemble of discriminants, where a classifier is used for some classes only. We investigate criteria including accuracy, significant improvement, diversity, correlation, and the role of search direction. For discriminant ensembles, we test subset selection and trees. Fusion is by voting or by a linear model. Using 14 classifiers on 38 data sets. incremental search finds small, accurate ensembles in polynomial time. The discriminant ensemble uses a subset of discriminants and is simpler, interpretable, and accurate. We see that an incremental ensemble has higher accuracy than bagging and random subspace method; and it has a comparable accuracy to AdaBoost. but fewer classifiers.Yayın Adaptive Kalman receiver for OFDM systems with transmit diversity in mobile wireless channels(Walter De Gruyter GMBH, 2004-12) Şen, Adnan; Çırpan, Hakan Ali; Panayırcı, ErdalA new joint channel tracking and symbol detection scheme is proposed in this paper for pilot symbol assisted transmit diversity OFDM systems by exploiting the correlation of the adjacent subchannels. Modelling the channel frequency response of every subcarrier corresponding to each transmit antenna as random processes, we employ Kalman filters for both channel tracking and subsequent decoding with diversity gain. Among different stochastic models, the AR model is adopted herein for channel dynamics. Since the proposed adaptive receiver uses two Kalman filters to track the variations of the channel and subsequently to detect the information symbols, they are combined in the coupled receiver structure. Finally the performance of the proposed method is studied through experimental results.
