EM-Based sequence estimation for wireless systems with orthogonal transmit diversity
Pusane, Ali Emre
MetadataTüm öğe kaydını göster
In this paper, an optimum sequence estimation algorithm for wireless systems with Alamouti's two transmitter diversity in the presence of multipath fading is proposed. The algorithm is based on a jointly iterative channel and sequence estimation according to the maximum likelihood (ML) criterion, using the Expectation-Maximization (EM) algorithm employing M-PSK modulation scheme with additive Gaussian noise. The discrete multipath channel is represented in terms of the channel gains from each transmit antenna to the receive antenna. EM algorithm derived estimates jointly the complex channel parameters of each channel And the data sequence transmitted, iteratively, which converges to the true ML solution. The channel estimation is achieved in a simple way through the iterative equations by decoupling of the signals transmitted from different antennas. The algorithm is applied to the trellis coded modulation systems and efficiency of the algorithm proposed has been shown by the computer simulations. Simulation results show that the EM algorithm converges quickly for fast fading channels. The performance of the EM-based decoder approaches that of the ML receiver which has perfect knowledge of the channel.
Başlık, yazar, küratör ve konuya göre gösterilen ilgili öğeler.
Panayırcı, Erdal (IEEE, 2000)In this paper, a computationally efficient algorithm is presented for joint maximum likelihood (ML) timing and carrier phase synchronization of OFDM systems employing M-PSK modulation scheme with additive Gaussian noise, ...
Panayırcı, Erdal; Georghiades, Costas N. (IEEE, 2000)In this paper, a computationally efficient algorithm is presented for joint maximum likelihood (ML) timing and carrier phase estimation of OFDM systems employing M-PSK modulation scheme with additive Gauissian noise, based ...
Öner, Mustafa Mengüç; Mühlhaus, Michael S.; Dobre, Octavia Adina; Jkel, Holger U.; Jondral, Friedrich K. (IEEE, 2012-09-03)Automatic classification of the modulation type of an unknown communication signal is a challenging task, with applications in both commercial and military contexts, such as spectrum surveillance, cognitive radio, and ...