Isbn: 9783659637438 - map decoding of correlated sources: studied over soft-decision orthogonal multiple access fading channels with memory (6 risultati)

Taschenbuch. Condizione: Neu. MAP Decoding of Correlated Sources | Studied over Soft-Decision Orthogonal Multiple Access Fading Channels with Memory | Seyed Parsa Beheshti | Taschenbuch | 184 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659637438 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We consider the joint source-channel coding (JSCC) problem where the real valued outputs of two correlated memoryless Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying any error correcting code, over a multiple access channel (MAC) which consists of two orthogonal point-to-point time-correlated Rayleigh fading sub-channels with soft-decision demodulation. At the receiver side, a joint sequence maximum a posteriori (MAP) detector is used to exploit the correlation between the two sources as well as the redundancy left in the quantizers' indices, the channel's soft-decision outputs, and noise memory. The MAC's sub-channels are modeled via non-binary Markov noise discrete channels recently shown to effectively represent point-to-point fading channels. Two scenarios are studied in this book. In the first scenario, the sources are memoryless and generated according to a bivariate Gaussian distribution with a given correlation parameter. In the second scenario, the sources have memory, captured by a changing correlation parameter which is governed by a two state first order Markov process. 184 pp. Englisch.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Beheshti Seyed ParsaSeyed Parsa Beheshti received his B.Sc. in Electrical Engineering from the Sharif University of Technology, Tehran, Iran in 2012.In 2014, he graduated with the M.A.Sc. degree from the ECE department at the Queen s.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -We consider the joint source-channel coding (JSCC) problem where the real valued outputs of two correlated memoryless Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying any error correcting code, over a multiple access channel (MAC) which consists of two orthogonal point-to-point time-correlated Rayleigh fading sub-channels with soft-decision demodulation. At the receiver side, a joint sequence maximum a posteriori (MAP) detector is used to exploit the correlation between the two sources as well as the redundancy left in the quantizers' indices, the channel's soft-decision outputs, and noise memory. The MAC's sub-channels are modeled via non-binary Markov noise discrete channels recently shown to effectively represent point-to-point fading channels. Two scenarios are studied in this book. In the first scenario, the sources are memoryless and generated according to a bivariate Gaussian distribution with a given correlation parameter. In the second scenario, the sources have memory, captured by a changing correlation parameter which is governed by a two state first order Markov process.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 184 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We consider the joint source-channel coding (JSCC) problem where the real valued outputs of two correlated memoryless Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying any error correcting code, over a multiple access channel (MAC) which consists of two orthogonal point-to-point time-correlated Rayleigh fading sub-channels with soft-decision demodulation. At the receiver side, a joint sequence maximum a posteriori (MAP) detector is used to exploit the correlation between the two sources as well as the redundancy left in the quantizers' indices, the channel's soft-decision outputs, and noise memory. The MAC's sub-channels are modeled via non-binary Markov noise discrete channels recently shown to effectively represent point-to-point fading channels. Two scenarios are studied in this book. In the first scenario, the sources are memoryless and generated according to a bivariate Gaussian distribution with a given correlation parameter. In the second scenario, the sources have memory, captured by a changing correlation parameter which is governed by a two state first order Markov process.…