Title :
Multiple-symbol differential detection of M-DPSK using neural network
Author :
Pham, C. ; Ogunfunmi, T.
Author_Institution :
Lockheed Missiles & Space Co. Inc., Sunnyvale, CA, USA
fDate :
27 Jun- 2 Jul 1994
Abstract :
In this paper, the application of artificial neural network (ANN) to differential detection receiver for M-ary differential encoded phase-shift keying (MDPSK) utilizing multiple symbols is investigated. It is shown that the performance of this non-coherent receiver not only approaches its coherent receiver counterpart, but its structure is also simple and easy to implement in hardware. Some other desirable properties are obtained, such as no training process involved in this application, fast computational time and high accuracy. Simulation results are made to illustrate its superior performance
Keywords :
Hopfield neural nets; demodulation; differential phase shift keying; maximum likelihood detection; Hopfield neural network; M-DPSK; M-ary differential encoded phase-shift keying; maximum likelihood detection; multiple symbol differential detection; non-coherent receiver; AWGN; Artificial neural networks; Bit error rate; Counting circuits; Gas detectors; Hardware; Maximum likelihood detection; Missiles; Neural networks; Phase detection;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374908
