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  • Investigation of Non-binary Block Codes Soft-decision Decoding Methods in Communication Systems with Nonparametric Reception

Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Dmitrii Titov
Investigation of Non-binary Block Codes Soft-decision Decoding Methods in Communication Systems with Nonparametric Reception
Data Science
(Master’s programme)
2017
This thesis deals with the problem of enabling reliable communication in communication systems operating under severe mixed jamming. This problem can be of great importance for both researchers and manufacturers of the next generation communication systems in the nearest future due to the growing demand for the opportunities that are offered by wireless communications and the limited access to frequency bands due to both commercial considerations and regulation restrictions. In particular in this thesis a DHA FH OFDMA system employing non-coherent FSK, nonparametric reception and error correction coding is considered. This approach attracted considerable attention lately. A serious issue associated with this approach is the decoding complexity. The decoding algorithms that were proposed so far have prohibitively large complexity for all but the low rate codes and therefore only low rate codes can be considered for practical applications. In this thesis the possibility of using sequential decoding on syndrome trellises to solve this problem is investigated. In particular a decoding algorithm based on a classical Zigangirov- Jelinek sequential algorithm is proposed. In order to adapt the sequential decoding concept to the case of nonparametric reception a novel reception technique that combines Normalized Envelope Detection (NED) and Rank Sum Detection has been proposed. The effectiveness of the proposed solution is verified by simulation. The simulation results demonstrate that the proposed solution can be used to provide reliable communication even under severe mixed jamming. Furthermore the results obtained confirm that the complexity of the proposed solution is not prohibitively high as opposed to the decoding algorithms that boil down to exhaustive search. Thus the proposed algorithm can be considered as competitive alternative to the solutions that has been proposed so far and possible candidate for practical implementation.

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