In next-generation wireless communication and 5G-based mobile communication, error-free communication with high transmission efficiency and reliability in a limited bandwidth is required along with diverse services. Highly reliable communication is difficult with wireless communication systems due to surrounding environment, movement of transmitters and receivers, and various noises. Channel coding technology should be applied to overcome these problems. In addition, an algorithm that can overcome the loss of transmission efficiency caused by the application of channel coding technology should be applied. However, since there is a trade-off relationship between improved transmission rates and performance, it is difficult to satisfy both. Thus, recently, methods to improve both transmission rates and performance simultaneously are being studied. Accordingly, this dissertation proposes a channel coded turbo equalization model that enables improved performance in a high transmission wireless communication system with improved transmission efficiency.
The topic of this dissertation can be largely divided into two aspects: performance improvement and high transmission efficiency.
First, a turbo equalization model combined with iterative codes for performance improvement in a wireless communication system was investigated, and a soft decision-based iterative coding schemes such as the convolutional code-based BCJR, turbo codes and LDPC codes were introduced. Subsequently, the performance of these coding schemes was comparatively analyzed. The BER performance analysis through the simulation showed that the LDPC code was approximately 1.2 [dB] at BER , which was the closest to the Shannon's channel capacity limit. In addition, the LDPC coding method was suggested as a channel coding scheme suitable for high-speed wireless communication by comparatively analyzing the characteristics of each coding scheme for complexity, decoding speed and performance.
Second, the algorithm that achieved high transmission efficiency was investigated. Conventional high-transmission efficiency algorithms such as punctured, FTN and MIMO algorithms were introduced, and these three were comparatively analyzed from the perspective of the same transmission rate. In addition, MIMO-FTN and P-FTN algorithms, which combined each of the punctured and MIMO algorithms with the FTN algorithm to maximize the transmission efficiency, were proposed. The performances of the proposed algorithms were analyzed through the simulation from the perspective of the same transmission rate, and the W-ZF based MIMO-FTN algorithm was found to be the best. However, the performance degradation due to the application of FTN occurred, and subsequently, a turbo equalization model of FTN signals based UEP was proposed to overcome this problem.
The UEP scheme was applied to the MIMO-FTN algorithm to maximize the improvement in transmission rates, and the UEP-FTN transmission scheme applying the OFDM scheme in multi-path channels was proposed. The performance of the proposed UEP-based FTN transmission scheme was analyzed through simulation, which showed that the application of the UEP scheme led to the improved performance. Based on this study, a turbo equalization model to achieve the performance improvement and high transmission efficiency was proposed.
In addition, not limiting its usage only in the surface wireless communication but expanding its scope to underwater acoustic communication, the way to apply the model to underwater acoustic communication was investigated. Based on the decoded data and the turbo equalization-based UEP-FTN model that improved the transmission efficiency and performance in underwater acoustic communication, a method to calibrate the frequency and phase of the following packet was proposed. Its efficiency was verified through the actual underwater experiment at Gyeongcheon Lake in Mungyeong-si, Geyongsangbuk-do.
The results of the experiment showed that the proposed method worked efficiently.