ONE-MINIUM-ONLY BASIC-SET TRELLIS MIN-MAX DECODER ARCHITECTURE FOR NONBINARY LDPC CODE

Nonbinary low-density-parity-check (NB-LDPC) code outperforms their binary counterpart in terms of error-correcting performance and error-floor property when the code length is moderate. However, the drawback of NB-LDPC decoders is high complexity and the complexity increases considerably when increasing the Galois-field order. In this paper, an One-Minimum-Only basic-set trellis min-max (OMO-BS-TMM) algorithm and the corresponding decoder architecture are proposed for NBLDPC codes to greatly reduce the complexity of the check node unit (CNU) as well as the whole decoder. In the proposed OMO-BS-TMM algorithm, only the first minimum values are used for generating the check node messages instead of using both the first and second minimum values, and the number of messages exchanged between the check node and the variable node is reduced in comparison with the previous works. Layered decoder architectures based on the proposed algorithm were implemented for the (837, 726) NB-LDPC code over GF(32) using 90-nm CMOS technology. The implementation results showed that the OMO-BS-TMM algorithm achieves the almost similar error-correcting performance, and a reduction of the complexity by 31.8% and 20.5% for the whole decoder, compared to previous works. Moreover, the proposed decoder achieves a higher throughput at 1.4 Gbps, compared with the other state-of-the-art NBLDPC decoders.

Management of Wireless Communication Systems Using Artificial Intelligence-Based Software Defined Radio

The wireless communication system was investigated by novel methods, which produce an optimized data link, especially the software-based methods. Software-Defined Radio (SDR) is a common method for developing and implementing wireless communication protocols. In this paper, SDR and artificial intelligence (AI) are used to design a self-management communication system with variable node locations. Three affected parameters for the wireless signal are considered: channel frequency, bandwidth, and modulation type. On one hand, SDR collects and analyzes the signal components while on the other hand, AI processes the situation in real-time sequence after detecting unwanted data during the monitoring stage. The decision was integrated into the system by AI with respect to the instantaneous data read then passed to the communication nodes to take its correct location. The connectivity ratio and coverage area are optimized nearly double by the proposed method, which means the variable node location, according to the peak time, increases the attached subscriber by a while ratio

Simplified Variable Node Unit Architecture for Nonbinary LDPC Decoder

Abstract— Nonbinary low-density-parity-check (NB-LDPC) code outperforms their binary counterpart in terms of error correcting performance and error-floor property when the code length is moderate. However, the drawback of NB-LDPC decoders is high complexity and the complexity increases considerably when increasing the Galois-field order. In this paper, a simplified basic-set trellis min-max (sBS-TMM) algorithm that is especially efficient for high-order Galois Fields, is proposed for the variable node processing to reduce the complexity of the variable node unit (VNU) as well as the whole decoder. The decoder architecture corresponding to the proposed algorithm is designed for the (837, 726) NB-LDPC code over GF(32). The implementation results using 90-nm CMOS technology show that the proposed decoder architecture reduces the gate count by 21.35% and 9.4% with almost similar error-correcting performance, compared to the up-to-date works.Tóm tắt— Các mã LDPC phi nhị phân (NB-LDPC) vượt trội so với các mã LDPC nhị phân về chất lượng sửa lỗi và thuộc tính lỗi san bằng khi chiều dài là trung bình. Tuy nhiên, nhược điểm của các bộ giải mã NB-LDPC là tính phức tạp cao và độ phức tạp tăng đáng kể khi bậc của trường Galois cao. Trong bài báo này, thuật toán Trellis Min-Max dựa trên tập cơ sở được đơn giản hóa được đề xuất cho xử lý nốt biến mà hiệu quả cho các trường Galois bậc cao để giảm độ phức tạp của khối nốt biến (VNU) cũng như cả bộ giải mã. Kiến trúc bộ giải mã tương ứng với thuật toán đề xuất được thiết kế cho mã NB-LDPC (837, 726) thông qua trường GF(32). Các kết quả thực hiện sử dụng công nghệ CMOS 90-nm chỉ ra rằng kiến trúc bộ giải mã được đề xuất giảm số lượng cổng logic 21,35% và 9,4% với chất lượng sửa lỗi gần như không thay đổi so với các nghiên cứu gần đây.