Deploying Enhanced Reed-Muller and Polar Decoders for SDN-based C-RAN Fronthaul

Autor: Song Xing, Yi Wu, Hsin-chiu Chang, Zheng Yang, Yan Zhang, Wen-Kang Jia
Rok vydání: 2019
Předmět:
Zdroj: CCNC
Popis: In this paper, we propose enhanced Reed-Muller (RM) and Polar decoder for SDN-based C-RAN fronthaul. The simulation results show that our proposed algorithm outperforms traditional decoding algorithm in terms of average number of connected user equipment to RRHs, and the feasibility of decoding the RM codes by the Successive Cancellation (SC) decoding algorithm is verified by comparing the performance and decoding time of the RM and Polar codes under the SC and Belief Propagation (BP) iterative algorithm. The simulation results show that the decoding time of SC decoding algorithm is reduced about 98.98% compared with the BP decoding algorithm. For the BP decoding algorithm with excellent decoding performance but long decoding time, this paper proposes an improved BP decoding algorithm based on early terminating iteration criterion of the absolute values difference for the likelihood, which reduces the computational complexity of criterion. The simulation results illustrate that the early-terminating iteration criterion proposed in this paper reduces the computational complexity, thereby reducing the decoding delay and energy consumption effectively, and satisfying the low complexity and energy consumption decoding requirements.
Databáze: OpenAIRE