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<p>Wireless communication systems face many challenges due to fluctuating channel conditions resulting in variable error rates and demands robust error management tactics. Traditional Automatic Repeat Request (ARQ) methods suffer from high communication overhead and latency and are inefficient in handling retransmissions. Although traditional Hybrid Automatic Repeat Request (HARQ) is effective, its widespread use is limited by high implementation costs. This underscores the need for adaptive systems that dynamically respond to changing channel conditions based on Signal-to-Noise ratio (SNR). This paper proposes the Dynamic HARQ (D-HARQ), which switches between ARQ, HARQ with Bose–Chaudhuri–Hocquenghem codes, and HARQ with turbo codes based on channel conditions during the transmission. Further, this paper incorporates a selective soft-combining technique by estimating the receiver end’s SNR. The main goal is to achieve the maximum possible throughput even at very low SNR values while maintaining optimal complexity.</p>

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SNR-Responsive Communication: Turbo Codes and BCH in a Dynamic HARQ Scheme for Enhanced Efficiency

  • 期刊论文

  • 发表日期：

    2025年4月23日

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  • Gnana Jyothi Chintha,
  • Chandana Sai Sri Hasitha Prathapa,
  • Yaswanth Namburi,
  • B. R. Chandavarkar

摘要

Wireless communication systems face many challenges due to fluctuating channel conditions resulting in variable error rates and demands robust error management tactics. Traditional Automatic Repeat Request (ARQ) methods suffer from high communication overhead and latency and are inefficient in handling retransmissions. Although traditional Hybrid Automatic Repeat Request (HARQ) is effective, its widespread use is limited by high implementation costs. This underscores the need for adaptive systems that dynamically respond to changing channel conditions based on Signal-to-Noise ratio (SNR). This paper proposes the Dynamic HARQ (D-HARQ), which switches between ARQ, HARQ with Bose–Chaudhuri–Hocquenghem codes, and HARQ with turbo codes based on channel conditions during the transmission. Further, this paper incorporates a selective soft-combining technique by estimating the receiver end’s SNR. The main goal is to achieve the maximum possible throughput even at very low SNR values while maintaining optimal complexity.