SISO HARQ Implementation Program

In modern wireless communication systems, the combination of SISO (Single Input Single Output) with HARQ (Hybrid Automatic Repeat Request) represents a fundamental technical approach for enhancing data transmission reliability. SISO systems utilize single transmit and receive antennas, while HARQ provides an error control mechanism that combines forward error correction with automatic retransmission requests. The implementation typically involves CRC (Cyclic Redundancy Check) for error detection and convolutional/Turbo codes for error correction.

The core principle of HARQ involves appending error correction codes to transmitted data. When the receiver detects errors, it first attempts to correct them using these codes. If correction fails, the receiver sends a NAK (Negative Acknowledgement) to request retransmission. Compared to traditional ARQ, HARQ improves retransmission efficiency by storing and combining information from multiple transmissions, significantly reducing packet loss rates. Code implementation often includes soft-combining algorithms like Chase Combining or Incremental Redundancy (IR) schemes.

Implementing HARQ in SISO systems typically follows these algorithmic steps: First, the transmitter performs channel coding (using functions like LDPC or Turbo encoding), modulation (QPSK/16-QAM), and transmits through wireless channels. The receiver executes demodulation and error correction attempts, employing Viterbi or BCJR decoding algorithms. Upon failure, it triggers NAK signaling, prompting retransmission. Key programming components include transmit buffer management, ACK/NAK processing state machines, and combining metric calculations for HARQ Chase or IR strategies.

This technology finds applications in 4G/5G mobile communications, Wi-Fi systems, and other wireless standards, particularly demonstrating significant performance improvements in challenging channel conditions. Future enhancements integrating MIMO (Multiple Input Multiple Output) or Adaptive Modulation and Coding (AMC) technologies can further optimize system performance through spatial diversity and dynamic parameter adjustment algorithms.