The power consumption of the integrated circuit is becoming a significant burden, particularly for large-scale signal processing tasks requiring high throughput. The decoding process of LDPC codes is such a heavy signal processing task that demands power efficiency and higher decoding throughput. A promising approach to reducing both power and latency of a decoding process is to use an analog circuit instead of a digital circuit. This paper investigates a continuous-time gradient flow-based approach for decoding LDPC codes, which employs a potential energy function similar to the objective function used in the gradient descent bit flipping (GDBF) algorithm. We experimentally demonstrate that the decoding performance of the gradient flow decoding is comparable to that of the multi-bit mode GDBF algorithm. Since an analog circuit of the gradient flow decoding requires only analog arithmetic operations and an integrator, future advancements in programmable analog integrated circuits may make practical implementation feasible.
翻译:集成电路的功耗对大规模信号处理任务的高吞吐量要求日益成为重要的负担。低密度奇偶校验码的解码过程是这种沉重信号处理任务,要求功率效率和更高的解码吞吐量。减少解码过程的功耗和延迟的一种有前途的方法是使用模拟电路而非数字电路。本文研究了一种基于梯度流的连续时间解码低密度奇偶校验码的方法,该方法采用了一个潜能能量函数,类似于梯度下降比特翻转 (GDBF) 算法中使用的目标函数。我们实验表明,梯度流解码的解码性能与多比特模式的 GDBF 算法相当。由于梯度流解码的模拟电路仅需要模拟算术运算和积分器,未来可编程模拟集成电路的进一步发展可能使实际实现变得可行。