Design and Implementation of Low-Complexity Multiple Symbol Detection Algorithm Using Hybrid Stochastic Computing in...

The Multiple Symbol Detection (MSD) algorithm can effectively lower the demodulation threshold in Frequency Modulation (FM) technology, which is widely used in aircraft wireless communications due to its insensitivity to large Doppler shifts. However, the high computational complexity of the MSD algorithm leads to considerable hardware resource overhead. In this paper, we propose a novel MSD architecture based on hybrid stochastic computing (SC), which allows for accurate signal detection while maintaining low hardware complexity. Given that the correlation calculation dominates the computational load in the MSD algorithm, we develop an SC-based, low-complexity unit to perform complex correlation operations using simple hardware circuits, significantly reducing the hardware overhead. Particularly, we integrate a flexible and scalable stochastic adder in the SC-based correlation calculation, which incorporates an adjustable scaling factor to enable high distinguishability in all possible correlation results. Additionally, for the symbol decision process of the MSD algorithm, we design a binary computing-based pipeline architecture to execute the computing process serially, which leverages the inherent low update rate of SC-based correlation results to further reduce the overall resource overhead. Experimental results show that, compared to an 8-bit quantization MSD implementation, our proposed hybrid SC-based MSD architecture achieves a comparable bit error rate while reducing the hardware resources to 69%, 45%, and 36% of those required for the three-, five-, and seven-symbol MSD algorithms, respectively.