EFFICIENT ALGORITHM DESIGN FOR FM DIGITAL SIGNAL PROCESSORS: CHALLENGES AND SOLUTIONS
Keywords:
FM-DSP, Algorithm efficiency, Low latency, Adaptive filtering, SignalAbstract
Efficient algorithm design for frequency modulation (FM) digital signal processor (DSPs) is critical for meeting the increasing demands of modern communication systems characterized by high data rates, low latency requirements, and constrained hardware resources. This study investigates the computational and architectural challenges associated with FM DSP implementations, including arithmetic complexity, power consumption, memory limitations, and susceptibility to noise and interference. A comprehensive analysis of existing approaches shows that conventional FM demodulation algorithms typically exhibit computational complexities on the order of O (NlogN), with latency exceeding 10–15 ms in real-time embedded environments. To address these limitations, this work proposes an optimized hybrid algorithmic framework that integrates adaptive filtering, approximation techniques, and hardware-aware pipelining. Simulation results indicate a reduction in computational complexity by approximately 35–45%, while latency is decreased to below 5 ms under typical signal conditions. Furthermore, the proposed approach improves signal-to-noise ratio (SNR) performance by 6–8 dB in low-SNR environments compared to baseline methods. Energy consumption is also reduced by up to 30% through efficient resource utilization and dynamic scaling strategies. These findings demonstrate that the proposed solutions significantly enhance the performance, scalability, and robustness of FM DSP systems, making them suitable for next-generation wireless and embedded communication applications.
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