科研之友
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摘要
Compressive sensing (CS) has recently become a critical technique to reduce the high computational cost of signal processing systems. One of the main signal processing modules of CS systems is the signal reconstruction processor. Orthogonal matching pursuit (OMP) is one of the main signal reconstruction algorithms because of its low complexity and high regularity compared with the greedy l1 algorithm. However, the main problem of an OMP-based signal reconstruction processor is its low reconstruction performance. Therefore, this paper proposed an enhanced projection-based atom selection orthogonal matching pursuit (POMP) algorithm to solve this problem. The original POMP algorithm has more favorable signal-to-reconstruction-noise ratio (SRNR) performance than the OMP algorithm, but the computational complexity of the POMP is too high to be realized in hardware. The proposed algorithm greatly reduces the computational complexity of the original POMP algorithm without any SRNR performance loss by using multiple index candidates and matrix-inversion-bypass method. The proposed reconstruction processor architecture was designed and implemented using the TSMC 90-nm 1P9M CMOS technology. The postlayout results showed that the proposed processor exhibited a lower normalized processing latency and achieved a higher SRNR of 34.9 dB compared with the processors in previous studies.
- 出版日期2016-12
- 单位清华大学
