Abstract
Due to the sparse multipath characteristic of the channel, millimeter wave (mmWave) channel estimation can be treated as a sparse signal recovery problem. By exploiting the channel sparse characteristics with compressive sensing (CS) theory, sparse signal recovery algorithms can be used for channel estimation. Orthogonal matching pursuit (OMP) algorithm is one of the most popular CS reconstruction algorithms. Hence, in this paper, we present OFDM-based mmWave sparse indoor channel estimation using the OMP algorithm. However, the computational effort for OMP remains high, even for problems of moderate size in real-time applications. Hence, a new VLSI architecture for mmWave channel estimation using the OMP algorithm is designed and simulated using Xilinx 15.4 Vivado HLS simulator in this paper. Our empirical results illustrate the efficacy of the proposed approach.
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