Abstract
Massive Multiple Input Multiple Output (MIMO) is a promising technique for communications due to the high data transmission rate. To harvest the benefit from the massive MIMO, it is necessary to have accurate channel estimates. Such channels often exhibit sparsity in the virtual angular domain. This paper proposes a dichotomous coordinate descent (DCD) based algorithm for joint sparse channel estimation in the virtual angular domain for the orthogonal-frequency-division-multiplexing massive MIMO. We show that compared to the distributed sparsity adaptive matching pursuit algorithm previously proposed for this purpose, the DCD-based algorithm has significantly lower complexity and better channel estimation performance.
Highlights
Massive Multiple Input Multiple Output (MIMO) has been proposed for generations of communication systems, since it provides higher spectral efficiency [1], [2]
We focus on the channel estimation in the feedback scheme
dichotomous coordinate descent (DCD)-JSR ALGORITHM FOR THE CHANNEL ESTIMATION IN VIRTUAL ANGULAR DOMAIN In [7], the distributed sparsity adaptive matching pursuit (DSAMP) algorithm was proposed to jointly estimate multiple sparse channels by estimating the common support shared by different subcarriers in orthogonal frequency division multiplexing (OFDM)
Summary
Massive MIMO has been proposed for generations of communication systems, since it provides higher spectral efficiency [1], [2]. By exploiting the common sparsity in the virtual angular domain, we can jointly estimate the channel for multiple subcarriers. Since the DCD algorithm in [13] can only deal with single sparse channel at one time, by exploiting the spatially common sparsity in the virtual angular domain of the massive MIMO channels, a DCD-Joint-Sparse-Recovery (DCD-JSR) algorithm is proposed here. The DCD-JSR algorithm can jointly estimate multiple sparse channels and provide accurate CSI acquisition with a low computational complexity. DCD-JSR ALGORITHM FOR THE CHANNEL ESTIMATION IN VIRTUAL ANGULAR DOMAIN In [7], the distributed sparsity adaptive matching pursuit (DSAMP) algorithm was proposed to jointly estimate multiple sparse channels by estimating the common support shared by different subcarriers in OFDM.
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