High-Dimensional CSI Acquisition in Massive MIMO: Sparsity-Inspired Approaches
作者： Khaled B. Letaief , Juei-Chin Shen , Jun Zhang , Kwang-Cheng Chen
DOI: 10.1109/JSYST.2015.2448661
关键词: Electronic engineering 、 Wireless network 、 Reduction (complexity) 、 3G MIMO 、 Computer engineering 、 Compressed sensing 、 Precoding 、 Engineering 、 Spectral efficiency 、 MIMO 、 Overhead (computing)
摘要: Massive multiple-input–multiple-output (MIMO) has been regarded as one of the key technologies for fifth-generation wireless networks, it can significantly improve both spectral efficiency and energy efficiency. The availability high-dimensional channel side information (CSI) is critical its promised performance gains, but overhead acquiring CSI may potentially deplete available radio resources. Fortunately, recently discovered that harnessing various sparsity structures in massive MIMO channels lead to significant reduction, thus system performance. This paper presents discusses use sparsity-inspired acquisition techniques MIMO, well underlying mathematical theory. Sparsity-inspired approaches frequency-division duplexing time-division systems will be examined compared from an overall perspective, including design tradeoffs between two modes, computational complexity algorithms, applicability structures. Meanwhile, some future prospects research on meet practical demands identified.
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