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CSI feedback method for large-scale MIMO system based on compressed sensing
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A compressed sensing, large-scale technology, applied in the field of CSI feedback, can solve the problem of wasting measurement overhead
Active Publication Date: 2016-12-07
XIHUA UNIV
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At the same time, the number of measurements required by the BS to accurately reconstruct the "support set" mainly depends on the small-magnitude elements; that is, the BS reconstructs the index of the small-magnitude elements wastes a lot of measurement overhead
However, existing CS-based CSI feedback does not take advantage of these properties
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example 1
[0078] Example 1: The "sorting" example described is as follows:
[0079] Suppose N=16, S=4, then H can be expressed as H=h 1 ,h 2 ,..., h 16 T . In particular, the number N of BS antennas in an actual massive MIMO system is hundreds to thousands, and only N=16 is considered here for the convenience of writing. Among the elements of H, except h 3 ,h 6 ,h 10 ,h 14 Except for 4 elements, the other elements are all 0, that is, the support set w=3, 6, 10, 14. Suppose h 3 ,h 6 ,h 10 ,h 14 The value is
[0080] h 3 = 0.3 + j 0.25 h 6 = 0.05 - j ...
example 2
[0087] Example 2: An example of the described search "preserve sparsity" λ is as follows:
[0088] On the basis of Example 1, assuming γ=0.9, then we have
[0089]
[0090] Therefore, it can be seen that the "reserved sparsity" λ=3.
[0091] b) The MS calculates the "required measurement number" M, and then compresses the downlink CSI (that is, H) that needs to be fed back according to the compressed sensing method; the specific process is as follows:
[0092] The "required number of measurements" M mentioned in b1) is calculated according to the following formula.
[0093] M = m a x { μlog 2 N , Cλlog 2 ( N λ ) }
[0094] Among them, the "reserved sparsity" λ is obtained according to step a3), N is the number of BS antennas, C is ...
example 3
[0111] Example 3: The generation example of the "partial supporting set bitstream" G is as follows:
[0112] Suppose N=8, S=3, λ=1, thereby
[0113] [ log 2 ( N ! S - λ ! N + λ - S ! ) ] = 5
[0114] Therefore, the with 5 bits b 5 b 4 b 3 b 2 b 1 According to the mapping method from small to large (that is, 1, 2 is mapped to 00000, 1, 3 is mapped to 00001, ..., 2, 3 is mapped to 00111, ..., 7, 8 is mapped to 11011) to encode "partial support set bitstream" For G=10000 (ie b 5 b 4 b 3 b 2 b 1 = 10000).
[0115] c13) Quantize the sparsity S into a "sparsity bit stream" (denoted as S).
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Abstract
The invention discloses a CSI feedback method for a large-scale MIMOsystem based on compressed sensing, and belongs to the technical field of compressed feedback of channel state information in a large-scale wireless communication system. The CSI feedback method comprises the steps that a mobile station MS calculates retention sparsity according to a preset energy factor of the system; the MS calculates a necessary number of measurements according to the retention sparsity, and calls a measurement matrix to compress downlink CSI needing to be fed back according to the necessary number of measurements; the MS converts the CSI needing to be fed back into bit stream and feeds back the bit stream to a base station BS, wherein the CSI needing to be fed back comprises a measurement signal, a partial supporting set and the sparsity; the BS demodulates the sparsity containing noise, the partial supporting set and the measurement signal according to the received bit stream, and calls an improved reconstruction algorithm to reconstruct the downlink CSI. By adopting the CSI feedback method in the scheme disclosed by the invention, the feedback overhead of the CSI feedback based on the compressed sensing can be effectively reduced, and the computational complexity of the CSI reconstruction algorithm on the BS side is reduced.
Description
technical field [0001] The present invention relates to a channel state information (CSI, channel state information) compression feedback technology in a massive MIMO (Multiple-Input Multiple-Output) wireless communication system, and specifically provides a CSI feedback of a massive MIMO system based on compressed sensing method. Background technique [0002] As a key research technology of the fifth generationwireless and mobile communication (5G), massive MIMO (Massive MIMO) has attracted much attention due to its advantages of high system capacity and high link reliability. In a massive MIMO system, a base station (BS, basestation) is usually configured with a large number of BS antennas (hundreds or thousands of base station antennas) to obtain better spatial multiplexing and diversity gain. [0003] In order to obtain the benefits brought by the massive MIMO system, the base station needs relatively accurate downlink CSI. Usually, the mobile station (MS, mobile stat...
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