Method for improving communication energy efficiency based on antenna selection in large-scale MIMO system

An antenna selection, large-scale technology, applied in the field of 5G communication, to achieve the effect of increasing complexity, increasing system energy efficiency, and reducing complexity

Active Publication Date: 2017-03-15
SHENZHEN RES INST CENT SOUTH UNIV
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Problems solved by technology

Although the above-mentioned algorithms already exist, there is still room

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  • Method for improving communication energy efficiency based on antenna selection in large-scale MIMO system

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Embodiment Construction

[0042] Below in conjunction with accompanying drawing and example, the present invention is described in further detail.

[0043] The present invention proposes an energy efficiency algorithm based on antenna selection in a massive MIMO system, the specific process is as follows figure 1 shown, including the following steps:

[0044] S1. Use figure 2 As shown in the massive MIMO system model, the power consumption model of the system is established:

[0045]

[0046]Among them, E(L, M) is the system energy efficiency function, and its value is a function of the number L of antennas selected for transmission and the number M of receiving antennas when the transmission power and channel state are determined; C(L, M) is the transmission power and the system capacity when the channel is determined, P(L, M) is the system power consumption when the transmission power and the channel are determined, and the system bandwidth is B, λ i is the channel gain, p i is the transmitte...

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Abstract

The invention discloses a method for improving communication energy efficiency based on antenna selection in a large-scale MIMO system. The method comprises the following steps: S1, establishing a system power consumption model according to a system channel status condition, transmission link power, receiving link power and conversion efficiency, and performing the channel estimation to obtain a channel status, and feeding back the channel status to a base station to determine the minimum capacity requirement at a user side and compute the minimum antenna number; S2, computing the antenna number with the optimal energy efficiency by use of an improved search method according to the system power consumption model and the minimum antenna number; S3, obtaining a sub-set more than the antenna number with the optimal energy efficiency by use of the maximum norm method, and then selecting an antenna array with the antenna number with the optimal energy efficiency by use of a successive subtraction method in the sub-set. Compared with the traditional antenna selection algorithm, the method disclosed by the invention has higher system capacity and lower computing complexity, the communication energy efficiency of the large scale MIMO system can be improved, and the performance of the system is improved.

Description

technical field [0001] The invention relates to the technical field of 5G communication, in particular to a method for improving communication energy efficiency based on antenna selection in a massive MIMO system. Background technique [0002] Massive MIMO systems make full use of the spatial freedom of the system by configuring ultra-large-scale antenna arrays at the transceiver end to provide more users with high-quality wireless communication services. It is expected that without increasing the additional system transmission power and bandwidth, Significantly improving the spectral efficiency and energy efficiency of the system is one of the most competitive mainstream alternatives for 5G in the future. [0003] When all antennas are used for wireless data transmission, the base station of the massive MIMO system needs to install the same number of radio frequency links as the number of base station antennas, which greatly increases the hardware cost and implementation co...

Claims

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Application Information

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IPC IPC(8): H04B7/0417H04B7/06H04B17/391
CPCH04B7/0417H04B7/061H04B17/391Y02D30/70
Inventor 邓宏贵张朝阳杜捷钱学文
Owner SHENZHEN RES INST CENT SOUTH UNIV
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