Antenna selection method based on sub-mode function for large-scale multiple input multiple output scenario

An antenna selection, multi-input technology, applied in diversity/multi-antenna systems, transmission systems, radio transmission systems, etc., can solve the problems of unguaranteed system channel capacity performance, high antenna complexity, and high complexity, and achieve intuitive analysis. Ideas, calculations are simple and intuitive, low-complexity effects

Inactive Publication Date: 2018-06-29
XIDIAN UNIV +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The optimal method of antenna selection is too complex and not suitable for large-scale MIMO communication scenarios
The complexity of the increasing/decreasing method is lower than that of the optimal method, and the system channel capacity performance can approach the optimal method, but the complexity is still high
The norm-based selection method is considered to be mo

Method used

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  • Antenna selection method based on sub-mode function for large-scale multiple input multiple output scenario
  • Antenna selection method based on sub-mode function for large-scale multiple input multiple output scenario
  • Antenna selection method based on sub-mode function for large-scale multiple input multiple output scenario

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Embodiment 1

[0025] In a large-scale multiple-input multiple-output system, a large number of antennas are configured at the transmitting (or receiving) end, which can provide diversity gain to reduce the bit error rate and improve service quality or provide multiplexing gain to improve service efficiency, which brings about an improvement in the performance of the communication system . In practical applications, configuring a large number of antennas will be limited by practical problems such as hardware cost and signal processing complexity. The radio frequency link is proportional to the number of antennas. Although the antenna itself is relatively cheap, each radio frequency link in the antenna system includes communication devices such as low noise amplifiers, up (down) converters, and digital-to-analog (analog-to-digital) converters. , the price is high; at the same time, the complexity of system processing is also proportional to the number of antennas. On the premise of maintaini...

Embodiment 2

[0050] The antenna selection method based on the submodular function in a large-scale multi-input and output scene is the same as that in Embodiment 1, and the antenna selection model under the framework of the submodular function is established in step (2) of the present invention, specifically including:

[0051] (2a) Use the channel capacity formula to express the total channel capacity C of the original channel matrix G full :

[0052]

[0053] in, Indicates that the dimension is N R The identity matrix of N R =128,N T = 12 respectively represents the number of receiving antennas (base stations) and the number of transmitting antennas (single-antenna users) in the uplink system, ρ is the signal-to-noise ratio, det(·) represents the determinant, (·) H Represents the conjugate transpose of a matrix.

[0054] The present invention is applied to reduce the processing complexity of a large-scale multiple input and output system. If all antennas are used as the antennas...

Embodiment 3

[0066] The antenna selection method based on the submodular function in a large-scale multiple input and output scenario is the same as that in Embodiment 1-2. The standard for determining the greedy selection method in step (3) is to select the antenna based on the maximization of the channel capacity increment, specifically including Have:

[0067] Iterate through the original channel matrix each row in c t , and make a greedy selection to find the row c that contributes the most to the channel capacity increment tar , tar represents the matrix The tar line in , which satisfies the formula for maximizing channel capacity increment, see the following formula for details:

[0068]

[0069] Indicates the channel capacity increment, defined here is the value increment of the set function C(·) of element i on set A, where A+i means the union A∪{i} of set A and element i, and A-i is defined to mean the difference set of set A and element i A\{i}.

[0070] The present...

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Abstract

The invention discloses an antenna selection method based on a sub-mode function for a large-scale multiple input multiple output (MIMO) scenario, which solves the technical problems that the complexity is high due to too many antennas and the channel capacity of the conventional antenna selection method is not high enough. The method comprises the steps of: defining antenna selection parameters;establishing an antenna selection model of the sub-mode function; determining criteria for greedy selection; approximating the model with a greedy selection algorithm; and completing the antenna selection. The method intuitively transforms the antenna selection into a discrete problem of the sub-mode function from the idea of set selection, and solves a mathematical model to complete the antenna selection. A greedy selection approximation algorithm for solving the discrete problem of the sub-mode function is designed, with the approximate ratio (1-1/e), which simplifies the calculation and reduces the complexity. The implementation complexity of the method is low, the channel capacity performance of the system is improved under the same condition, the performance is guaranteed in any practical application, and the method can be used for fifth-generation mobile communication large-scale MIMO systems and cell mobile communication systems.

Description

technical field [0001] The invention belongs to the field of fifth-generation mobile communication technology, and mainly relates to antenna selection, in particular to an antenna selection method based on a submode function in a large-scale multi-input and output scene, which can be used in a cellular cell mobile communication system. Background technique [0002] With the vigorous development of the information society, smart phones have been popularized in people's daily life, and have now become one of the main tools for people to carry out daily communication, entertainment and online shopping. The popularity of smart phones has stimulated the continuous integration of Internet services and mobile communications. In recent years, a large number of mobile Internet services have emerged one after another. The emergence of these services meets the growing application needs of mobile users, and also brings many challenges to future mobile communications. Future mobile commu...

Claims

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Application Information

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IPC IPC(8): H04B7/08H04B7/06H04B7/0413
CPCH04B7/0413H04B7/0602H04B7/0802
Inventor 王勇超张杰王江涛金鑫
Owner XIDIAN UNIV
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