Unlock instant, AI-driven research and patent intelligence for your innovation.

mimo resource optimization method, device and electronic device

A technology to be optimized and moths, applied in the field of communication, can solve problems such as unsatisfactory optimization results, low intelligence of individual algorithms, and many optimization times, and achieve the effect of solving invalid optimization problems and increasing the speed of optimization

Active Publication Date: 2022-04-26
BEIJING UNIV OF POSTS & TELECOMM +1
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, MIMO optimization usually adopts swarm intelligence algorithm. The individual intelligence ability of the above-mentioned algorithm is low, and the individual algorithm performs optimization along the established trajectory, so that the optimization process usually includes many invalid searches, and the number of optimization times is extremely high, resulting in inaccurate optimization results. Ideal, the time complexity of the algorithm is large

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • mimo resource optimization method, device and electronic device
  • mimo resource optimization method, device and electronic device
  • mimo resource optimization method, device and electronic device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0031] figure 1 A flowchart of a method for MIMO resource optimization provided by an embodiment of the present invention, such as figure 1 As shown, the method specifically includes the following steps:

[0032] Step S102: Obtain the candidate sub-beam set of the MIMO geographic area to be optimized and the weight quantity of the target antenna weight group.

[0033] Specifically, to optimize the MIMO weights for the MIMO geographic area to be optimized, it is first necessary to obtain the candidate sub-beam set of the MIMO geographic area to be optimized, and the number of weights of the target antenna weight group. A MIMO geographic area to be optimized can be It is a cell, or a geographical range specified by a user. This embodiment of the present invention does not specifically limit the geographical range of a MIMO geographical area; an alternative sub-beam can be understood as a kind of alternative antenna, and the target antenna weight group refers to The MIMO weight...

Embodiment 2

[0080] An embodiment of the present invention further provides a MIMO resource optimization apparatus, which is mainly used to execute the MIMO resource optimization method provided in the above-mentioned first embodiment.

[0081] Figure 5 is a functional block diagram of a MIMO resource optimization device provided by an embodiment of the present invention, such as Figure 5 As shown, the device mainly includes: an acquisition module 10, a first determination module 20, an iterative update module 30, and a second determination module 40, wherein:

[0082] The obtaining module 10 is configured to obtain the candidate sub-beam set of the MIMO geographic area to be optimized and the weight quantity of the target antenna weight group.

[0083] The first determination module 20 is configured to determine the initial moth population based on the number of weights and the set of candidate sub-beams; wherein, the initial moth population includes a plurality of moth agents; each mo...

Embodiment 3

[0105] see Image 6 , an embodiment of the present invention provides an electronic device, the electronic device includes: a processor 60, a memory 61, a bus 62 and a communication interface 63, the processor 60, the communication interface 63 and the memory 61 are connected through the bus 62; the processor 60 is used to execute executable modules, such as computer programs, stored in memory 61 .

[0106] The memory 61 may include a high-speed random access memory (RAM, Random Access Memory), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 63 (which may be wired or wireless), and the Internet, wide area network, local network, metropolitan area network, etc. may be used.

[0107] The bus 62 may be an ISA bus, a PCI bus, an EISA bus, or the like. The bus can be divi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The present invention provides a MIMO resource optimization method, device and electronic equipment, relating to the technical field of communication, including obtaining the weight quantity of the candidate sub-beam set and the target antenna weight group of the MIMO geographical area to be optimized; based on the weight quantity Determine the initial moth population with the set of alternative sub-beams; use the preset moth flame-fighting algorithm to iteratively update the initial moth population until the preset end condition is reached; correspond to the optimal moth agent under the preset end condition The optional antenna weight group of is determined as the target antenna weight group of the MIMO geographic area to be optimized. The preset moth-fighting algorithm used in this method is an algorithm that determines the action of each moth agent in each generation of moth populations based on a strategy function and a greedy algorithm. The fixed action strategy of the agent, this method solves the invalid optimization problem existing in the traditional algorithm, and improves the optimization speed of the algorithm for the MIMO antenna weight group.

Description

technical field [0001] The present invention relates to the technical field of communications, and in particular, to a method, apparatus and electronic device for optimizing MIMO resources. Background technique [0002] MIMO (Multiple Input Multiple Output, Multiple Input Multiple Output) weight optimization is one of the core technologies of 5G, and the system capacity is doubled through multiple sets of antenna units. The MIMO weight group is composed of a preset number of weights, and each weight represents a sub-beam. MIMO weight optimization is to find a set of sub-beams so that the reference signal receiving power (RSRP) of all grids in a specified geographical area is the largest as a whole. When there are hundreds of alternative sub-beams, the MIMO weight is There are hundreds of millions of combinations in the group, and it is very difficult to select the best combination among the hundreds of millions of MIMO weight groups. [0003] At present, swarm intelligence...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): H04B7/06H04B7/08H04W24/02G06N3/00
CPCH04B7/0695H04B7/0691H04B7/0874H04B7/088H04W24/02G06N3/006
Inventor 姚海鹏黄山苏波买天乐忻向军葛洪武吴巍吴小华王山
Owner BEIJING UNIV OF POSTS & TELECOMM