Multi-target optimization resource distribution algorithm of MU-MIMO system in degenerate-rank of channel

A multi-objective optimization and resource allocation technology, applied in the field of multi-objective optimization resource allocation algorithm for MU-MIMO systems when the channel is under-ranked

Active Publication Date: 2018-11-16
NANJING UNIV OF POSTS & TELECOMM
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Therefore, for real-time services, the rate exceeding the upper lim

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  • Multi-target optimization resource distribution algorithm of MU-MIMO system in degenerate-rank of channel
  • Multi-target optimization resource distribution algorithm of MU-MIMO system in degenerate-rank of channel
  • Multi-target optimization resource distribution algorithm of MU-MIMO system in degenerate-rank of channel

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[0095] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0096] Such as Figure 1 to Figure 2 As shown, the present invention proposes a multi-objective optimal resource allocation algorithm for MU-MIMO systems when the channel is under-ranked, including the following steps:

[0097] Step 1: Establish a system model and analyze the conditions of the channel under rich scattering and non-rich scattering environments.

[0098] Such as figure 2 As shown, in the MU-MIMO system, it is assumed that the system base station (BS) has N T The total number of users in the system is K, and the number of receiving antennas of the mth user terminal is n m ,1≤m≤K, generally N T ≥n m , let M be the maximum number of users that the base station can serve simultaneously.

[0099] In the MU-MIMO system, since users...

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Abstract

The invention discloses a multi-target optimization resource distribution algorithm of a MU-MIMO system in a degenerate-rank of channel. The algorithm comprises the following steps: step one, establishing a system model, and analyzing user capacity upper limit and equivalent channel status when being located in rich scattering environment and non-rich scattering environment; step two, establishinga dual-target optimization problem model; and step three, solving the dual-target optimization problem, realizing the dual-target optimization of system effective throughput and energy efficiency through the power distribution and user selection; since the dual-target optimization problem is not a standard convex optimization problem and cannot be solved by directly utilizing the convex optimization technology, the optimization problem is solved through a Lagrange dual algorithm. The energy efficiency and spectrum efficiency of the system effective throughput and energy efficiency system canbe optimized when the user delay and the service rate upper limit and lower limit are simultaneously guaranteed through power distribution and user selection.

Description

technical field [0001] The present invention relates to the field of communications, in particular to a multi-objective optimal resource allocation algorithm for MU-MIMO systems when the channel rank is low. Background technique [0002] Multi-user MIMO technology can effectively use space resources to improve the throughput of wireless communication systems without consuming additional spectrum bandwidth. Therefore, multi-user MIMO technology has become one of the key technologies of 5G networks. With the continuous improvement of people's demand for wireless communication and society's requirements for energy conservation and environmental protection, optimizing system throughput and energy efficiency (the data rate that can be transmitted per unit of energy) are two important goals for researching multi-user MIMO resource allocation. The resource allocation algorithm optimizes throughput and energy through user selection and power allocation. User selection and power allo...

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Application Information

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IPC IPC(8): H04B7/0452H04B7/0426H04B17/382
CPCH04B7/0426H04B7/0452H04B17/382Y02D30/70
Inventor 潘甦闫妍
Owner NANJING UNIV OF POSTS & TELECOMM
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