Wireless resource allocation method for ultra-dense networks based on noma and beamforming

Abstract

The invention discloses a method for allocating wireless resources in an ultra-dense network based on NOMA and beamforming. By combining beamforming and NOMA, a base station equipped with multiple antennas communicates with multiple single-antenna user equipment, from macro base stations to small base stations , use beamforming to improve signal coverage and signal-to-noise ratio, use NOMA in the process of transmission from small base stations to users, and allocate different transmission power to different users, so as to adapt to the fact that users cannot feedback effectively according to changes in the network environment The status of the network status information. The present invention not only effectively suppresses inter-cluster interference and intra-cluster user interference, but also ensures the fairness among users to a certain extent, improves the throughput performance of the system, performs power allocation fairly and effectively, and makes the system have high throughput The advantages of high volume, high signal quality, and high power efficiency, and support for a large number of users to communicate at the same time, thus greatly improving system performance and spectrum utilization.

Description

technical field [0001] The invention relates to a resource allocation method, in particular to an ultra-dense network wireless resource allocation method based on NOMA and beamforming, and belongs to the technical field of communications. Background technique [0002] The fifth generation mobile communication system (5G), its theoretical peak transmission rate can reach tens of Gbit / s, which is hundreds of times higher than the transmission rate of 4G system, and the data traffic is increased by 1000 times. will be significantly improved. In order to achieve this goal, in addition to increasing spectrum bandwidth and using advanced wireless transmission technology to improve spectrum utilization, one of the main methods is to increase spatial reuse through densified cell deployment and build ultra-dense networks (UDNs). The ultra-dense network enables the user terminal to obtain more spectrum in the coverage area and is closer to each transmitting node, which improves the s...

AI Technical Summary

Problems solved by technology

[0005] 1) Interference limitation: With the increase of base station density and the decrease of the distance between users and base stations, the UDN inter-cluster interference intensity and the number of interfering base stations increase, which will increase a lot of extra overhead and power consumption, and due to multiple Each user shares a beamforming vector, therefore, the total capacity is easily affected by interference from other beamforming vectors, and the previous resource management control method is not applicable under multiple interferences

[0006] 2) Overhead limitation: Traditional random beamforming still requires all users to send channel state information to the base station, which consumes a lot of resources

[0007] 3) Service restriction: With the reduction of cell coverage, the behavior of users has a high correlation, and the problem of service association becomes more complicated

The service association technology will directly affect the resource allocation scheme of the network, thereby affecting the network performance.

[0008] 4) Complexity limitation: Compared with the traditional SIC receiver, the SIC receiver adopted by NOMA is more complex and requires higher signal processing capabilities

However, in a cluster-based NOMA system, it is very difficult to determine how best to dynamically allocate users to a dynamic number of clusters with different sizes

More importantly, the resulting combinatorial optimization problems are usually difficult to solve, and the calculation is huge

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