A low-complexity cognitive-based spectrum resource allocation method for femtocells

Abstract

The present invention relates to a low-complexity cognitive-based home base station spectrum resource allocation method, which belongs to the field of wireless communication. The method includes: the macro cell layer of the network divides the macro cell into a central area and an edge area by using a method of partial frequency reuse , the central area uses the entire spectrum, and the edge areas use three orthogonal sub-bands of the spectrum; the home base station adopts a polling mechanism to sequentially allocate resources to the home users in the home cell, and the home users use the entire frequency band; the home base station is isolated When performing resource allocation, the base station only needs to consider the interference of the users in the macro cell to the home cell; otherwise, in addition to considering the interference of the macro cell users, resource block allocation also considers the overlapping area with the home cell where the home base station Nj is located Interference from users in a home cell. The method proposed by the invention has low complexity, is easy to operate, effectively avoids interference, and improves frequency spectrum utilization efficiency.

Description

technical field [0001] The invention belongs to the field of frequency spectrum resource allocation of wireless communication, in particular to a low-complexity cognitive-based frequency spectrum allocation method for resource allocation of heterogeneous networks. Background technique [0002] In traditional cellular networks, the spectral efficiency of point-to-point links is close to the theoretical limit, but people's requirements for high-quality services and large data traffic continue to increase, so it is necessary to further increase network capacity to meet people's needs. However, in the case where the current network has been deployed relatively densely, the interference between cells severely limits the gain obtained through cell splitting technology, and due to the high cost of high-power nodes, this further makes the method of cell splitting unfeasible . Therefore, the technology of significantly improving the network capacity by changing the topology of the n...

AI Technical Summary

Problems solved by technology

However, in the case where the current network has been deployed relatively densely, the interference between cells severely limits the gain obtained through cell splitting technology, and due to the high cost of high-power nodes, this further makes the method of cell splitting unfeasible

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