Radio resource management measurements in dense network scenarios

Abstract

A method of a wireless communication device for operation in a wireless communication network comprising a plurality of cells is disclosed. The method comprises performing radio resource management measurements based on received reference signals of one or more of the cells, wherein the radio resource management measurements are performed over a bandwidth comprising K subcarriers. The method also comprises organizing the K subcarriers into N blocks, wherein each block comprises adjacent subcarriers, performing coherent averaging of the radio resource management measurements over the adjacent subcarriers of each block to produce intermediate measurement results and performing non-coherent averaging of the intermediate measurement results to produce a radio resource management measurement result. The method further comprises detecting whether a condition is fulfilled, wherein the condition is suitable for determining if the wireless communication device is in a dense network scenario, setting N to a first value if the condition is fulfilled and to a second value if the condition is not fulfilled, wherein the first value is lower than the second value. Corresponding arrangement, wireless communication device and computer program product are also disclosed.

Description

technical field [0001] The present invention generally relates to the field of radio resource management measurements. More specifically, the present invention relates to such measurements in dense network scenarios. Background technique [0002] Wireless communication systems experience demands for higher end-user data rates and increased system capacity. Some examples of solutions to increase system capacity include more efficient use of existing spectrum resources, use of additional spectrum resources, increased spatial reuse of (existing and / or additional) spectrum (i.e. in dense network node deployments adding more cells to the system), and various combinations of these three solutions. [0003] For example, extreme system capacity requirements may be the result of a large number of users requiring high average data rates, a scenario with high traffic density within a geographic area that may typically occur in urban environments. To support such business requirement...

AI Technical Summary

Problems solved by technology

However, such a generally robust design limits performance in some specific scenarios

For example, using a generally robust design in dense network scenarios may lead to RRM measurements that limit the benefits of dense network deployments (such as increased capacity), because generally robust methods do not lead to sufficiently high accuracy of RRM measurements, and, therefore, the RRM algorithm (e.g. cell selection, handover, etc.) becomes suboptimally performed

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