Methods and apparatus for evaluating behaviour of communication device in view of antenna patterns thereof

A device for evaluating a behaviour of a communication device in view of an antenna pattern thereof, the device comprising at least one processor and a memory storing a set of instructions, and the set of instructions, when executed by the at least one processor is configured to perform a method comprising:

• receiving a first dataset representing a first set of values of at least two parameters relating to a first antenna pattern;
• receiving a second dataset representing a second set of values of the at least two parameters relating to a second antenna pattern being formed by the communication device;
• relating the first dataset and the second dataset using a metric to obtain a relationship as a result of the metric being applied;
• and
• evaluating the behaviour of the communication device using the relationship,
• wherein the evaluating the behaviour of the communication device is performed at least in part at:
• the communication device;
• a part of a test and measurement equipment;
• a different node comprising information about the first antenna pattern and the second antenna pattern;
• or
• a network controller,
• wherein the evaluating the behaviour of the communication device is a basis of a selection of a beam pattern being formed to optimize a link performance existing between the communication device and another communication device according to a link performance criterion, and
• wherein the metric is based on at least one of:
• a sample mean providing a first mean value of a parameter of the first dataset and a second mean value of the parameter of the second dataset, so as to relate the first mean value and the second mean value;
• a sample variance providing a variance value of values of a parameter of the second dataset in relation to values of the parameter in the first dataset;
• a sample standard variation providing a standard variation value of values of a parameter of the second dataset in relation to values of the parameter in the first dataset;
• a distribution of a sample mean providing for a distribution value of values of the parameter compared to a mean value of the parameter;
• a hypothesis testing;
• a similarity measure providing for a similarity value indicating a similarity between the first dataset and the second dataset;
• a dissimilarity measure providing for a dissimilarity value indicating a dissimilarity between the first dataset and the second dataset;
• a distance measure providing for a distance value indicating a distance between the first dataset and the second dataset;
• a probability distribution function (PDF);
• a cumulative distribution function;
• or
• a complementary cumulative distribution function,
• or
• wherein the method further comprises matching a structure of at least one of the first dataset and the second dataset based on the metric so as to fit to a common data space or data structure prior to relating the first dataset and the second dataset, and wherein the matching the structure of the at least one of the first dataset and the second dataset comprises;
• an adaptation of parameter value units of the first dataset to match parameter value units of the second dataset;
• an adaptation of the parameter value units of the second dataset to match the parameter value units of the first dataset;
• or
• an adaptation of the parameter value units of the first dataset or the second dataset to commonly match the parameter value units of a third dataset.