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In Fixed Channel Allocation or Fixed Channel Assignment (FCA) each cell is given a predetermined set of frequency channels. FCA requires manual frequency planning, which is an arduous task in time-division multiple access (TDMA) and frequency-division multiple access (FDMA) based systems since such systems are highly sensitive to co-channel interference from nearby cells that are reusing the ...
The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]
Detrended correspondence analysis (DCA) is a multivariate statistical technique widely used by ecologists to find the main factors or gradients in large, species-rich but usually sparse data matrices that typify ecological community data. DCA is frequently used to suppress artifacts inherent in most other multivariate analyses when applied to ...
Maximum throughput scheduling is a procedure for scheduling data packets in a packet-switched best-effort network, typically a wireless network, in view to maximize the total throughput of the network, or the system spectral efficiency in a wireless network. This is achieved by giving scheduling priority to the least "expensive" data flows in ...
Dynamic RRM schemes adaptively adjust the radio network parameters to the traffic load, user positions, user mobility, quality of service requirements, base station density, etc. Dynamic RRM schemes are considered in the design of wireless systems, in view to minimize expensive manual cell planning and achieve "tighter" frequency reuse patterns, resulting in improved system spectral efficiency.
If the sample size is 1,000, then the effective sample size will be 500. It means that the variance of the weighted mean based on 1,000 samples will be the same as that of a simple mean based on 500 samples obtained using a simple random sample.
Direct coupling analysis or DCA is an umbrella term comprising several methods for analyzing sequence data in computational biology. [1] The common idea of these methods is to use statistical modeling to quantify the strength of the direct relationship between two positions of a biological sequence , excluding effects from other positions.
The value 3.267 is taken from the sample size-specific D 4 anti-biasing constant for n=2, as given in most textbooks on statistical process control (see, for example, Montgomery [2]: 725 ). Calculation of individuals control limits