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The spectrum scheduler (SS) forms an optimal schedule by incorporating the observations and calculations from different components within the spectrum allocator with the prime objective of interference avoidance (eviction/silence) with PU and transmission power reduction.
We describe the phases of the proposed FA algorithms, saturation metric, and coloring label with the objective of interference minimization and throughput maximization and the transmit power control strategy in Section 5.
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The precoder obtained with the objective of weighted interference minimization allows some multiuser interference in the system, and it is shown to improve the sum rate by 66% compared to a conventional zero forcing approach, for those users experiencing low signal to interference plus noise ratio.
A new CAA, Topology-controlled Interference-aware Channel-assignment Algorithm (TICA), which uses the Select x for less than x TCA to intelligently assign the available channels to the MRs with the objective of minimizing interference and hence, improving network throughput.
The main contributions of this study are as follows: A new TCA, Select x for less than x, that builds the network connectivity graph by selecting the nearest neighbors for each mesh node in the network with the objective of minimizing interference among MRs and enhancing frequency reuse as well as simultaneously ensuring a connected network.
Our proposed TCA controls the network topology by selecting the nearest neighbors for each mesh node in the network with the objective of minimizing interference among MRs. The proposed TCA, which is shown in Figure 1, is based on the following assumptions: Figure 1 Select x for less than x TCA.
Here, we investigate the different algorithms with the objective of the minimal interference and maximal throughput.
Given these weights, the two proposed power adjustment strategies have the common objective of mitigating the interference on victim MUEs while implementing two different degrees of awareness of FUEs' throughput degradation.
We have presented centralized and distributed sequential algorithms that can assign channels to the SU communication links in the CR network with the objective of minimizing network interference (CminSumInt, DminInt) and maximizing network throughput (CMaxSumCap, DMaxCap).
The channel assignment (CA) problem is one of the most important issues in CRNs, with the objective of satisfying the interference constraints, and maximizing the number of nodes with channels assigned.
In order to find a closed-form solution for Eq. (21), we consider an assumption already made in[29], in which it is considered the use of a whitening filter with the objective of converting the interference into an approximately Gaussian signal.
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