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Dimensionality reduction to solve resource allocation problem in 5G UDN using genetic algorithm
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DOI：10.1007/s00500-020-05473-8.png)
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5G ultra-dense network (UDN) systems consist of massive deployment of small cells. This technology allows increasing spectral efficiency and solving the spectrum scarcity problem. However, as small cell count increases, the probability of severe interference increases, causing a network capacity degradation. The resource allocation (RA) algorithms distribute the available spectrum resources with the least interference. It is modeled as an optimization problem, and allocating the different resources results exceedingly complex. In this work, a new design approach for RA is proposed. The strategy is based on allocating a single block of channels to either users or cells instead of disjoint channels across the available spectrum. We call them user block allocation and cell block allocation, respectively. They consider a filtered search space of channel allocations providing two-dimensionality reduction levels to the channel allocation problem. The scenario evaluation consists of an unplanned UDN and a uniform small cell deployment, where at least one active user is present for each cell. The results obtained through the genetic algorithm solution on the network's spectral efficiency, cell's average capacity, and subchannel allocation rate show that the proposed arrangements alleviate the high complexity of the channel allocation problem and find feasible solutions for UDN scenarios.
Keyword:
Ultra-dense networks
Resource allocation
Genetic algorithm
5G system
Computational complexity reduction
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