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.

5G超密集网络（UDN）系统由大规模部署小型蜂窝组成。该技术可以提高频谱效率并解决频谱稀缺问题。但是，随着小小区数量的增加，严重干扰的可能性也会增加，从而导致网络容量下降。资源分配（RA）算法以最小的干扰分配可用频谱资源。它被建模为一个优化问题，分配不同的资源结果极其复杂。在这项工作中，提出了一种新的RA设计方法。该策略基于为用户或小区分配单个信道块，而不是在可用频谱上分配不相交的信道。我们分别称它们为用户块分配和单元块分配。他们考虑了经过过滤的信道分配搜索空间，从而为信道分配问题提供了二维降级。方案评估包括计划外的UDN和统一的小型小区部署，其中每个小区至少有一个活动用户。通过遗传算法解决方案获得的网络频谱效率，小区平均容量和子信道分配速率的结果表明，所提出的方案减轻了信道分配问题的高复杂性，并为UDN方案找到了可行的解决方案。