Abstract
The present study proposes a new algorithm for device‐to‐device (D2D) user density identification in a 5G network based on resource allocation. The method initially established a multiobjective optimization function that calculates system throughput and quality of service (QoS) of D2D users. The optimal resource allocation result of the multiobjective function is obtained via the improved whale optimization algorithm (IWOA). System throughput after resource allocation exhibits a linear relationship with the number of users. Therefore, the D2D user density areas are accurately identified via the throughput value. The simulation result reveals that the accuracy of D2D user density identification reaches 95%.
Highlights
With the popularization and performance improvement of smartphones, it is important for a 5G network to satisfy individuals’ demands for ultrahigh tra c density and connection density
The study proposes a resource allocation method based on user interrupt probability and connection probability to maximize system throughput. e study [5] proposes a new resource allocation method based on the interference control mechanism of DT maximum/minimum power standard, and this decreases the interference of hybrid cellular networks. e study [6] proposes a method that guarantees the quality of service (QoS) the method does not improve the throughput. e study [7] proposes the resource allocation method under a 28 GHz bandwidth, and this improves system throughput via limiting the interference value it does not signi cantly decrease interference
In [9], the resource allocation problem in the underlying cellular network of D2D communication was de ned as a game of alliance formation, and the power allocation was optimized by the whale optimization algorithm (WOA). is method maximizes the throughput of the D2D system and guarantees the Complexity minimum rate per user
Summary
With the popularization and performance improvement of smartphones, it is important for a 5G network to satisfy individuals’ demands for ultrahigh tra c density and connection density. The study proposes a resource allocation method based on user interrupt probability and connection probability to maximize system throughput. E study [5] proposes a new resource allocation method based on the interference control mechanism of DT maximum/minimum power standard, and this decreases the interference of hybrid cellular networks. E study [8] proposes an adaptive power control method based on the cellular user interference threshold that maximizes energy e ciency under the condition of satisfying the minimum QoS of D2D users. The multiobjective optimization function is solved via the improved whale optimization algorithm (IWOA), and the result corresponds to an optimal resource allocation method. Erefore, D2D user density areas are accurately identi ed by the throughput value after performing the optimal resource allocation method. Experimental results indicate that the proposed algorithm obtains a high-accuracy result for D2D user density identi cation
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