Resource Block Allocation: Performance Comparison of Auction, Greedy, and Round Robin Algorithms

Heterogeneous Networks (HetNets) that integrate Wi-Fi, 4G, and 5G technologies present significant challenges in resource management and power allocation. This study evaluates the performance of resource block (RB) allocation in a two-level HetNet model consisting of one macro cell base station (MBS) and four small cell base stations (SBS). Utilizing K-Medoids clustering, allocations are analyzed under various conditions using Greedy, Auction, and round robin algorithms. Simulations reveal that the Greedy algorithm outperforms the Auction and round robin algorithms in optimizing data rate, sum rate, spectral efficiency, power efficiency, and fairness. Specifically, the Greedy algorithm achieves an average data rate of 1.642 bps, an average sum rate rate of 1.218 bps, an average spectral efficiency of 3.046 bps/Hz, an average power efficiency of 1.650 bps/W, and an average fairness of 0.329, indicating its effectiveness in improving HetNet performance.