Convex Optimization
EBA: An Enhancement of the IEEE 802.11 DCF via Distributed Reservation
IEEE Transactions on Mobile Computing
Adaptive radio resource allocation in OFDMA systems: a survey of the state-of-the-art approaches
Wireless Communications & Mobile Computing - Next Generation Wireless Communications and Mobile Computing-Networking Technologies
LTE: the evolution of mobile broadband
IEEE Communications Magazine
Performance Analysis of the WLAN-First Scheme in Cellular/WLAN Interworking
IEEE Transactions on Wireless Communications
Next-generation wireless communications concepts and technologies
IEEE Communications Magazine
Hotspot wireless LANs to enhance the performance of 3G and beyond cellular networks
IEEE Communications Magazine
Mobile WiMAX systems: performance and evolution
IEEE Communications Magazine
Capacity Maximization through Energy-Aware Multi-Mode Relaying
Wireless Personal Communications: An International Journal
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In the heterogeneous networks, radio resource management (RRM) plays an important role to utilize the potential network diversity. In this paper, we study the RRM strategy in the heterogeneous networks involved with an orthogonal frequency division multiple access (OFDMA) network, with the aim of maximizing the minimum user throughput. An analytical model which reflects the feature of heterogeneous networks is presented in order to formulate the RRM problem. Assuming that the system can support multi-homing access and the subcarrier can be shared by multiple users in the OFDMA network, the problem can be formulated by a convex optimization problem and the optimal solution is obtained. We also propose a suboptimal RRM algorithm for practical applications, including network selection and resource allocation in each network. The performance of the proposed RRM algorithms is evaluated in the heterogeneous long term evolution (LTE)-wireless local area network (WLAN) networks. Our simulation results show considerable gains in comparison to the performance of LTE-Only and WLAN-First strategies. In addition, the performance gap between the optimal solution and suboptimal algorithm becomes minor as the number of users increases.