Convex Optimization
Resource Allocation in Multiuser Multicarrier Wireless Systems
Resource Allocation in Multiuser Multicarrier Wireless Systems
Fairness-aware resource allocation in OFDMA cooperative relaying network
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Semi-Distributed User Relaying Algorithm for Amplify-and-Forward Wireless Relay Networks
IEEE Transactions on Wireless Communications
Cooperative diversity in wireless networks: Efficient protocols and outage behavior
IEEE Transactions on Information Theory
Multiuser OFDM with adaptive subcarrier, bit, and power allocation
IEEE Journal on Selected Areas in Communications
Opportunistic transmission scheduling with resource-sharing constraints in wireless networks
IEEE Journal on Selected Areas in Communications
Dynamic load balancing and sharing performance of integrated wireless networks
IEEE Journal on Selected Areas in Communications
Resource Allocation for OFDMA Relay Networks With Fairness Constraints
IEEE Journal on Selected Areas in Communications
IEEE Journal on Selected Areas in Communications
Joint optimization of relay strategies and resource allocations in cooperative cellular networks
IEEE Journal on Selected Areas in Communications
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In this paper, we derive optimal joint power allocation, subchannel pairing and scheduling strategies in multiple orthogonal channels multiple users wireless networks in the presence of a single regenerative relay node. Two models with users' data rate request (fairness) constraint in different time domains are considered. The first one is called deterministic model in which each user's data rate request has to be satisfied in each time slot t (named short term fairness constraint) and the second one is called stochastic model in which users have average data rate request (named long term fairness). In these two models the optimization problems of maximizing system capacity with total transmit power constraint and fairness constraint are formulated. The Lagrangian dual method is used to derive the optimal solution for deterministic model and in the stochastic model stochastic approximation and dual method are employed to find out the optimal algorithm. Both algorithms have polynomial times complexity, which is reduced significantly compared with the Exhaustive Search Method (ESM). Since Lagrangian dual method is utilized in both schemes, the dual gap is also analyzed. Furthermore, through the analysis and simulation, we see that the optimal resource allocation algorithm in stochastic model has better performance than that in the deterministic model for its ability to exploit temporal diversity.