By Haijun Zhang, Xiaoli Chu, Xiangming Wen
This short examines source allocation and interference administration for 4G femtocells. It introduces 4G femtocells within the context of 4G cellular networks and discusses similar technical demanding situations in source allocation and interference administration. issues comprise ant colony set of rules dependent downlink source allocation, clever scheduling and tool keep watch over, uplink and downlink for two-tier networks, caliber of carrier (QoS) constraints and the cross-tier interference constraint. The authors current algorithms to relieve universal femtocell-related difficulties reminiscent of subchannel energy allocation. The complexity of the proposed source allocation algorithms is analyzed, and the effectiveness of the proposed algorithms is confirmed by means of simulations. This concise and functional e-book at once addresses universal difficulties in relation to femtocells and source administration. It serves as a great tool for researchers within the box. Advanced-level scholars or execs drawn to femtocells and networks also will locate the content material helpful.
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Extra info for 4G Femtocells: Resource Allocation and Interference Management
5) is concave . 6) are convex, the feasible set 42 4 Resource Allocation in Femtocells with Cross-Tier Interference Limits of the objective function is convex. 5) has a unique optimal solution, which may be obtained in polynomial time. 5) is solved by using the Lagrangian dual decomposition method. 6) will be absorbed in the Karush-Kuhn-Tucker (KKT) conditions , as it will be shown later. t. 7) into a master problem and K × N subproblems. The dual problem can be solved iteratively with each FBS solving the corresponding local subproblem via local information in each iteration.
We first model the uplink power and subchannel allocation in femtocells as a non-cooperative game, where inter-cell interference is taken into account in maximizing the femtocell capacity and uplink femto-to-macro interference is alleviated by charging each femto user a price proportional to the interference that it causes to the macrocell. Based on the non-cooperative game, we then devise a semi-distributed algorithm for each femtocell to first assign subchannels to femto users and then allocate power to subchannels.
1 0 1 2 3 4 5 Number of Femto Users per Femtocell 6 Fig. 4 Tiered fairness versus the number of femto users F in each femtocell with the number of macro users M = 50 non-cooperative game framework. Using the proposed algorithm, each femtocell can maximize its capacity through resource allocation, taking into account intercell interference reported by its femto users, and with uplink femto-to-macro interference alleviated by a pricing scheme imposed on femto users. It has been shown through simulations that the proposed interference-aware resource allocation algorithm is able to provide improved capacities of both macrocell and femtocells, together with comparable tiered fairness, as compared with the existing unpriced subchannel allocation and MIWF based power allocation algorithm.