SUMMARYIn this paper, we study the resource allocation problem of the uplink transmission with delay quality-ofservice constraints in two-tier femtocell networks. Particularly, to provide statistical delay guarantees, the effective capacity is employed as the network performance measure instead of the conventional Shannon capacity. To make the problem computationally efficient and numerically tractable, we decompose the problem into three subproblems, namely, cluster configuration subproblem, intra-cluster subchannel allocation subproblem and inter-cluster power control subproblem. Firstly, we develop a low-complexity heuristic semi-dynamic clustering scheme, where the delay of the channel state information feedback via backhaul is considered. We model such system in the framework of networked partial observation Markov decision process and derive a strategy to reduce the search range for the best cluster configuration. Then, for a given cluster configuration, the cluster heads deal with subchannel allocation and power control within each cluster. We propose a subchannel allocation scheme with proportional fairness. Thereafter, the inter-cluster power control subproblem is modeled as a set of exact potential games, and a channel quality related pricing mechanism is presented to mitigate inter-cluster interference. The existence and uniqueness of Nash equilibriums for the proposed game are investigated, and an effective decentralized algorithm with guaranteed convergence is designed. Simulation results demonstrate that the proposed algorithms not only have much lower computational complexity but also perform close to the exhaustive search solutions and other existing schemes.

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Femtocells have attracted growing attention in academia, industry, and standardization forums in recent years. However, most of existing works on femtocell networks are focused on spectrum efficiency and interference mitigation, energy efficiency aspect is neglected. In this paper, we investigate the energy efficient resource allocation of downlink femtocell networks in sparsely and densely deployed scenario respectively. To decrease the complexity, joint subchannel allocation and power control are decomposed into two steps. Firstly, given subchannel allocation, a closed-form best response of transmit power is obtained. Secondly, a fair energy efficient subchannel allocation metric has been derived out. At last, we propose a distributed suboptimal subchannel allocation and low-complex power control algorithm. Simulation results show that the proposed algorithm has a low complexity with slight loss of energy efficiency compared with Round-Robin Scheduling and a non-cooperative energy-efficient power optimization algorithm. 