Spectrum-sharing Femtocell Network Research Articles

Game theoretic approach for joint resource allocation in spectrum sharing femtocell networks

In this paper, we study the joint price and power allocation in spectrum sharing macro-femtocell networks. The proposed game theoretic framework is based on bi-level Stackelberg game where macro base station (MBS) works as a leader and underlaid femto base stations (FBSs) work as followers. MBS has fixed data rate and imposes interference price on FBSs for maintaining its data rate and earns revenue while FBSs jointly adjust their power for maximizing their data rates and utility functions. Since the interference from FBSs to macro user equipment is kept under a given threshold and FBSs compete against each other for power allocation, there is a need to determine a power allocation strategy which converges to Stackelberg equilibrium. We consider two cases for MBS power allocation, i.e., fixed and dynamic power. MBS can adjust its power in case of dynamic power allocation according to its minimum data rate requirement and number of FBSs willing to share the spectrum. For both cases we consider uniform and nonuniform pricing where MBS charges same price to all FBSs for uniform pricing and different price to each FBS for non-uniform pricing according to its induced interference. We obtain unique closed form solution for each case if the co-interference at FBSs is assumed fixed. And an iterative algorithm which converges rapidly is also proposed to take into account the effect of co-tier interference on interference price and power allocation strategy. The results are explained with numerical simulation examples which validate the effectiveness of our proposed solutions.

Distributed power optimization for spectrum-sharing femtocell networks: A fictitious game approach

Power control techniques are becoming increasingly important for a two-tier network, where a central macrocell is underlaid with femtocells, since cross-tier and co-tier interference severely limits network performance. In this paper, we propose a distributed power control scheme for the uplink transmission of spectrum-sharing femtocell networks based on fictitious game. Each user announces a price that reflects its sensitivity to the current interference level, and adjusts its power to maximize its utility. Power and price are updated at terminals and base stations, respectively. The scheme is proved to converge to a unique optimal equilibrium. Furthermore, we propose a simple macrocell link protection scheme, where a macro user can protect itself by increasing its price. Most importantly, we investigate the power optimization scheme proposed in frequency-selective channels based on the Stackelberg game, in which each user prices its limited power allocated to subchannels. Numerical results show that the proposed schemes are effective in resource allocation for spectrum-sharing two-tier networks.

Stackelberg game based interference management for two-tier femtocell networks

Femtocell is viewed as a promising option for mobile operators to improve coverage and provide high-data-rate services in a cost-effective manner. This paper considers the uplink interference management problem in a spectrum-sharing femtocell network. Assuming that the macrocell base station (MBS) is rewarded for sharing the spectrum with femtocells by setting a reasonable interference cap (IC) for femtocell users’ (FUEs’) transmissions. Within IC, the FUEs allocate their transmission powers competitively while not introducing much interference to both the macrocell users (MUEs) and other FUEs. A Stackelberg game is formulated to jointly maximize the utility of MBS and the individual utility of FUEs. Specifically, the maximum tolerable interference at the MBS is used as the resource that the leader (MBS) and the followers (FUEs) compete for. Then, the backward induction method is applied to achieve the Stackelberg equilibrium and a distributed power update rule is developed for FUEs. In addition, the implementation protocol is presented, some issues related to the implementations and some future extensions regarding the MUEs’ uplink protection are discussed. Lastly, numerical results demonstrate the performance of our proposed power allocation in detail, and show the effects of varying the number of FBSs and changing other system parameters on the system’s performance.

Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach

This paper investigates the price-based resource allocation strategies for the uplink transmission of a spectrum-sharing femtocell network, in which a central macrocell is underlaid with distributed femtocells, all operating over the same frequency band as the macrocell. Assuming that the macrocell base station (MBS) protects itself by pricing the interference from the femtocell users, a Stackelberg game is formulated to study the joint utility maximization of the macrocell and the femtocells subject to a maximum tolerable interference power constraint at the MBS. Especially, two practical femtocell channel models: sparsely deployed scenario for rural areas and densely deployed scenario for urban areas, are investigated. For each scenario, two pricing schemes: uniform pricing and non-uniform pricing, are proposed. Then, the Stackelberg equilibriums for these proposed games are studied, and an effective distributed interference price bargaining algorithm with guaranteed convergence is proposed for the uniform-pricing case. Finally, numerical examples are presented to verify the proposed studies. It is shown that the proposed algorithms are effective in resource allocation and macrocell protection requiring minimal network overhead for spectrum-sharing-based two-tier femtocell networks.