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This paper aims at improving the energy efficiency of OFDMA small cell networks with data rate constraints. Different with the existing energy efficiency works that focus on the base station side, the effect of backhaul links is analyzed based on a bufferless data flow model. A joint forward and backhaul link optimization (JFBLO) scheme is proposed to iteratively increase the system energy efficiency by optimizing the emission power and backhaul data rate. The system energy efficiency is proved to be non-decreasing and convergent in JFBLO. Simulation results indicate that though occupying a small share of the total system power consumption, the emission power is necessary to be optimized to improve the system energy efficiency when the effect of backhaul links is considered.

In order to offload network traffic, we design a device caching strategy by jointly considering a popularity model, social influence and incentive design in this paper. Firstly, we propose a prediction model by virtue of users' social network information to evaluate users' encounter probability. Moreover, users' content preference is predicted using users' context information. Based on these predicted values, a content placement algorithm is described provided that the users will fully cooperate to optimize system performance. Thereafter, a more practical scenario where users are selfish and unwilling to devote their resources is considered. A Stackelberg game is established between the mobile network operator (MNO) and users by providing an incentive to encourage cooperation. Device caching strategy and incentive price design are determined by analyzing the Stackelberg game and finding the Stackelberg equilibrium point. We verify the effectiveness of our prediction models utilizing real data sets. Simulation results show that the cache hit ratio can be considerably improved by exploiting social and context information. Incentive design and profit analysis are also thoroughly investigated.

Many real-world phenomena can be described as complex contagions, which has attracted much attention in the field of network science. However, the effects of the heterogeneous adoption thresholds on complex contagions in weighted networks have not been systematically investigated. In this paper, we propose a heterogeneous complex contagion model on the weighted network, in which individuals have different adoption thresholds. For individuals with a relatively small adoption threshold, they are more likely to adopt the contagion and act as activists. An edge-weight based compartmental theory is developed to unveil spreading dynamics. Through extensive numerical simulations and theoretical analysis, we find that, for any weight distribution heterogeneity, with the increase of the activist fraction, the growth pattern of the final adoption size versus the information spreading probability changes from hybrid phase transition to a second-order continuous phase transition. Meanwhile, increasing the activist fraction can promote behavior spreading. Through bifurcation analysis, we discover that changing the heterogeneity of the weight distribution will not change the type of phase transition. Besides, reducing weight distribution heterogeneity can facilitate behavior spreading. Extensive numerical simulations verify that the theoretical solutions coincide with the numerical results very well. INDEX TERMS Complex contagions, heterogeneous adoption, weighted networks, threshold model, compartmental theory.

This paper aims at improving the system throughput of orthogonal frequency division multiple access small cell networks. Different with traditional schemes that neglect the cooperation among small cells, a scheme named as resource block exclusion-based power control (RBEBPC) is proposed by sharing the interference correlated information. RBEBPC consists of two steps that are iteratively conducted. First, based on current power allocation results, partial system resource blocks are excluded by playing the formulated cooperative coalition formation games. Second, the transmission power of each small cell is determined by solving a modified throughput maximization problem after the resource block exclusion. As the generated interference is constrained in the second step, part of the small cells transmit without full power. Thereby, the overall system interference keeps non-increasing after RBEBPC is adopted. Simulation results indicate that about 15% system throughput gain and 13% power saving gain are obtained compared to traditional iterative water filling scheme.