With the advance of the photovoltaic panel technology, the infrastructure equipment of cellular networks with solar energy sources has attracted extensive interests. It is expected that base stations (BSs) and relay stations (RSs) with renewable energy will play important roles in reducing the power consumption from electrical grids in future green cellular networks. Inspired by this technology trend, this paper considers a heterogeneous green cellular network, in which a part of RSs is powered by solar energy sources to represent the incremental deployment for the infrastructure with renewable energy in the near future. We formulate a new relay selection and power allocation problem with Mixed Integer Linear Programming to select solar-powered RSs and grid-powered RSs, such that the total grid power consumption is effectively minimized in decode-and-forward cooperative communication networks. We design an algorithm to derive the optimal solution, and also devise an efficient distributed algorithm to reduce the computational cost. The simulation results demonstrate that the algorithms can effectively reduce the total grid power consumption with different channel conditions, different deployments of RSs in a network, and different available power levels in solar-powered RSs. In addition, the problem model and the proposed algorithms can be extended to support hybrid energy sources.

With the recent emergence of 3D TVs, video service providers now face an opportunity to provide high resolution multi-view 3D videos over IP networks. One simple way is to deliver each desired view in a multicast stream. Nevertheless, it is expected that significantly increased bandwidth will be required to support the transmission of all views in multi-view 3D videos. However, the recent emergence of a new video synthesis technique called Depth-Image-Based Rendering (DIBR) suggests that a multi-view 3D video does not necessarily require the transmission of all views. Therefore, we formulate a new problem, named Multi-view and Multicast Delivery Selection Problem (MMDS), and design an algorithm, called MMDEA, to find the optimal solution. Simulation results manifest that using DIBR can effectively reduce bandwidth consumption by 35% compared to the original multicast delivery scheme.

Depth-Image-Based Rendering (DIBR) is a popular technology and enables the viewers to watch multi-view 3D videos via TV or smart phone. In this paper, we propose a game-theoretical framework over a multi-view and multi-video network where one server delivers multiple multi-view 3D videos to multiple viewers. In a mobile network, any individual viewers can subscribe to a video with any viewing angle within a specified viewing range in 3D-enabled mobile handsets. To facilitate efficient resource allocation for multi-view 3D videos, we formulate a new resource allocation problem, named Price-based 3D Viewing Range Control problem (PVRC), as a Stackelberg game in Game Theory, in which the server and the viewers are modeled as the leader and the followers, respectively, to jointly consider the revenue of the server and the utilities of the viewers. We analyze the price setting problem by investigating the Stackelberg equilibrium between the server and viewers. Simulation results demonstrate that compared to popular uniform-price setting, non-uniform pricing is an effective approach for reducing the difference of utilities among the viewers, effectively controlling the viewing ranges and avoiding starvation of the network resources to only few viewers. Moreover, we also derive the social optimum in the problem, and the simulation results show that the derived Stackelberg equilibrium is close to the social optimum.

The effectiveness of epidemic routing for information dissemination in energy harvesting wireless sensor networks is examined in this work. Here, information is to be disseminated from a few nodes to a considerable fraction of all other nodes in the network. The use of epidemic routing is motivated by the fact that, when sensors are supported solely by harvested energy, the sensors' availability and the network topology may change dynamically due to the uncertainty of the energy arrival at the sensors. With epidemic routing, a node will receive and forward a packet to all other nodes in its neighborhood whenever it is able to do so. Each node will keep the packet only for a certain time duration depending on its recovery rate. By utilizing only energy harvested from the environment, the transmission radius of each sensor (and, thus, the network connectivity) is affected by its local energy arrival and the time in between transmissions. The less frequently it transmits, the further the distance it is able to reach. Two cases are examined in this work: 1) the case with identical transmission radius and 2) the case with identical inter-transmission time. The first case occurs when sensors transmit with fixed power and the second case occurs when the sensors operate under a fixed sleep-wake cycle or TDMA scheduling. The transmission radius and intertransmission time required to guarantee that a considerable fraction of nodes receive the information is derived for a given sensor density and recovery rate. Computer simulations are provided to validate our theoretical claims.