Attribute-based encryption (ABE) is a preferred technology used to access control the data stored in the cloud servers. However, in many cases, the authorized decryption user may be unable to decrypt the ciphertext in time for some reason. To be on the safe side, several alternate users are delegated to cooperate to decrypt the ciphertext, instead of one user doing that. We provide a ciphertext-policy ABE scheme with shared decryption in this article. An authorized user can recover the messages independently. At the same time, these alternate users (semi-authorized users) can work together to get the messages. We also improve the basic scheme to ensure that the semi-authorized users perform the decryption tasks honestly. An integrated access tree is used to improve the efficiency for our scheme. The new scheme is proved CPA-secure in the standard model. The experimental result shows that our scheme is very efficient on both computational overhead and storage cost.

Energy efficiency is becoming more and more important to the development of wireless communication. In this paper, we study energy-efficient resource allocation in an Orthogonal Frequency Division Multiplexing (OFDM) system with mixed traffic. Considering both the energy efficiency and spectral efficiency, we model the allocation of sub-carriers and power as a mixed integer nonlinear programming (MINLP) problem maximizing the utility per Watt. The formulated problem is non-convex and is computationally forbidden. To simplify the solution of the problem, a two-step resource allocation (TSRA) algorithm is proposed. In the first step, we simplify the problem to a convex one and obtain the sub-carrier allocation using Karush-Kuhn-Tucker (KKT) conditions. On this basis, we solve the power allocation problem in the second step by transforming it into a parametric programming problem and applying Dinkelbach's theory. Simulation results show that our algorithm can provide 28% energy efficiency improvement compared to conventional algorithms.

In cellular wireless networks, base station (BS) cooperation is a promising technique to realize high spectral efficiency, whose potential gain, however, is restricted by the backhaul network. In this paper, we consider combining different decentralized cooperative strategies to fully utilize the limited backhaul. Firstly, the impact of limited backhaul capacity on different cooperative strategies is modeled. Then, we develop a analytical framework that gives a mathematical expression for the combination idea. Afterwards, we consider the establishment of the combination to fully exploit the backhaul capacity as well as the wireless channel realizations, which is a scheduling problem consisting of strategy selection and backhaul capacity allocation. A heuristic algorithm with polynomial time complexity is proposed. Finally, the validity of the combination idea and the proposed algorithm are confirmed by Monte Carlo simulations.

Resource allocation in Orthogonal Frequency Division Multiplexing (OFDM) system with mixed traffic is studied in this paper. The sub-carriers and power of a base station (BS) are allocated to users to maximize energy efficiency, which is measured by utility per Watt. We model the allocation of sub- carriers and power as a mixed integer nonlinear programming (MINLP) problem, which is computationally forbidden due to its non-concave objective function, non-convex feasible region and integer variables. To simplify the solution of the problem, a two-step resource allocation (TSRA) algorithm is proposed. In the first step, the integer variables are transformed into continuous variables and uniform power allocation is assumed. On this basis, sub-carrier allocation is obtained using KKT condition. Knowing the allocation of sub- carrier, the optimal power allocation is solved by an iterative sub-gradient method in the second step. Simulation results show that our algorithm can provide 25% energy efficiency improvement compared to conventional algorithms.