Search

In the incoming communication system, especially for the battery constrained Internet of Things devices, consumption of power resources will be a critical performance metric. This point shows importance when throughput minimal requirement and interference limit have been carried out. This paper investigates such a power allocation problem in a multiple-parallel-channel wireless system to minimize the sum power consumed by the entire system, while meeting the sum power constrains for each group of channels and the whole system as well as meeting the throughput constraints for each of the groups and the system. Sum power minimization itself is also a key issue for margin-adaptive loading. Resorting to geometric concepts, an algorithm named as the group virtual bottom power water-filling (GVB-PWF) is proposed to solve the problem, including the large-scale problems, which computes the exact solution with a low degree of the polynomial computational complexity. Optimality of the proposed algorithm is also proved strictly. To the best of our knowledge, no prior algorithm in the open literature offered such an optimal solution to the proposed problem, with the merit of exactness and efficiency. Simulation results demonstrate that the proposed power allocation algorithm uses less power about 25%, compared with the popular primal-dual interior-point method with the same amount of computations. [ABSTRACT FROM AUTHOR]

In cognitive networks, the cooperative transmission between primary user and secondary user has been regarded as an effective method to promote harmonious coexistence between themselves where how to balance user's benefits and improve the system throughput is a key issue. In this paper, we study the joint pricing and power allocation strategy for the cognitive relay transmission by using the Stackelberg model which is a classical dynamic game model. We first give presentations of a cognitive relay model over Rayleigh fading channels and then investigate the primary benefits in power saving during this cooperation. According to the profits of primary user (as a game leader) and secondary user (as a follower), corresponding utility functions which describe their overall profits in the cognitive relay transmission are derived one by one. Then, optimal strategies for interference pricing and power allocation are fixed by resolving the objective functions. The existence of the Nash equilibrium and the sufficient conditions for the positive equilibrium are further discussed. Numerical results are presented to show that the algorithm can achieve encouraging outcomes with low-complexity. [ABSTRACT FROM AUTHOR]