دانلود رایگان مقاله زمانبندی خواب انرژی BS و RS در شبکه سلولی رله کمکی

Abstract

The deployment of relay stations (RSs) offers a promising and viable approach to satisfy the increasing need of high data rate in cellular networks. With the expected increase of the number of RSs, the energy efficiency (EE) becomes a crucial system design parameter. One of the most effective energy saving methods is to switch off some stations. In this paper, joint base station (BS) and RS sleep scheduling algorithms are investigated in relay-assisted cellular networks. We aim to maximize the EE of the relay-assisted cellular networks under the spectral efficiency (SE) constraint. First, we establish a mathematical model which is a mixed integer nonlinear fractional programming problem. To solve it with globally optimal solution, a branch and bound (BnB) algorithm based on the denominator interval values of the objective function is designed and its convergence is proved theoretically. Then, two kinds of sub-optimal algorithms are proposed to compare with the optimal algorithm: one is a greedy algorithm and the other is based on the Cellular Automata (CA) theory. Simulation results are presented to demonstrate the effectiveness of our algorithms.

5. Conclusions

In this paper, we have proposed joint BS and RS sleep scheduling algorithms and investigate the EE maximization problem in the relay-assisted cellular network. A mixed integer nonlinear fractional programming mathematical model is constructed for the optimization problem. In particular, the proposed BnB algorithm can obtain the globally optimal EE, and the convergence of the BnB is proved. Moreover, we have proposed a greedy algorithm and a CA algorithm to compare with the BnB algorithm. Results have demonstrated that the BnB algorithm can achieve the globally optimal EE and is consistent with the results obtained by exhaustive search. The BnB algorithm is superior to the greedy and CA algorithms in improving the EE. Furthermore, performance of the proposed algorithms is better than that of the scheme without sleep scheduling. Convergence of the algorithms is also illustrated.