Network-assisted optimal rate control methods in cognitive networks

Abstract

Orienting the multi-rate cognitive networks,overcoming the typical characteristics of dynamics to implement the autonomy and rationality of rate control,first the rate control framework based on the presented improved IEEE 1900.4 architecture was proposed.Meanwhile,different scaled rate control schemes on different levels were investigated.Then,the real-time rate control problem on the terminal we concentrate on.Most importantly,both the distributed rate selection of TRM towards RNRM and the centralized rate allocation of RNRM to TRM were investigated.Simulation results show that the latter can achieve 60% utility and certain fairness improvements,in addition,the rationality and fairness guaranteed by the newly-built pricing function is verified.

Keywords

• cognitive networks;rate control;game theory;IEEE 1900.4