Portfolio selection based power allocation in OFDM Cognitive Radio networks

Abstract

In most existing channel decision mechanisms for Cognitive Radio (CR), it is assumed that instantaneous channel state information (CSI) and Primary User (PU) activity information is available. However, in many CR network applications, frequent channel sensing and estimation could introduce excessive overhead and reduce system throughput. Channel sensing by Secondary Users (SUs) may also not be completely reliable, and sensing error could result in reduced PU and SU Quality of Service (QoS). In this paper we examine the recently proposed use of historical CSI, combined with Portfolio Theory based optimization to arrive at joint channel decision and power allocation strategy for CR-OFDM. By also considering historical PU occupancy statistics, we extend this method to enable provision of a soft guarantee for both PU and SU traffic QoS. Simulation results show the effectiveness of the improved method in increasing the SU throughput and reducing PU interference, especially under conditions where the PU occupancy and signal to noise and interference ratio (SNIR) is positively correlated.