Underlay Cognitive Radio with Full or Partial Channel Quality Information

TL;DR

This paper investigates underlay cognitive radio systems with varying levels of channel quality information, proposing new approaches for partial CQI scenarios and analyzing their impact on secondary user capacity and primary user interference.

Contribution

It introduces a location-aided UCR model with partial CQI and develops new approaches that improve secondary user rates under limited channel information.

Findings

Partial CQI approaches achieve comparable secondary rates to full CQI systems.

The proposed methods reduce primary user capacity penalty.

Numerical results demonstrate the effectiveness of partial CQI strategies.

Abstract

Underlay cognitive radios (UCRs) allow a secondary user to enter a primary user's spectrum through intelligent utilization of multiuser channel quality information (CQI) and sharing of codebook. The aim of this work is to study two-user Gaussian UCR systems by assuming the full or partial knowledge of multiuser CQI. Key contribution of this work is motivated by the fact that the full knowledge of multiuser CQI is not always available. We first establish a location-aided UCR model where the secondary user is assumed to have partial CQI about the secondary-transmitter to primary-receiver link as well as full CQI about the other links. Then, new UCR approaches are proposed and carefully analyzed in terms of the secondary user's achievable rate, denoted by $C_2$, the capacity penalty to primary user, denoted by $\Delta C_1$, and capacity outage probability. Numerical examples are provided to visually compare the performance of UCRs with full knowledge of multiuser CQI and the proposed approaches with partial knowledge of multiuser CQI.