Estimation-Throughput Tradeoff for Underlay Cognitive Radio Systems

TL;DR

This paper investigates how channel estimation errors impact the throughput of underlay cognitive radio systems, revealing that traditional models tend to overestimate system performance and proposing a new model to better understand the tradeoff.

Contribution

It introduces a novel model that accounts for channel estimation errors in underlay cognitive radio systems, analyzing the estimation-throughput tradeoff and identifying the maximum achievable throughput.

Findings

Conventional models overestimate system performance.

The new model accurately captures the impact of estimation errors.

Maximum throughput is determined under realistic estimation conditions.

Abstract

Understanding the performance of cognitive radio systems is of great interest. To perform dynamic spectrum access, different paradigms are conceptualized in the literature. Of these, Underlay System (US) has caught much attention in the recent past. According to US, a power control mechanism is employed at the Secondary Transmitter (ST) to constrain the interference at the Primary Receiver (PR) below a certain threshold. However, it requires the knowledge of channel towards PR at the ST. This knowledge can be obtained by estimating the received power, assuming a beacon or a pilot channel transmission by the PR. This estimation is never perfect, hence the induced error may distort the true performance of the US. Motivated by this fact, we propose a novel model that captures the effect of channel estimation errors on the performance of the system. More specifically, we characterize the performance of the US in terms of the estimation-throughput tradeoff. Furthermore, we determine the maximum achievable throughput for the secondary link. Based on numerical analysis, it is shown that the conventional model overestimates the performance of the US.