Tradeoff Analysis between Spectral and Energy Efficiency Based on Sub-Channel Activity Index in Wireless Cognitive Radio Networks

Abstract

In recent years, there has been a rapid evolution of wireless technologies that has led to the challenge of high demand for spectral resources. To overcome this challenge, good spectrum management is required that calls for more efficient use of the spectrum. In this paper, we present a general system, which makes a tradeoff between the spectral efficiency (SE) and energy efficiency (EE) in the cellular cognitive radio networks (CCRN) with their respective limits. We have analyzed the system taking into account the different types of power used in the CCRN, namely the spectrum detection power (Zs) and the relay power (Zr). Optimal policy for emission power allocation formulated in the function of sub-channel activity index (SAI) as an optimization problem in order to maximize spectrum utilization and minimize the energy consumption in the base station of the secondary system energy consumption, is subject to different constraints of the main user system. We also evaluate the collaborative activity index of the sub-channel describing the activity of the primary users in the CCRN. The theoretical analyses and simulation results sufficiently demonstrate that the SE and EE relationship in the CCRN is not contrary and thus the achievement of optimal tradeoff between SE and EE. By making a rapprochement with a cognitive cellular network where SBSs adopts an equal power allocation strategy for sub-channels, the results of our proposed scheme indicate a significant improvement. Therefore, the model proposed in this paper offers a better tradeoff between SE and EE.

WITHDRAWN: A Survey on the Performance Analysis of NOMA-Assisted Cognitive Radio Sensor Networks

“…The SS unit allows the SU to sense the channel and promptly vacate it when the PU resumes its activities. By employing spectrum sensing, CR networks enable efficient and reliable utilization of the available spectrum resources [7][8] [9].…”

Improved hard fusion methods for enhancing detection and energy efficiency in cognitive radio networks

“…The spectral efficiency (SE) of a network is defined as the ratio of the number of bits transmitted per second for a given bandwidth [26,27]. Table 15 demonstrates the comparison of SE achieved by the conventional and proposed relay assisted hard fusion methods.…”

Spectral and energy efficiency tradeoff in optical code division multiple access networks

“…In a communication system, the EE and SE are often conflicting metrics, that is, increasing one parameter reduces another and vice versa 4‐10 . Moreover, in the CDMA‐based systems, the use of sophisticated detection techniques has a positive impact on the EE‐SE tradeoff, since advanced detectors are able to reduce the effects of multiple access interference (MAI), so that the power levels necessary to achieve quality of service (QoS) can be reduced substantially, resulting in more energy efficient systems.…”