JOURNAL ARTICLE

Energy efficient resource allocation for cognitive radio networks with imperfect spectrum sensing

Abstract

This paper investigates the energy efficient resource allocation strategy for OFDM-based cognitive radio (CR) networks with imperfect spectrum sensing. The interference model taking the sensing errors into account is formulated at first. And the objective is to maximize the energy efficiency of the multiuser CR system subject to the total transmission power budget and each primary user's (PU) interference constraints. As the primal problem is a mixed integer nonlinear programming issue, we will separate the resource allocation scheme into two steps, i.e., subcarrier assignment and power allocation. After the suboptimal subcarrier assignment, an optimal power allocation algorithm is proposed based on fractional programming and sub-gradient method. The simulation results show that the proposed resource allocation scheme can achieve higher energy efficiency than the one maximizing the capacity of the CR networks. Meanwhile, it can protect the normal communication of each PU compared to the scheme without considering sensing errors.

Keywords:
Cognitive radio Subcarrier Computer science Resource allocation Mathematical optimization Interference (communication) Efficient energy use Orthogonal frequency-division multiplexing Resource management (computing) Nonlinear programming Integer programming Throughput Power budget Optimization problem Power (physics) Computer network Algorithm Telecommunications Power control Nonlinear system Engineering Wireless Mathematics Electrical engineering

Metrics

14
Cited By
2.17
FWCI (Field Weighted Citation Impact)
12
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cognitive Radio Networks and Spectrum Sensing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Wireless Network Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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