Joint Spectrum Sensing and Resource Allocation in Multi-Band-Multi-User Cognitive Radio Networks

Xu Wang, Sabit Ekin, Erchin Serpedin

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In this paper, the joint spectrum sensing and resource allocation problem is investigated in a multi-band-multi-user cognitive radio (CR) network. Assuming imperfect spectrum sensing information, our goal is to jointly optimize the sensing threshold and power allocation strategy such that the average total throughput of secondary users (SUs) is maximized. Additionally, the power of SUs is constrained to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a nonconvex mixed integer non-linear programming (MINLP) optimization problem. Our contribution in this paper is threefold. First, it is illustrated that the dimension of the nonconvex MINLP problem can be significantly reduced, which helps to re-formulate the optimization problem without resorting to integer variables. Second, it is demonstrated that the simplified formulation admits the canonical form of a monotonic optimization and an ∈-optimal solution can be achieved using the polyblock outer approximation algorithm. Third, a practical low-complexity spectrum sensing and resource allocation algorithm is developed to reduce the computational cost. Finally, the effectiveness of proposed algorithms is verified by simulations.

Original languageEnglish
JournalIEEE Transactions on Communications
DOIs
Publication statusAccepted/In press - 16 Feb 2018

Fingerprint

Cognitive radio
Resource allocation
Nonlinear programming
Approximation algorithms
Throughput
Costs

Keywords

  • Approximation algorithms
  • Cognitive radio
  • Interference
  • MINLP
  • monotonic optimization
  • Optimization
  • Radio frequency
  • resource allocation
  • Resource management
  • Sensors
  • spectrum sensing
  • Throughput

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

@article{c890798d735147fb94ded43ef0473be2,
title = "Joint Spectrum Sensing and Resource Allocation in Multi-Band-Multi-User Cognitive Radio Networks",
abstract = "In this paper, the joint spectrum sensing and resource allocation problem is investigated in a multi-band-multi-user cognitive radio (CR) network. Assuming imperfect spectrum sensing information, our goal is to jointly optimize the sensing threshold and power allocation strategy such that the average total throughput of secondary users (SUs) is maximized. Additionally, the power of SUs is constrained to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a nonconvex mixed integer non-linear programming (MINLP) optimization problem. Our contribution in this paper is threefold. First, it is illustrated that the dimension of the nonconvex MINLP problem can be significantly reduced, which helps to re-formulate the optimization problem without resorting to integer variables. Second, it is demonstrated that the simplified formulation admits the canonical form of a monotonic optimization and an ∈-optimal solution can be achieved using the polyblock outer approximation algorithm. Third, a practical low-complexity spectrum sensing and resource allocation algorithm is developed to reduce the computational cost. Finally, the effectiveness of proposed algorithms is verified by simulations.",
keywords = "Approximation algorithms, Cognitive radio, Interference, MINLP, monotonic optimization, Optimization, Radio frequency, resource allocation, Resource management, Sensors, spectrum sensing, Throughput",
author = "Xu Wang and Sabit Ekin and Erchin Serpedin",
year = "2018",
month = "2",
day = "16",
doi = "10.1109/TCOMM.2018.2807432",
language = "English",
journal = "IEEE Transactions on Communications",
issn = "0096-1965",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Joint Spectrum Sensing and Resource Allocation in Multi-Band-Multi-User Cognitive Radio Networks

AU - Wang, Xu

AU - Ekin, Sabit

AU - Serpedin, Erchin

PY - 2018/2/16

Y1 - 2018/2/16

N2 - In this paper, the joint spectrum sensing and resource allocation problem is investigated in a multi-band-multi-user cognitive radio (CR) network. Assuming imperfect spectrum sensing information, our goal is to jointly optimize the sensing threshold and power allocation strategy such that the average total throughput of secondary users (SUs) is maximized. Additionally, the power of SUs is constrained to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a nonconvex mixed integer non-linear programming (MINLP) optimization problem. Our contribution in this paper is threefold. First, it is illustrated that the dimension of the nonconvex MINLP problem can be significantly reduced, which helps to re-formulate the optimization problem without resorting to integer variables. Second, it is demonstrated that the simplified formulation admits the canonical form of a monotonic optimization and an ∈-optimal solution can be achieved using the polyblock outer approximation algorithm. Third, a practical low-complexity spectrum sensing and resource allocation algorithm is developed to reduce the computational cost. Finally, the effectiveness of proposed algorithms is verified by simulations.

AB - In this paper, the joint spectrum sensing and resource allocation problem is investigated in a multi-band-multi-user cognitive radio (CR) network. Assuming imperfect spectrum sensing information, our goal is to jointly optimize the sensing threshold and power allocation strategy such that the average total throughput of secondary users (SUs) is maximized. Additionally, the power of SUs is constrained to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a nonconvex mixed integer non-linear programming (MINLP) optimization problem. Our contribution in this paper is threefold. First, it is illustrated that the dimension of the nonconvex MINLP problem can be significantly reduced, which helps to re-formulate the optimization problem without resorting to integer variables. Second, it is demonstrated that the simplified formulation admits the canonical form of a monotonic optimization and an ∈-optimal solution can be achieved using the polyblock outer approximation algorithm. Third, a practical low-complexity spectrum sensing and resource allocation algorithm is developed to reduce the computational cost. Finally, the effectiveness of proposed algorithms is verified by simulations.

KW - Approximation algorithms

KW - Cognitive radio

KW - Interference

KW - MINLP

KW - monotonic optimization

KW - Optimization

KW - Radio frequency

KW - resource allocation

KW - Resource management

KW - Sensors

KW - spectrum sensing

KW - Throughput

UR - http://www.scopus.com/inward/record.url?scp=85042200128&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85042200128&partnerID=8YFLogxK

U2 - 10.1109/TCOMM.2018.2807432

DO - 10.1109/TCOMM.2018.2807432

M3 - Article

AN - SCOPUS:85042200128

JO - IEEE Transactions on Communications

JF - IEEE Transactions on Communications

SN - 0096-1965

ER -