Optimal resource allocation for downlink OFDM-Based cognitive radio networks

Xu Wang, Sabit Ekin, Erchin Serpedin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we study the downlink resource allocation (RA) problem in orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) networks. Our goal is to maximize the aggregated capacity of secondary users (SUs). In addition, the power of SUs is controlled to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a non-convex mixed integer non-linear programming (MINLP) optimization problem. In this paper, it is illustrated that the non-convex MINLP formulation admits a special structure and the optimal solution can be always achieved using standard convex optimization techniques under a general and practical assumption. In particular, the subgradient method is adopted to address the problem in the dual domain. The effectiveness of the proposed algorithms is verified by simulations.

Original languageEnglish
Title of host publication2017 International Symposium on Networks, Computers and Communications, ISNCC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509042593
DOIs
Publication statusPublished - 18 Oct 2017
Event2017 International Symposium on Networks, Computers and Communications, ISNCC 2017 - Marrakech, Morocco
Duration: 16 May 201718 May 2017

Other

Other2017 International Symposium on Networks, Computers and Communications, ISNCC 2017
CountryMorocco
CityMarrakech
Period16/5/1718/5/17

Fingerprint

Nonlinear programming
Cognitive radio
Orthogonal frequency division multiplexing
Resource allocation
Convex optimization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture

Cite this

Wang, X., Ekin, S., & Serpedin, E. (2017). Optimal resource allocation for downlink OFDM-Based cognitive radio networks. In 2017 International Symposium on Networks, Computers and Communications, ISNCC 2017 [8072008] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISNCC.2017.8072008

Optimal resource allocation for downlink OFDM-Based cognitive radio networks. / Wang, Xu; Ekin, Sabit; Serpedin, Erchin.

2017 International Symposium on Networks, Computers and Communications, ISNCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 8072008.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, X, Ekin, S & Serpedin, E 2017, Optimal resource allocation for downlink OFDM-Based cognitive radio networks. in 2017 International Symposium on Networks, Computers and Communications, ISNCC 2017., 8072008, Institute of Electrical and Electronics Engineers Inc., 2017 International Symposium on Networks, Computers and Communications, ISNCC 2017, Marrakech, Morocco, 16/5/17. https://doi.org/10.1109/ISNCC.2017.8072008
Wang X, Ekin S, Serpedin E. Optimal resource allocation for downlink OFDM-Based cognitive radio networks. In 2017 International Symposium on Networks, Computers and Communications, ISNCC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 8072008 https://doi.org/10.1109/ISNCC.2017.8072008
Wang, Xu ; Ekin, Sabit ; Serpedin, Erchin. / Optimal resource allocation for downlink OFDM-Based cognitive radio networks. 2017 International Symposium on Networks, Computers and Communications, ISNCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017.
@inproceedings{69218f80dc0b492eae21155ead7e2f6f,
title = "Optimal resource allocation for downlink OFDM-Based cognitive radio networks",
abstract = "In this paper, we study the downlink resource allocation (RA) problem in orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) networks. Our goal is to maximize the aggregated capacity of secondary users (SUs). In addition, the power of SUs is controlled to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a non-convex mixed integer non-linear programming (MINLP) optimization problem. In this paper, it is illustrated that the non-convex MINLP formulation admits a special structure and the optimal solution can be always achieved using standard convex optimization techniques under a general and practical assumption. In particular, the subgradient method is adopted to address the problem in the dual domain. The effectiveness of the proposed algorithms is verified by simulations.",
author = "Xu Wang and Sabit Ekin and Erchin Serpedin",
year = "2017",
month = "10",
day = "18",
doi = "10.1109/ISNCC.2017.8072008",
language = "English",
booktitle = "2017 International Symposium on Networks, Computers and Communications, ISNCC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Optimal resource allocation for downlink OFDM-Based cognitive radio networks

AU - Wang, Xu

AU - Ekin, Sabit

AU - Serpedin, Erchin

PY - 2017/10/18

Y1 - 2017/10/18

N2 - In this paper, we study the downlink resource allocation (RA) problem in orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) networks. Our goal is to maximize the aggregated capacity of secondary users (SUs). In addition, the power of SUs is controlled to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a non-convex mixed integer non-linear programming (MINLP) optimization problem. In this paper, it is illustrated that the non-convex MINLP formulation admits a special structure and the optimal solution can be always achieved using standard convex optimization techniques under a general and practical assumption. In particular, the subgradient method is adopted to address the problem in the dual domain. The effectiveness of the proposed algorithms is verified by simulations.

AB - In this paper, we study the downlink resource allocation (RA) problem in orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) networks. Our goal is to maximize the aggregated capacity of secondary users (SUs). In addition, the power of SUs is controlled to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a non-convex mixed integer non-linear programming (MINLP) optimization problem. In this paper, it is illustrated that the non-convex MINLP formulation admits a special structure and the optimal solution can be always achieved using standard convex optimization techniques under a general and practical assumption. In particular, the subgradient method is adopted to address the problem in the dual domain. The effectiveness of the proposed algorithms is verified by simulations.

UR - http://www.scopus.com/inward/record.url?scp=85032291800&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85032291800&partnerID=8YFLogxK

U2 - 10.1109/ISNCC.2017.8072008

DO - 10.1109/ISNCC.2017.8072008

M3 - Conference contribution

BT - 2017 International Symposium on Networks, Computers and Communications, ISNCC 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -