Downlink Channel Assignment and Power Control for Cognitive Radio Networks

• Published in: IEEE transactions on wireless communications 2008-08, Vol.7 (8), p.3106-3117
• Main Authors: ANH TUAN HOANG, LIANG, Ying-Chang
• Format: Article
• Language: English
• Subjects: Active control; Allocations; Applied sciences; Base stations; Bit error rate; Channel assignment; Channels; Cognitive radio; Decisions; Downlink; Exact sciences and technology; Frequency conversion; Frequency division multiaccess; Interference; Linear programming; Networks; Power control; Radio; Radio networks; Radiocommunication specific techniques; Radiocommunications; Signal to noise ratio; Studies; Subscribers; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; throughput maximization; Transmission and modulation (techniques and equipments); Wireless communication
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2008.070022

We consider a cognitive radio network in which a set of base stations make opportunistic spectrum access to support fixed-location wireless subscribers within their cells. The spectrum of interest is divided into independent channels using frequency division multiple access (FDMA) and is licensed to the operator of a primary network. Channel assignment and power control must be carried out in the cognitive network so that no excessive interference is caused to users of the primary network. We are interested in the downlink channel/power allocation problem for the cognitive radio network, with the objective of maximizing the total number of active subscribers that can be supported. Here, we assume that each subscriber of the cognitive network can be either active or idle and only active subscribers require downlink transmission. We first consider the case when global knowledge of all active subscribers is available for making control decisions. In that case, a downlink channel/power allocation scheme that maximizes the number of supported subscribers can be obtained by solving a mixed-integer linear programming. We also propose a suboptimal scheme that can be obtained at lower complexity based on a dynamic interference graph. We then consider the case when control decisions can only be made based on local knowledge of active subscribers within each cell. For that, we propose a scalable two-phase channel/power allocation scheme. Numerical results show the effectiveness of our proposed schemes.