Resource Allocation Algorithm for Multi‐cell Cognitive Radio Networks with Imperfect Spectrum Sensing and Proportional Fairness

Abstract

This paper addresses the resource allocation (RA) problem in multi-cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered-such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP-hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub-gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.

Comparison of two methodologies on spectrum sharing information for unlicensed use in the 6‐GHz band

“…This is defined as the summation of the on-tune rejection (OTR) and the off-frequency rejection (OFR) as follows: FDR(n ch ) k = OTR + OFR(Δ𝑓 ), where Δf is the difference between center frequencies of CF(n ch ) for RLAN and f k for k-th FWS [31]. Here, the OTR and OFR are defined as follows [32]:…”

“…In this process, the AFCSP may include specific procedures to maximize the service quality of the RLAN. There may be diverse approaches that can be adopted by the AFCSP to optimize the RLAN performance while complying with EIRP max [33,34]. One of these approaches involves optimally scheduling the resources to the stations and allocating the power while considering with the channel quality in order to maximize the network capacity.…”