Pricing-Based Multiresource Allocation in OFDMA Cognitive Radio Networks: An Energy Efficiency Perspective

Abstract

Both the orthogonal frequency-division multiple access (OFDMA) and cognitive radio (CR) technologies offer great flexibility and feasibility for future green wireless communications. In this paper, an energy-efficient multiresource-allocation scheme is proposed for OFDMA CR networks (CRNs) with multiple secondary transmitters (STs). To maximize the energy efficiency (EE) and guarantee the primary transmitter's (PT's) quality-of-service (QoS) requirement, a linear pricing technique is employed to handle both the inter-ST coupling (the spectrum competition among STs) and intra-ST coupling (the correlation between the available transmit power and assigned subchannels for each ST). Furthermore, a distributed algorithm is devised to harvest the multiresource and multiuser gains, and the multiresource allocation is transformed to 1-D pricing-factor profile searching. Simulation results demonstrate that the proposed strategy brings higher EE. Additionally, by adjusting the pricing factors, a different performance can be achieved by the STs with different priorities.