Spectrum Leasing and Cooperative Resource Allocation in Cognitive OFDMA Networks

TL;DR

This paper proposes a joint optimization framework for cooperative spectrum leasing in cognitive OFDMA networks, enabling secondary users to act as relays or transmit independently, thereby improving network throughput.

Contribution

It introduces a novel joint optimization model for spectrum leasing and cooperation strategies, with a polynomial-time algorithm for near-optimal solutions in cognitive OFDMA systems.

Findings

Optimal strategy is exclusive relay or transmit mode per subcarrier.

The proposed algorithm significantly improves network performance.

Cooperation strategies differ from conventional single-channel spectrum leasing.

Abstract

This paper considers a cooperative OFDMA-based cognitive radio network where the primary system leases some of its subchannels to the secondary system for a fraction of time in exchange for the secondary users (SUs) assisting the transmission of primary users (PUs) as relays. Our aim is to determine the cooperation strategies among the primary and secondary systems so as to maximize the sum-rate of SUs while maintaining quality-of-service (QoS) requirements of PUs. We formulate a joint optimization problem of PU transmission mode selection, SU (or relay) selection, subcarrier assignment, power control, and time allocation. By applying dual method, this mixed integer programming problem is decomposed into parallel per-subcarrier subproblems, with each determining the cooperation strategy between one PU and one SU. We show that, on each leased subcarrier, the optimal strategy is to let a SU exclusively act as a relay or transmit for itself. This result is fundamentally different from the conventional spectrum leasing in single-channel systems where a SU must transmit a fraction of time for itself if it helps the PU's transmission. We then propose a subgradient-based algorithm to find the asymptotically optimal solution to the primal problem in polynomial time. Simulation results demonstrate that the proposed algorithm can significantly enhance the network performance.