On the Distributed Resource Allocation of MIMO Cognitive Radio Networks

Abstract

One of the key challenges of cognitive radio networks is the design of efficient resource allocation schemes. Here we propose a distributed resource allocation algorithm for an underlay multiple-input multiple-output (MIMO) cognitive radio network. To reduce the complexity and cost, we introduce two different antenna selection techniques to allow the secondary communication via a single radio frequency (RF) chain. We show that the proposed distributed algorithm approaches the centralized performance while reducing the delay and overhead. Moreover, the simulation results compare the performance of the two proposed techniques showing their merits and demerits. The results show that the proposed algorithm achieves high throughput with low complexity.

A rate‐maximizing spectrum sharing algorithm for cognitive radio networks with generic resource constraints

“…In the work of Tanab et al, 18 the authors proposed a distributed resource allocation scheme for multiple-input-multiple-output CRNs. The spectrum sharing scheme in the work of Lopez-Ramos et al 17 aimed at maximizing the throughput (sum-rate) of the CRN while protecting the PU through an average interference constraint.…”

“…The spectrum sharing scheme in the work of Lopez‐Ramos et al aimed at maximizing the throughput (sum‐rate) of the CRN while protecting the PU through an average interference constraint. In the work of Tanab et al, the authors proposed a distributed resource allocation scheme for multiple‐input–multiple‐output CRNs. The proposed scheme is based on antenna selection at the transmitter and receiver sides.…”