Capacity scaling limits of cognitive multiple access networks

Abstract

Introduction The ever-increasing interest and dependence of our society, industry, and service sectors in and on wireless telecommunication technologies have transformed the electromagnetic radio spectrum into one of the most precious common wireless communication resources. In particular, efficient use of the radio frequency spectrum has recently become a widespread goal of prime importance to introduce and accommodate nextgeneration wireless applications and services, and thereby to unlock the potential of industry and service sectors for product innovation and useful intellectual property generation. However, some spectrum occupancy measurements in the early 2000s indicated, perhaps as a positive and research-provocative finding, that most currently allocated frequency bands are both spatially and temporally underutilized [3]. It was also soon discovered that this is mainly a predicament of the conventional command-and-control approach for spectrum sharing [1, 7]. This spectrum scarcity problem is a fundamental bottleneck towards accommodating 4G and beyond 4G wireless networks as well as their associated services in today’s already “vastly crowded” radio spectrum [5]. Out of these forward-looking considerations and observations, cognitive radio technology has emerged as a promising remedy for the spectrum scarcity problem both in academia and industry. The idea underpinning the cognitive radio technology to alleviate the spectrum scarcity problem is to allow cognitive radio users, also called secondary users (SUs), to opportunistically share underutilized frequency bands with the legacy users, also called primary users (PUs), as long as the PUs’ quality of service (QoS) requirements are satisfied. To this end, the design of interference management and spectrum sharing mechanisms, for regulating performance degrading effects of cognitive radio networks (CRNs) on the primary networks, are projected to be the main challenge towards successful implementation of CRNs.