A Survey of Radio Resource Management in Cognitive Radio Networks

Background

The data rates in wired and wireless networks are driven by Moore’s Law and are thus rising approximately tenfold, every five years (Zhang, 2011). Conversely, the requirements for multimedia high rate transmissions in Information and Communications Technology (ICT) drive the greatly increasing power consumption. According to a recent Ericsson research report (Ericsson Press Release, 2008), energy costs account for as much as half of a mobile operators operating expenses. The price paid for the enormous energy growth is a doubling of the power consumption in cellular networks infrastructure (base stations and core network) every 4–5 years. This was is about 60 TWh (billion kWh) in 2007. The radio access network accounts for 80% of this energy consumption (GreenComm, 2009). Most importantly, currently 3% of energy world-wide is consumed by ICT infrastructure. This causes about 2% of CO2 emissions world-wide, comparable to CO2 emissions by airplanes or one quarter of the world-wide CO2 emissions by cars (W-GREEN, 2008).

The steadily rising energy cost and the need to reduce global CO2 emission to protect our environment are economic and ecological drivers for the consideration of energy consumption in all fields of our manufacturing and daily lives. Therefore, radio networking solutions that improve energy efficiency, as well as resource efficiency (green communications), are of benefit to the global environment. It also makes commercial sense for telecommunication operators supporting sustainable and profitable businesses. Within the framework of “green communications,” a number of paradigm-shifting technical approaches can be expected. These include, but are not limited to, energy-efficient network architecture and protocols, energy-efficient wireless transmission techniques (e.g., reduced transmission power and reduced radiation), cross-layer optimization methods, and opportunistic spectrum sharing without causing harmful interference pollution (i.e., green spectrum) (Zhang, 2011).

Cognitive radio (Mitola, 1999; Haykin, 2005) is one of the best candidates to achieve the targets of green communications. CR is a promising radio access method to increase resource utilization by exploiting unused or low utilization spectrum which has been already authorized to primary systems. Traditional wireless technologies allocate the wireless resources statically, whilst CR technology works in a sensing, learning, reasoning and acting manner, and hence allocates the resource dynamically. CR system is expected to dynamically allocate the power to the users who can use it most efficiently in dynamically changing environments. CR users adapt to the dynamic radio environments, then make decisions on their operational parameters, such as working spectrum, transmission power, time slot and even modulation and coding type. In CR frameworks, future wireless devices will not operate on statically assigned resources, but dynamically acquire spectrum according to the spectral environment and allocate the power/timeslot/code in a most efficient way, by which the resource-efficiency and energy-efficiency of the CR system will be eventually increased.

Secondary Users (SUs) of CR systems opportunistically lease spare spectrum from Primary Users (PUs), which have the exclusive right to use the spectrum, without disturbing the PUs’ operations. In this manner, cognitive networks are envisioned to maximize the spectrum utilization and use the radio resources efficiently via heterogeneous wireless architectures. To make users utilize wireless resources efficiently, one of the main challenges in cognitive networks is realizing the dynamic resource management.