Radio Environment Maps and Its Utility in Resource Management for Dynamic Spectrum Access Networks

Radio Environment Maps and Its Utility in Resource Management for Dynamic Spectrum Access Networks

Saptarshi Debroy (Hunter College, City University of New York, USA) and Mainak Chatterjee (University of Central Florida, USA)
DOI: 10.4018/978-1-5225-2023-8.ch002
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Abstract

Recent measurements on radio spectrum usage have revealed the abundance of under-utilized bands of spectrum that belong to licensed users. This necessitated the paradigm shift from static to dynamic spectrum access (DSA). Researchers argue that prior knowledge about occupancy of such bands, such as, Radio Environment Maps (REM) can potentially help secondary networks to devise effective strategies to improve utilization. In the chapter, we discuss how different interpolation and statistical techniques are applied to create REMs of a region, i.e., an estimate of primary spectrum usage at any arbitrary location in a secondary DSA network. We demonstrate how such REMs can help in predicting channel performance metrics like channel capacity, spectral efficiency, and secondary network throughput. We show how REMs can help to attain near perfect channel allocation in a centralized secondary network. Finally, we show how the REM can be used to perform multi-channel multi-hop routing in a distributed DSA network.
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Introduction

Radio spectrum allocation and management have traditionally followed a ‘command-and-control’ approach where chunks of spectrum are allocated for specific services under restrictive licenses. The restrictions specify the technologies to be used and the services to be provided, thereby constraining the ability to make use of new technologies and the ability to redistribute the spectrum to higher valued users. Over the past years, traditional approaches to spectrum management have been challenged by new insights into the actual use of spectrum. In most countries, all frequencies have been completely allocated to specific uses and spectrum appears to be a scarce resource within the current regulatory framework. Moreover, recent experimental studies have revealed that spectrum utilization is time and space dependent and that most parts of radio spectrum are highly underutilized (Shared Spectrum Company, 2007; Buddhikot, M., 2005; F. communications commission, 2004).

Such limitations have motivated a paradigm shift from static spectrum allocation towards a notion of dynamic spectrum management where secondary networks/users (non-license holders) can ‘borrow’ idle spectrum from those who primary networks/users (license holders) without causing harmful interference to the latter. Dynamic Spectrum Access (DSA) networks that utilize such unused spectrum holes within the licensed band have been proposed as a possible solution to the spectrum crisis. The idea is to detect times when a particular licensed band is unused and use it for transmission without causing interference to the licensed user. Secondary users equipped with cognitive radio enabled devices will facilitate such DSA where the cognitive radios continuously monitor the presence of primary users and opportunistically access the unused or under-utilized licensed bands (Akyildiz, I. F, 2006). However, the most important regulatory aspect of these networks is that the secondary nodes must not interfere with primary transmissions. Thus, when secondary nodes detect transmissions from primaries, they are mandated to relinquish those interfering channels immediately and switch to other non-interfering channels.

Due to the temporal and spatial fleetingness of spectrum occupancy, such reactive nature of secondary networks is insufficient for desired utilization of under-used licensed spectrum. Researchers have argued that a prior knowledge of the possible transmission activities of the primaries can allow the secondary nodes to effectively access the available resource and predict the expected radio and network performances for quality of service (QoS) provisioning in secondary networks. Such prior knowledge would also help the secondary networks in finding better routes from a source to a destination where route existence and quality are ever changing with primary activity. Thus, there is a need to proactively estimate the spectrum usage at any arbitrary location and then extend that for predicting the nature of spectrum utilization in a region of interest. The recent ruling by FCC (FCC, 2007) also necessitates the need for secondary networks to create, manage and refer to spectrum usage databases for secondary access opening new discussions on design, implementation techniques, and capabilities of such spectrum usage databases.

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