from Part III - Resource Allocation and Networking in C-RANs
Published online by Cambridge University Press: 23 February 2017
Introduction
The spectrum is becoming an increasingly scarce resource, owing to the emergence of a plethora of bandwidth-intensive and delay-critical applications (e.g. multimedia streaming, video conferencing, and gaming). To achieve the gigabit data rates required by next-generation wireless systems, we need to manage efficiently the interference among a multitude of wireless devices, most of which have limited computational capability. Central to interference management are spectrum-sharing policies, which specify when and at which power level each device should access the spectrum. Given the heterogeneity and the huge number of distributed wireless devices, it is computationally hard to design efficient spectrum sharing policies.
Cloud-RANs present a promising network architecture for designing spectrum-sharing policies. They consist of two components, a pool of baseband processing units (BBUs) and remote radio heads (RRHs), and allocate most demanding computations to the BBU pool (i.e., the “cloud”) [1-7]. In this way, C-RANs open up opportunities for designing efficient (even optimal) spectrum-sharing protocols. However, these opportunities come with the following challenges in C-RANs [1-7]:
How to allocate the computations between the BBU pool and the RRHs and minimize message exchange between them?
How to cope with dynamic entry and exit in large networks?
How to support the delay-sensitive applications that constitute amajority of the traffic in C-RANs?
This chapter presents advances made in the past years on a systematic design methodology for spectrum-sharing protocols that are particularly suitable for C-RANs. The spectrum-sharing protocols designed by the presented methodology can be implemented naturally in two phases:
• the first phase, of determining the optimal network operating point, which requires
• most computation and can be done in the BBU pool; and
• the second, phase of distributed implementation by RRHs with very limited computational capability.
Requiring limited message exchange between the BBU pool and the RRHs, the presented methodology results in provably optimal spectrum-sharing policies for C-RANs in interference-limited scenarios. More importantly, the presented methodology is general and can flexibly reconfigure the BBU pool to compute different optimal operating points in a variety of different C-RAN deployment scenarios.
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