Abstract

Emergence of shared spectrum, such as the 3.5-GHz citizen broadband radio service (CBRS) band in the U.S., promises to broaden the mobile operator ecosystem and lead to proliferation of small cell deployments. We consider the inter-operator interference problem that arises when multiple small cell networks access the shared spectrum. Towards this end, we take a novel communication-free approach that seeks implicit coordination between operators without explicit communication. The key idea is for each operator to sense the spectrum through its mobiles to be able to model the channel vacancy distribution and extrapolate it for the next epoch. We use reproducing kernel Hilbert space kernel embedding of channel vacancy and predict it by vector-valued regression. This predicted value is then relied on by each operator to perform independent but optimal channel assignment to its base stations taking traffic load into account. Via numerical results, we show that our approach, aided by the above channel vacancy forecasting, adapts the spectrum allocation over time as per the traffic demands and more crucially, yields as good as or better performance than a coordination-based approach, even without accounting the overhead of the latter.

Highlights

  • Mobile data traffic continues to grow rapidly and scaling the capacity of mobile networks to meet this demand is a key driver for the emerging 5G mobile networks

  • Middle tier users access the spectrum in 10 MHz chunks using Priority Access Licenses obtained for a medium term (3 years) via auctions

  • (§VI) Via an extensive set of numerical results, we show that our approach forecasts channel vacancy with good accuracy

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Summary

INTRODUCTION

Mobile data traffic continues to grow rapidly and scaling the capacity of mobile networks to meet this demand is a key driver for the emerging 5G mobile networks. We consider the inter-operator interference management problem that arises when multiple small cell network operators access shared spectrum (e.g., as GAA users in the CBRS 3.5 GHz band). While having the cloud-based/centralized SAS mediate access to shared spectrum for interference protection to incumbents and higher tier users is essential, using it to coordinate spectrum sharing among the same tier users (e.g., GAA users in CBRS) as suggested in [8], [9] limits dynamic and fine-grained spectrum use. Another approach would be to have operators exchange their respective spectrum usage information to base their individual interference management. The two sections describe the system model and formally state the problem being tackled

SYSTEM MODEL
FORMAL DESCRIPTION
Channel Vacancy
Spatial Map of Channel Vacancy
Sensing and Feedback Overhead
Statistics of Channel Vacancy Data
Reproducing Kernel Hilbert Spaces
Kernel Mean Embedding of Channel Vacancy
CHANNEL ASSIGNMENT
Benchmark
Expected Value and Variance of Subcarrier Vacancy
Error Performance of Kernel-based Extrapolation
Spectrum Efficiency Performance
Impact of Erroneous Feedback
RELATED WORK
VIII. CONCLUSIONS
Proof of Theorem 1
Sn2c nc
Full Text
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