Adapting cellular networks to whitespaces spectrum
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This document provides information about final year IEEE projects for 2015-2016, including contact details for Praveen Kumar. It also summarizes two wireless network projects adapting cellular networks to use TV white space spectrum. The first project proposes a novel base station design using many low-power transmitters to maximize throughput given the power-spectrum tradeoff in white spaces. The second analyzes the impact of spatial variability in white spaces availability and proposes spectrum-aware algorithms to optimize base station placement to improve network coverage.
Adapting cellular networks to whitespaces spectrum
- 1. NEXGEN TECHNOLOGY FINAL YEAR IEEE PROJECTS TITLES 2015-2016 CONTACT: PRAVEEN KUMAR. L (+91 – 9751442511, +91 – 9791938249) MAIL ID: sunsid1989@gmail.com, praveen@nexgenproject.com web:www.nexgenproject.com 1. Adapting Cellular Networks to Whitespaces Spectrum TV Whitespaces, recently opened up by the Federal Communications Commission (FCC) for unlicensed use, are seen as a potential cellular offload and/or standalone mechanism, especially in dense metros where the demand for throughput is high. In this paper, we use real data collected from whitespaces databases to empirically demonstrate features unique to whitespaces- power-spectrum tradeoff and spatial variation in spectrum availability. From this study, we conclude the need for whitespaces-specific adaptations to cellular networks so as to be able to extract maximum throughput and guarantee reliability. To tackle the effects of the power- spectrum tradeoff, we propose a novel base-station design that specifically uses low-power transmitters as a means to maximize throughput. This design co-locates and networks together many low-powered mode-I devices to act as a multiple-antenna array. We estimate the size of the array required to meet typical rate targets, and show that the array design significantly outperforms traditional designs in terms of throughput for a given cost. We then turn our attention to spatial variability and study its impact on the problem of locating base stations in a whitespaces network. Here, we propose spectrum-aware placement algorithms for whitespaces, which account for this spatial variability along with key parameters like user density. We show that such algorithms clearly outperform traditional placement algorithms and improve network coverage in this band.