Practical Spectrum Aggregation for Secondary Networks with Imperfect Sensing

Haeyoung Lee, Youngwook Ko, Seiamak Vahid, Klaus Moessner

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
275 Downloads (Pure)

Abstract

We investigate a collision-sensitive secondary network that intends to opportunistically aggregate and utilize spectrum of a primary network to achieve higher data rates. In opportunistic spectrum access with imperfect sensing of idle primary spectrum, secondary transmission can collide with primary transmission. When the secondary network aggregates more channels in the presence of the imperfect sensing, collisions could occur more often, limiting the performance obtained by spectrum aggregation. In this context, we aim to address a fundamental query, that is, how much spectrum aggregation is worthy with imperfect sensing. For collision occurrence, we focus on two different types of collision: one is imposed by asynchronous transmission; and the other by imperfect spectrum sensing. The collision probability expression has been derived in closed-form with various secondary network parameters: primary traffic load, secondary user transmission parameters, spectrum sensing errors, and the number of aggregated sub-channels. In addition, the impact of spectrum aggregation on data rate is analysed under the constraint of collision probability. Then, we solve an optimal spectrum aggregation problem and propose the dynamic spectrum aggregation approach to increase the data rate subject to practical collision constraints. Our simulation results show clearly that the proposed approach outperforms the benchmark that passively aggregates sub-channels with lack of collision awareness.
Original languageEnglish
Number of pages11
JournalIEEE Transactions on Vehicular Technology
Early online date06 Aug 2015
DOIs
Publication statusPublished - 2016

Keywords

  • spectrum aggregation

Fingerprint

Dive into the research topics of 'Practical Spectrum Aggregation for Secondary Networks with Imperfect Sensing'. Together they form a unique fingerprint.

Cite this