Linear Combining in Dependent α-Stable Interference

Ce Zheng*, Laurent Clavier, Malcom Egan, Troels Pedersen, Jean-Marie Gorce

*Corresponding author

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

Recently, there has been a proliferation of wireless
communication technologies in unlicensed bands for the Internet
of Things. A key question is whether these networks can coexist
given that they have different power levels, symbol periods,
and access protocols. The main challenge is to characterize
the impact of mutual interference arising from distinct uncoordinated
networks. It is known that when interferers form
a homogeneous Poisson point process and transmit only on a
single subband, the interference is often well-modeled by the
heavy-tailed α-stable distribution. In this paper, we focus on
the scenario where interferers transmit on multiple subbands.
Under a policy where each interferer independently accesses each
band with probability p, we provide an exact characterization of
the interference random vector. Exploiting this characterization,
we derive optimal linear combining weights and an analytical
approximation for the bit error rate (BER), accurate for large
transmit power. A key observation is that the expression for the
BER admits an interpretation in terms of an array gain and a
fractional diversity gain.
Original languageEnglish
Title of host publicationProceedings of ICC 2020
Number of pages6
Publication statusAccepted/In press - 2020

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Zheng, C., Clavier, L., Egan, M., Pedersen, T., & Gorce, J-M. (Accepted/In press). Linear Combining in Dependent α-Stable Interference. In Proceedings of ICC 2020