Interference Alignment in Two-Tier Randomly Distributed Heterogeneous Wireless Networks Using Stochastic Geometry Approach
| Autor: | Tharmalingam Ratnarajah, Faheem A. Khan, Jiang Xue, Yi Luo |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer Networks and Communications
Computer science TK Distributed computing 0211 other engineering and technologies Heterogeneous wireless network 02 engineering and technology Multiplexing Poisson point process Computer Science::Networking and Internet Architecture 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Throughput (business) Computer Science::Information Theory Stochastic geometry models of wireless networks 021103 operations research T1 Wireless network business.industry ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS Transmitter 020206 networking & telecommunications Computer Science Applications TA Control and Systems Engineering business Stochastic geometry Information Systems Computer network |
| Zdroj: | Luo, Y, Ratnarajah, T, Xue, J & Khan, F A 2017, ' Interference Alignment in Two-Tier Randomly Distributed Heterogeneous Wireless Networks Using Stochastic Geometry Approach ', IEEE Systems Journal . https://doi.org/10.1109/JSYST.2017.2654688 |
| ISSN: | 2373-7816 1932-8184 |
| DOI: | 10.1109/jsyst.2017.2654688 |
| Popis: | With the massive increase in wireless data traffic in recent years, multi-tier wireless networks have been deployed to provide much higher capacities and coverage. However, heterogeneity of wireless networks bring new challenges for interference analysis and coordination due to spatial randomly distributed transmitters. In this paper, we present a distance dependent interference alignment (IA) approach for a generic 2-tier heterogeneous wireless network, where transmitters in the first and second tiers are distributed as Poisson Point Process (PPP) and Poisson Cluster Process (PCP) respectively. The feasibility condition of the IA approach is used to find upper bound of the number of interference streams that can be aligned. The proposed IA scheme maximizes the second-tier throughput by using the trade-off between signal-to-interference ratio and multiplexing gain. It is shown that acquiring accurate knowledge of the distance between the receiver in the second-tier and the nearest cross-tier transmitter only brings insignificant throughput gain compared to statistical knowledge of distance. Furthermore, the remaining cross-tier and inter-cluster interferences are modeled and analyzed using stochastic geometry technique. Numerical results validate the derived expressions of success probabilities and throughput, and show that the distance dependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect. |
| Databáze: | OpenAIRE |
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