Effects of Base-Station Spatial Interdependence on Interference Correlation and Network Performance
Juan Wen, Min Sheng, Kaibin Huang, Jiandong Li

TL;DR
This paper investigates how spatial interdependence among base stations, modeled as clustering, affects interference correlation and network performance, revealing that clustering increases interference correlation and degrades performance, but can be mitigated with a correlation-aware retransmission scheme.
Contribution
It introduces a Poisson clustered process model to quantify the impact of base station clustering on interference correlation and network performance, proposing a correlation-aware retransmission scheme.
Findings
Clustering increases interference correlation levels.
Interference correlation degrades network performance.
A correlation-aware retransmission scheme can improve performance.
Abstract
The spatial-and-temporal correlation of interference has been well studied in Poisson networks where the interfering base stations (BSs) are independent of each other. However, there exists spatial interdependence including attraction and repulsion among the BSs in practical wireless networks, affecting the interference distribution and hence the network performance. In view of this, by modeling the network as a Poisson clustered process, we quantify the effects of spatial interdependence among BSs on the interference correlation and analytically prove that BS clustering increases the level of interference correlation. In particular, it is shown that the level increases as the attraction between the BSs increases. Furthermore, we study the effects of spatial interdependence among BSs on network performance with a retransmission scheme via considering heterogeneous cellular networks in…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Cooperative Communication and Network Coding · Advanced Wireless Network Optimization
