Modeling and Analysis of Multi-Tier Clustered Millimeter-Wave Cellular Networks With User Classification for Large-Scale Hotspot Area

Abstract

This paper focuses on a comprehensive framework design and performance analysis for a largescale hotspot communication scenario where there exist large number of clustered pico base stations (P-BSs) and femto BSs (F-BSs) working on millimeter-Wave (mm-Wave). For such realistic hotspots' deployment, to exploit the coupling between user equipments (UEs) and base stations (BSs), we model the geographical centers of UE hotspots as independent PPP around which UEs, P-BSs and F-BSs are scattered and form independent and non-homogeneous Poisson cluster processes (PCPs). However, with clustered P-BSs and F-BSs, the UEs would experience the severer intra-cluster interference so that the performance is degraded greatly. To overcome this problem in clustered networks, an effective interference management scheme is proposed by using the ratio of the first and second nearest distances of a typical UE from P-BSs so that a typical UE can be classified as either cluster-center UEs (CCUEs) or cluster-edge UEs (CEUEs). Correspondingly, the total available spectrum band is divided as CCUE-band and CEUE-band, which are occupied by P-BSs associated with CCUEs and CEUEs, respectively. Unlike P-BSs, the F-BSs randomly access the CEUE-band and CCUE-band with a given access portion factor. By using the method from stochastic geometry and the distinguishing feature of mm-Wave, such as directional beamforming with sectored antenna model and modified line of sight ball model for blockage, the UE association probability and Laplace transforms of interference are derived. This yields the derivations of downlink transmission rates. The numerical results show that the proposed clustered heterogeneous scheme with the cluster-UE classification outperforms the traditional ones without the UE classification. This approach not only captures the UE-BS coupling and the non-homogeneous nature of multi-tier networks, but also restricts the severe intra-cluster interference due to clustered BSs.

Hybrid computational and real data-based positioning of small cells in 5G networks

“… Jia, Ji & Chen (2019) denotes another mathematically complex problem: the intra-clustering organization and interference issues of 5G millimeter wave (mmWave) networks. Given that mmWave has very little coverage, the usage of Pico cells and Femto cells proves to be necessary.…”

Multi-UAV Assisted Multi-Tier Millimeter-Wave Cellular Networks for Hotspots With 2-Tier and 4-Tier Network Association

“…With the fact h i,t ∼ Γ (N i,t , 1/N i,t ) and the derivation in [36] and [48]- [49], for a constant η > 0, the probability P (h i,t > η) is approximated by P (h i,t > η) =1 − 1 − e −ζ i,t η N i,t . P i,t (τ ) is given by PiG M i .…”

Unified Derivation of Optimal Feedback Rate in Downlink Cellular Systems With Multi-Antenna Base Stations

“…Real can be closely approximated as a linear function of P 2 α . Using big-O notation [40], it follows that ψ SU (P) = O P 2 α (33) as P → 0. In conclusion, from (27), (29), and (33), it is likely that B * Real logarithmically increases with P in the low SNR region; then, the rate of increase is gradually reduced until it is bounded by (N − 1) log 2 (1 + T c • ψ upper SU ).…”

“…This figure shows that both the upper and lower bounds are very tight regardless of the value of the SNR. From (30) and (33), ψ SU (P) can be approximated as ψ SU (P) ≈ C • P . Then, applying (27), we have as P approaches 0.…”

“…In [31], a cyber insurance framework for physical layer security was developed using homogeneous α−Ginibre point processes for BS and eavesdropper locations. In [32], [33], stochastic geometry was used to model heterogeneous networks in mmWave communication. It has also been utilized to model the random locations of the users performing machine-type communications [34], [35].…”