Dynamic e-ICIC using Moving Average Crossover

Yuri Melo,Tarcisio Maciel,Vicente Sousa Jr

doi:10.14209/jcis.2019.9

Yuri Melo, Tarcisio Maciel + Show 1 more

Open Access

https://doi.org/10.14209/jcis.2019.9

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Abstract

Heterogeneous Networks (HetNets) are considered a technology option capable of improving system capacity and spatial spectrum reuse. However, high spectrum reuse causes high inter-cell interference among macro and small cells. Almost Blank Subframe (ABS) is a method of the Enhanced Inter-Cell Interference Coordination (e-ICIC) framework proposed for LTE systems as a means to mitigate interference among macro and small cells. ABS mutes some of macro cell transmissions in selected subframes to reduce interference to small cells, orthogonalizing macro and small cell transmissions in time-domain. In this work, we use Moving Average Crossover (MAC) based on trading know-how to propose a new dynamic ABS e-ICIC algorithm. Using system-level simulations, we attest that the proposed algorithm outperforms traditional e-ICIC by 6.4% in terms of capacity.

Highlights

Heterogeneous Networks (HetNets) are considered a technology option capable of improving system capacity and spatial spectrum reuse
Cum,akcro = B log2 1 + γum,akcro, where B is the channel bandwidth, u is a User Equipment (UE) in the macro cell with u ∈ {1, 2, . . . , U}, k is the subframe index, and γum,akcro is the macro cell Signal to Interference-plus-Noise Ratio (SINR) calculated as: γum,akcro =
In order to calculate the mean capacity for small cells, we define four scenarios: (i) Homogeneous (20 UEs uniformly distributed at each small cell area); (ii) Heterogeneous; (iii) Heterogeneous with fixed Almost Blank Subframe (ABS)

Summary

Scheduling policy

D is the distance between the transmitter and the receiver in meters. Cum,akcro = B log2 1 + γum,akcro , where B is the channel bandwidth, u is a UE in the macro cell with u ∈ {1, 2, . U}, k is the subframe index, and γum,akcro is the macro cell Signal to Interference-plus-Noise Ratio (SINR) calculated as: γum,akcro =. With hu,k being the channel coefficient (comprising pathloss, shadowing, and small scale fading); t, t ∈ {1, 2, . T } are indices for small cells; and η is the Additive White Gaussian With hu,k being the channel coefficient (comprising pathloss, shadowing, and small scale fading); t, t ∈ {1, 2, . . . , T } are indices for small cells; and η is the Additive White Gaussian

Ns f U capacity is computed as Cmmeaacnro

Moving Average

Findings

TABLE II